U.S. patent application number 15/858288 was filed with the patent office on 2019-02-28 for technologies for automated network congestion management.
The applicant listed for this patent is Intel Corporation. Invention is credited to Mohan J. Kumar, Murugasamy K. Nachimuthu.
Application Number | 20190068521 15/858288 |
Document ID | / |
Family ID | 65434219 |
Filed Date | 2019-02-28 |
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United States Patent
Application |
20190068521 |
Kind Code |
A1 |
Kumar; Mohan J. ; et
al. |
February 28, 2019 |
TECHNOLOGIES FOR AUTOMATED NETWORK CONGESTION MANAGEMENT
Abstract
Technologies for congestion management include multiple storage
sleds, compute sleds, and other computing devices in communication
with a resource manager server. The resource manager server
discovers the topology of the sleds and one or more layers of
network switches that connect the sleds. The resource manager
server constructs a model of network connectivity between the sleds
and the switches based on the topology, and determines an
oversubscription of the network based on the model. The
oversubscription is based on available bandwidth for the layer of
switches and maximum potential bandwidth used by the sleds. The
resource manager server determines bandwidth limits for each sled
and programs each sled with the corresponding bandwidth limit. Each
sled enforces the programmed bandwidth limit. Other embodiments are
described and claimed.
Inventors: |
Kumar; Mohan J.; (Aloha,
OR) ; Nachimuthu; Murugasamy K.; (Beaverton,
OR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Intel Corporation |
Santa Clara |
CA |
US |
|
|
Family ID: |
65434219 |
Appl. No.: |
15/858288 |
Filed: |
December 29, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62584401 |
Nov 10, 2017 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H05K 7/18 20130101; H04L
43/065 20130101; H04L 49/40 20130101; G06F 2201/885 20130101; G06F
11/3006 20130101; H05K 7/20736 20130101; H04L 41/0816 20130101;
G06F 11/3409 20130101; H04L 63/0428 20130101; G06F 15/7867
20130101; G06F 2200/201 20130101; H04L 43/16 20130101; G06F 11/3442
20130101; G06F 21/105 20130101; G06Q 30/0283 20130101; H04L 41/044
20130101; H05K 7/1498 20130101; G06F 9/5088 20130101; G06F 2201/86
20130101; H05K 7/1489 20130101; G06F 9/5061 20130101; G06F 15/7807
20130101; H04L 43/0876 20130101; G06F 1/20 20130101; G06F 9/44
20130101; H04L 41/5025 20130101; H04L 67/1008 20130101; G06F
13/4022 20130101; H04L 41/0896 20130101; B25J 15/0014 20130101;
Y02D 30/00 20180101; G06F 9/4856 20130101; G06F 1/183 20130101;
G06F 11/3466 20130101; Y02D 10/00 20180101; H04L 41/14 20130101;
G06N 3/063 20130101; G06Q 10/0631 20130101; H04L 41/5019 20130101;
G06F 9/505 20130101 |
International
Class: |
H04L 12/911 20060101
H04L012/911; H04L 12/751 20060101 H04L012/751; H04L 12/873 20060101
H04L012/873 |
Foreign Application Data
Date |
Code |
Application Number |
Aug 30, 2017 |
IN |
201741030632 |
Claims
1. A resource manager server for bandwidth allocation, the resource
manager server comprising: one or more processors; and one or more
memory devices having stored therein a plurality of instructions
that, when executed by the one or more processors, cause the
resource manager server to: discover a topology of a plurality of
sleds coupled to a layer of switches that are communicatively
coupled to the resource manager server; construct a model of
network connectivity between the plurality of sleds and the layer
of switches based on the topology; determine an oversubscription of
a network based on the model of network connectivity, wherein the
oversubscription is based on an available bandwidth for the layer
of switches and a maximum bandwidth of the plurality of sleds;
determine a bandwidth limit for each sled of the plurality of sleds
based on the oversubscription; and program each sled of the
plurality of sleds with the corresponding bandwidth limit.
2. The resource manager server of claim 1, wherein to construct the
model of network connectivity comprises to identify which sleds of
the plurality of sleds are connected to a particular switch of the
layer of switches.
3. The resource manager server of claim 1, wherein to determine the
oversubscription comprises to determine a network uplink
oversubscription for the layer of switches.
4. The resource manager server of claim 1, wherein to determine the
oversubscription comprises to determine a storage resource
oversubscription of the plurality of sleds.
5. The resource manager server of claim 1, wherein to program the
bandwidth limit for each sled comprises to communicate the
bandwidth limit to a network interface controller of the
corresponding sled.
6. The resource manager server of claim 1, wherein the one or more
memory devices have stored therein a plurality of instructions
that, when executed by the one or more processors, further cause
the resource manager server to: monitor a bandwidth utilization of
the plurality of sleds; determine whether the network is congested
based on the bandwidth utilization of the plurality of sleds; and
modify a bandwidth limit in response to a determination that the
network is congested.
7. The resource manager server of claim 6, wherein to monitor the
bandwidth utilization of the plurality of sleds comprises to
receive telemetry data from the plurality of sleds indicative of
the bandwidth utilized by each sled.
8. The resource manager server of claim 7, wherein to determine
whether the network is congested comprises to determine whether a
queue depth of the network exceeds a predetermined queue depth
limit for a predetermined amount of time.
9. The resource manager server of claim 8, wherein the queue depth
comprises a switch port queue depth, a network interface controller
queue depth, or a network stack queue depth.
10. The resource manager server of claim 6, wherein to modify the
bandwidth limit comprises to: identify a first sled of the
plurality of sleds associated with a high input rate flow; and
reduce an input rate of the bandwidth limit for the first sled.
11. One or more computer-readable storage media comprising a
plurality of instructions stored thereon that, in response to being
executed, cause a resource manager server to: discover a topology
of a plurality of sleds coupled to a layer of switches that are
communicatively coupled to the resource manager server in a
network; construct a model of network connectivity between the
plurality of sleds and the layer of switches based on the topology;
determine an oversubscription of the network based on the model of
network connectivity, wherein the oversubscription is based on an
available bandwidth for the layer of switches and a maximum
bandwidth of the plurality of sleds; determine a bandwidth limit
for each sled of the plurality of sleds based on the
oversubscription; and program each sled of the plurality of sleds
with the corresponding bandwidth limit.
12. The one or more computer-readable storage media of claim 11,
wherein to construct the model of network connectivity comprises to
identify which sleds of the plurality of sleds are connected to a
particular switch of the layer of switches.
13. The one or more computer-readable storage media of claim 11,
wherein to determine the oversubscription comprises to determine a
network uplink oversubscription for the layer of switches.
14. The one or more computer-readable storage media of claim 11,
wherein to determine the oversubscription comprises to determine a
storage resource oversubscription of the plurality of sleds.
15. The one or more computer-readable storage media of claim 11,
wherein to program the bandwidth limit for each sled comprises to
communicate the bandwidth limit to a network interface controller
of the corresponding sled.
16. The one or more computer-readable storage media of claim 11,
further comprising a plurality of instructions stored thereon that,
in response to being executed, cause the resource manager server
to: monitor a bandwidth utilization of the plurality of sleds;
determine whether the network is congested based on the bandwidth
utilization of the plurality of sleds; and modify a bandwidth limit
in response to determining that the network is congested.
17. The one or more computer-readable storage media of claim 16,
wherein to monitor the bandwidth utilization of the plurality of
sleds comprises to receive telemetry data from the plurality of
sleds indicative of the bandwidth utilized by each sled.
18. The one or more computer-readable storage media of claim 17,
wherein to determine whether the network is congested comprises to
determine whether a queue depth of the network exceeds a
predetermined queue depth limit for a predetermined amount of
time.
19. The one or more computer-readable storage media of claim 18,
wherein the queue depth comprises a switch port queue depth, a
network interface controller queue depth, or a network stack queue
depth.
20. The one or more computer-readable storage media of claim 16,
wherein to modify the bandwidth limit comprises to: identify a
first sled of the plurality of sleds associated with a high input
rate flow; and reduce an input rate of the bandwidth limit for the
first sled.
21. A resource manager server for bandwidth allocation, the
resource manager server comprising: means for discovering a
topology of a plurality of sleds coupled to a layer of switches
that are communicatively coupled to the resource manager server in
a network; means for constructing a model of network connectivity
between the plurality of sleds and the layer of switches based on
the topology; means for determining an oversubscription of the
network based on the model of network connectivity, wherein the
oversubscription is based on an available bandwidth for the layer
of switches and a maximum bandwidth of the plurality of sleds;
means for determining a bandwidth limit for each sled of the
plurality of sleds based on the oversubscription; and means for
programming each sled of the plurality of sleds with the
corresponding bandwidth limit.
22. A method for bandwidth allocation, the method comprising:
discovering, by a resource manager server of a network, a topology
of a plurality of sleds coupled to a layer of switches that are
communicatively coupled to the resource manager server;
constructing, by the resource manager server, a model of network
connectivity between the plurality of sleds and the layer of
switches based on the topology; determining, by the resource
manager server, an oversubscription of the network based on the
model of network connectivity, wherein the oversubscription is
based on an available bandwidth for the layer of switches and a
maximum bandwidth of the plurality of sleds; determining, by the
resource manager server, a bandwidth limit for each sled of the
plurality of sleds based on the oversubscription; and programming,
by the resource manager server, each sled of the plurality of sleds
with the corresponding bandwidth limit.
23. The method of claim 22, further comprising: monitoring, by the
resource manager server, a bandwidth utilization of the plurality
of sleds; determining, by the resource manager server, whether the
network is congested based on the bandwidth utilization of the
plurality of sleds; and modifying, by the resource manage server, a
bandwidth limit in response to determining that the network is
congested.
24. The method of claim 23, wherein monitoring the bandwidth
utilization of the plurality of sleds comprises receiving telemetry
data from the plurality of sleds indicative of the bandwidth
utilized by each sled.
25. The method of claim 24, wherein determining whether the network
is congested comprises determining whether a queue depth of the
network exceeds a predetermined queue depth limit for a
predetermined amount of time.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application claims the benefit Indian
Provisional Patent Application No. 201741030632, filed Aug. 30,
2017, and U.S. Provisional Patent Application No. 62/584,401, filed
Nov. 10, 2017.
BACKGROUND
[0002] Datacenters and other large computer networks typically
include multiple layers of switches. For example, servers may be
installed in racks, and each server in a rack may be connected to a
top-of-rack switch. Multiple top-of-rack switches may be connected
to an upstream switch, and so on. Therefore, communicating between
servers or other nodes in different racks may require traversing
multiple switch layers. Traversing each layer of switches may
introduce queuing latency.
BRIEF DESCRIPTION OF THE DRAWINGS
[0003] The concepts described herein are illustrated by way of
example and not by way of limitation in the accompanying figures.
For simplicity and clarity of illustration, elements illustrated in
the figures are not necessarily drawn to scale. Where considered
appropriate, reference labels have been repeated among the figures
to indicate corresponding or analogous elements.
[0004] FIG. 1 is a simplified diagram of at least one embodiment of
a data center for executing workloads with disaggregated
resources;
[0005] FIG. 2 is a simplified diagram of at least one embodiment of
a pod of the data center of FIG. 1;
[0006] FIG. 3 is a perspective view of at least one embodiment of a
rack that may be included in the pod of FIG. 2;
[0007] FIG. 4 is a side plan elevation view of the rack of FIG.
3;
[0008] FIG. 5 is a perspective view of the rack of FIG. 3 having a
sled mounted therein;
[0009] FIG. 6 is a is a simplified block diagram of at least one
embodiment of a top side of the sled of FIG. 5;
[0010] FIG. 7 is a simplified block diagram of at least one
embodiment of a bottom side of the sled of FIG. 6;
[0011] FIG. 8 is a simplified block diagram of at least one
embodiment of a compute sled usable in the data center of FIG.
1;
[0012] FIG. 9 is a top perspective view of at least one embodiment
of the compute sled of FIG. 8;
[0013] FIG. 10 is a simplified block diagram of at least one
embodiment of an accelerator sled usable in the data center of FIG.
1;
[0014] FIG. 11 is a top perspective view of at least one embodiment
of the accelerator sled of FIG. 10;
[0015] FIG. 12 is a simplified block diagram of at least one
embodiment of a storage sled usable in the data center of FIG.
1;
[0016] FIG. 13 is a top perspective view of at least one embodiment
of the storage sled of FIG. 12;
[0017] FIG. 14 is a simplified block diagram of at least one
embodiment of a memory sled usable in the data center of FIG. 1;
and
[0018] FIG. 15 is a simplified block diagram of a system that may
be established within the data center of FIG. 1 to execute
workloads with managed nodes composed of disaggregated
resources.
[0019] FIG. 16 is a simplified block diagram of an at least one
embodiment of a system for bandwidth allocation;
[0020] FIG. 17 is a simplified block diagram of at least one
embodiment of a computing device of FIG. 16;
[0021] FIG. 18 is a simplified block diagram of at least one
embodiment of an environment of the resource manager of FIGS. 16
and 17;
[0022] FIG. 19 is a simplified block diagram of at least one
embodiment of an environment of a sled of FIGS. 16 and 17;
[0023] FIG. 20 is a simplified flow diagram of at least one
embodiment of a method for bandwidth allocation that may be
executed by the resource manager server of FIGS. 16-18; and
[0024] FIG. 21 is a simplified flow diagram of at least one
embodiment of a method for bandwidth allocation that may be
executed by the sled of FIGS. 16-17 and 19.
DETAILED DESCRIPTION OF THE DRAWINGS
[0025] While the concepts of the present disclosure are susceptible
to various modifications and alternative forms, specific
embodiments thereof have been shown by way of example in the
drawings and will be described herein in detail. It should be
understood, however, that there is no intent to limit the concepts
of the present disclosure to the particular forms disclosed, but on
the contrary, the intention is to cover all modifications,
equivalents, and alternatives consistent with the present
disclosure and the appended claims.
[0026] References in the specification to "one embodiment," "an
embodiment," "an illustrative embodiment," etc., indicate that the
embodiment described may include a particular feature, structure,
or characteristic, but every embodiment may or may not necessarily
include that particular feature, structure, or characteristic.
Moreover, such phrases are not necessarily referring to the same
embodiment. Further, when a particular feature, structure, or
characteristic is described in connection with an embodiment, it is
submitted that it is within the knowledge of one skilled in the art
to effect such feature, structure, or characteristic in connection
with other embodiments whether or not explicitly described.
Additionally, it should be appreciated that items included in a
list in the form of "at least one A, B, and C" can mean (A); (B);
(C); (A and B); (A and C); (B and C); or (A, B, and C). Similarly,
items listed in the form of "at least one of A, B, or C" can mean
(A); (B); (C); (A and B); (A and C); (B and C); or (A, B, and
C).
[0027] The disclosed embodiments may be implemented, in some cases,
in hardware, firmware, software, or any combination thereof. The
disclosed embodiments may also be implemented as instructions
carried by or stored on a transitory or non-transitory
machine-readable (e.g., computer-readable) storage medium, which
may be read and executed by one or more processors. A
machine-readable storage medium may be embodied as any storage
device, mechanism, or other physical structure for storing or
transmitting information in a form readable by a machine (e.g., a
volatile or non-volatile memory, a media disc, or other media
device).
[0028] In the drawings, some structural or method features may be
shown in specific arrangements and/or orderings. However, it should
be appreciated that such specific arrangements and/or orderings may
not be required. Rather, in some embodiments, such features may be
arranged in a different manner and/or order than shown in the
illustrative figures. Additionally, the inclusion of a structural
or method feature in a particular figure is not meant to imply that
such feature is required in all embodiments and, in some
embodiments, may not be included or may be combined with other
features.
[0029] Referring now to FIG. 1, a data center 100 in which
disaggregated resources may cooperatively execute one or more
workloads (e.g., applications on behalf of customers) includes
multiple pods 110, 120, 130, 140, each of which includes one or
more rows of racks. As described in more detail herein, each rack
houses multiple sleds, which each may be embodied as a compute
device, such as a server, that is primarily equipped with a
particular type of resource (e.g., memory devices, data storage
devices, accelerator devices, general purpose processors). In the
illustrative embodiment, the sleds in each pod 110, 120, 130, 140
are connected to multiple pod switches (e.g., switches that route
data communications to and from sleds within the pod). The pod
switches, in turn, connect with spine switches 150 that switch
communications among pods (e.g., the pods 110, 120, 130, 140) in
the data center 100. In some embodiments, the sleds may be
connected with a fabric using Intel Omni-Path technology. As
described in more detail herein, resources within sleds in the data
center 100 may be allocated to a group (referred to herein as a
"managed node") containing resources from one or more other sleds
to be collectively utilized in the execution of a workload. The
workload can execute as if the resources belonging to the managed
node were located on the same sled. The resources in a managed node
may even belong to sleds belonging to different racks, and even to
different pods 110, 120, 130, 140. Some resources of a single sled
may be allocated to one managed node while other resources of the
same sled are allocated to a different managed node (e.g., one
processor assigned to one managed node and another processor of the
same sled assigned to a different managed node). By disaggregating
resources to sleds comprised predominantly of a single type of
resource (e.g., compute sleds comprising primarily compute
resources, memory sleds containing primarily memory resources), and
selectively allocating and deallocating the disaggregated resources
to form a managed node assigned to execute a workload, the data
center 100 provides more efficient resource usage over typical data
centers comprised of hyperconverged servers containing compute,
memory, storage and perhaps additional resources). As such, the
data center 100 may provide greater performance (e.g., throughput,
operations per second, latency, etc.) than a typical data center
that has the same number of resources.
[0030] Referring now to FIG. 2, the pod 110, in the illustrative
embodiment, includes a set of rows 200, 210, 220, 230 of racks 240.
Each rack 240 may house multiple sleds (e.g., sixteen sleds) and
provide power and data connections to the housed sleds, as
described in more detail herein. In the illustrative embodiment,
the racks in each row 200, 210, 220, 230 are connected to multiple
pod switches 250, 260. The pod switch 250 includes a set of ports
252 to which the sleds of the racks of the pod 110 are connected
and another set of ports 254 that connect the pod 110 to the spine
switches 150 to provide connectivity to other pods in the data
center 100. Similarly, the pod switch 260 includes a set of ports
262 to which the sleds of the racks of the pod 110 are connected
and a set of ports 264 that connect the pod 110 to the spine
switches 150. As such, the use of the pair of switches 250, 260
provides an amount of redundancy to the pod 110. For example, if
either of the switches 250, 260 fails, the sleds in the pod 110 may
still maintain data communication with the remainder of the data
center 100 (e.g., sleds of other pods) through the other switch
250, 260. Furthermore, in the illustrative embodiment, the switches
150, 250, 260 may be embodied as dual-mode optical switches,
capable of routing both Ethernet protocol communications carrying
Internet Protocol (IP) packets and communications according to a
second, high-performance link-layer protocol (e.g., Intel's
Omni-Path Architecture's, Infiniband) via optical signaling media
of an optical fabric.
[0031] It should be appreciated that each of the other pods 120,
130, 140 (as well as any additional pods of the data center 100)
may be similarly structured as, and have components similar to, the
pod 110 shown in and described in regard to FIG. 2 (e.g., each pod
may have rows of racks housing multiple sleds as described above).
Additionally, while two pod switches 250, 260 are shown, it should
be understood that in other embodiments, each pod 110, 120, 130,
140 may be connected to different number of pod switches (e.g.,
providing even more failover capacity).
[0032] Referring now to FIGS. 3-5, each illustrative rack 240 of
the data center 100 includes two elongated support posts 302, 304,
which are arranged vertically. For example, the elongated support
posts 302, 304 may extend upwardly from a floor of the data center
100 when deployed. The rack 240 also includes one or more
horizontal pairs 310 of elongated support arms 312 (identified in
FIG. 3 via a dashed ellipse) configured to support a sled of the
data center 100 as discussed below. One elongated support arm 312
of the pair of elongated support arms 312 extends outwardly from
the elongated support post 302 and the other elongated support arm
312 extends outwardly from the elongated support post 304.
[0033] In the illustrative embodiments, each sled of the data
center 100 is embodied as a chassis-less sled. That is, each sled
has a chassis-less circuit board substrate on which physical
resources (e.g., processors, memory, accelerators, storage, etc.)
are mounted as discussed in more detail below. As such, the rack
240 is configured to receive the chassis-less sleds. For example,
each pair 310 of elongated support arms 312 defines a sled slot 320
of the rack 240, which is configured to receive a corresponding
chassis-less sled. To do so, each illustrative elongated support
arm 312 includes a circuit board guide 330 configured to receive
the chassis-less circuit board substrate of the sled. Each circuit
board guide 330 is secured to, or otherwise mounted to, a top side
332 of the corresponding elongated support arm 312. For example, in
the illustrative embodiment, each circuit board guide 330 is
mounted at a distal end of the corresponding elongated support arm
312 relative to the corresponding elongated support post 302, 304.
For clarity of the Figures, not every circuit board guide 330 may
be referenced in each Figure.
[0034] Each circuit board guide 330 includes an inner wall that
defines a circuit board slot 380 configured to receive the
chassis-less circuit board substrate of a sled 400 when the sled
400 is received in the corresponding sled slot 320 of the rack 240.
To do so, as shown in FIG. 4, a user (or robot) aligns the
chassis-less circuit board substrate of an illustrative
chassis-less sled 400 to a sled slot 320. The user, or robot, may
then slide the chassis-less circuit board substrate forward into
the sled slot 320 such that each side edge 414 of the chassis-less
circuit board substrate is received in a corresponding circuit
board slot 380 of the circuit board guides 330 of the pair 310 of
elongated support arms 312 that define the corresponding sled slot
320 as shown in FIG. 4. By having robotically accessible and
robotically manipulable sleds comprising disaggregated resources,
each type of resource can be upgraded independently of each other
and at their own optimized refresh rate. Furthermore, the sleds are
configured to blindly mate with power and data communication cables
in each rack 240, enhancing their ability to be quickly removed,
upgraded, reinstalled, and/or replaced. As such, in some
embodiments, the data center 100 may operate (e.g., execute
workloads, undergo maintenance and/or upgrades, etc.) without human
involvement on the data center floor. In other embodiments, a human
may facilitate one or more maintenance or upgrade operations in the
data center 100.
[0035] It should be appreciated that each circuit board guide 330
is dual sided. That is, each circuit board guide 330 includes an
inner wall that defines a circuit board slot 380 on each side of
the circuit board guide 330. In this way, each circuit board guide
330 can support a chassis-less circuit board substrate on either
side. As such, a single additional elongated support post may be
added to the rack 240 to turn the rack 240 into a two-rack solution
that can hold twice as many sled slots 320 as shown in FIG. 3. The
illustrative rack 240 includes seven pairs 310 of elongated support
arms 312 that define a corresponding seven sled slots 320, each
configured to receive and support a corresponding sled 400 as
discussed above. Of course, in other embodiments, the rack 240 may
include additional or fewer pairs 310 of elongated support arms 312
(i.e., additional or fewer sled slots 320). It should be
appreciated that because the sled 400 is chassis-less, the sled 400
may have an overall height that is different than typical servers.
As such, in some embodiments, the height of each sled slot 320 may
be shorter than the height of a typical server (e.g., shorter than
a single rank unit, "1U"). That is, the vertical distance between
each pair 310 of elongated support arms 312 may be less than a
standard rack unit "1U." Additionally, due to the relative decrease
in height of the sled slots 320, the overall height of the rack 240
in some embodiments may be shorter than the height of traditional
rack enclosures. For example, in some embodiments, each of the
elongated support posts 302, 304 may have a length of six feet or
less. Again, in other embodiments, the rack 240 may have different
dimensions. Further, it should be appreciated that the rack 240
does not include any walls, enclosures, or the like. Rather, the
rack 240 is an enclosure-less rack that is opened to the local
environment. Of course, in some cases, an end plate may be attached
to one of the elongated support posts 302, 304 in those situations
in which the rack 240 forms an end-of-row rack in the data center
100.
[0036] In some embodiments, various interconnects may be routed
upwardly or downwardly through the elongated support posts 302,
304. To facilitate such routing, each elongated support post 302,
304 includes an inner wall that defines an inner chamber in which
the interconnect may be located. The interconnects routed through
the elongated support posts 302, 304 may be embodied as any type of
interconnects including, but not limited to, data or communication
interconnects to provide communication connections to each sled
slot 320, power interconnects to provide power to each sled slot
320, and/or other types of interconnects.
[0037] The rack 240, in the illustrative embodiment, includes a
support platform on which a corresponding optical data connector
(not shown) is mounted. Each optical data connector is associated
with a corresponding sled slot 320 and is configured to mate with
an optical data connector of a corresponding sled 400 when the sled
400 is received in the corresponding sled slot 320. In some
embodiments, optical connections between components (e.g., sleds,
racks, and switches) in the data center 100 are made with a blind
mate optical connection. For example, a door on each cable may
prevent dust from contaminating the fiber inside the cable. In the
process of connecting to a blind mate optical connector mechanism,
the door is pushed open when the end of the cable enters the
connector mechanism. Subsequently, the optical fiber inside the
cable enters a gel within the connector mechanism and the optical
fiber of one cable comes into contact with the optical fiber of
another cable within the gel inside the connector mechanism.
[0038] The illustrative rack 240 also includes a fan array 370
coupled to the cross-support arms of the rack 240. The fan array
370 includes one or more rows of cooling fans 372, which are
aligned in a horizontal line between the elongated support posts
302, 304. In the illustrative embodiment, the fan array 370
includes a row of cooling fans 372 for each sled slot 320 of the
rack 240. As discussed above, each sled 400 does not include any
on-board cooling system in the illustrative embodiment and, as
such, the fan array 370 provides cooling for each sled 400 received
in the rack 240. Each rack 240, in the illustrative embodiment,
also includes a power supply associated with each sled slot 320.
Each power supply is secured to one of the elongated support arms
312 of the pair 310 of elongated support arms 312 that define the
corresponding sled slot 320. For example, the rack 240 may include
a power supply coupled or secured to each elongated support arm 312
extending from the elongated support post 302. Each power supply
includes a power connector configured to mate with a power
connector of the sled 400 when the sled 400 is received in the
corresponding sled slot 320. In the illustrative embodiment, the
sled 400 does not include any on-board power supply and, as such,
the power supplies provided in the rack 240 supply power to
corresponding sleds 400 when mounted to the rack 240.
[0039] Referring now to FIG. 6, the sled 400, in the illustrative
embodiment, is configured to be mounted in a corresponding rack 240
of the data center 100 as discussed above. In some embodiments,
each sled 400 may be optimized or otherwise configured for
performing particular tasks, such as compute tasks, acceleration
tasks, data storage tasks, etc. For example, the sled 400 may be
embodied as a compute sled 800 as discussed below in regard to
FIGS. 8-9, an accelerator sled 1000 as discussed below in regard to
FIGS. 10-11, a storage sled 1200 as discussed below in regard to
FIGS. 12-13, or as a sled optimized or otherwise configured to
perform other specialized tasks, such as a memory sled 1400,
discussed below in regard to FIG. 14.
[0040] As discussed above, the illustrative sled 400 includes a
chassis-less circuit board substrate 602, which supports various
physical resources (e.g., electrical components) mounted thereon.
It should be appreciated that the circuit board substrate 602 is
"chassis-less" in that the sled 400 does not include a housing or
enclosure. Rather, the chassis-less circuit board substrate 602 is
open to the local environment. The chassis-less circuit board
substrate 602 may be formed from any material capable of supporting
the various electrical components mounted thereon. For example, in
an illustrative embodiment, the chassis-less circuit board
substrate 602 is formed from an FR-4 glass-reinforced epoxy
laminate material. Of course, other materials may be used to form
the chassis-less circuit board substrate 602 in other
embodiments.
[0041] As discussed in more detail below, the chassis-less circuit
board substrate 602 includes multiple features that improve the
thermal cooling characteristics of the various electrical
components mounted on the chassis-less circuit board substrate 602.
As discussed, the chassis-less circuit board substrate 602 does not
include a housing or enclosure, which may improve the airflow over
the electrical components of the sled 400 by reducing those
structures that may inhibit air flow. For example, because the
chassis-less circuit board substrate 602 is not positioned in an
individual housing or enclosure, there is no backplane (e.g., a
backplate of the chassis) to the chassis-less circuit board
substrate 602, which could inhibit air flow across the electrical
components. Additionally, the chassis-less circuit board substrate
602 has a geometric shape configured to reduce the length of the
airflow path across the electrical components mounted to the
chassis-less circuit board substrate 602. For example, the
illustrative chassis-less circuit board substrate 602 has a width
604 that is greater than a depth 606 of the chassis-less circuit
board substrate 602. In one particular embodiment, for example, the
chassis-less circuit board substrate 602 has a width of about 21
inches and a depth of about 9 inches, compared to a typical server
that has a width of about 17 inches and a depth of about 39 inches.
As such, an airflow path 608 that extends from a front edge 610 of
the chassis-less circuit board substrate 602 toward a rear edge 612
has a shorter distance relative to typical servers, which may
improve the thermal cooling characteristics of the sled 400.
Furthermore, although not illustrated in FIG. 6, the various
physical resources mounted to the chassis-less circuit board
substrate 602 are mounted in corresponding locations such that no
two substantively heat-producing electrical components shadow each
other as discussed in more detail below. That is, no two electrical
components, which produce appreciable heat during operation (i.e.,
greater than a nominal heat sufficient enough to adversely impact
the cooling of another electrical component), are mounted to the
chassis-less circuit board substrate 602 linearly in-line with each
other along the direction of the airflow path 608 (i.e., along a
direction extending from the front edge 610 toward the rear edge
612 of the chassis-less circuit board substrate 602).
[0042] As discussed above, the illustrative sled 400 includes one
or more physical resources 620 mounted to a top side 650 of the
chassis-less circuit board substrate 602. Although two physical
resources 620 are shown in FIG. 6, it should be appreciated that
the sled 400 may include one, two, or more physical resources 620
in other embodiments. The physical resources 620 may be embodied as
any type of processor, controller, or other compute circuit capable
of performing various tasks such as compute functions and/or
controlling the functions of the sled 400 depending on, for
example, the type or intended functionality of the sled 400. For
example, as discussed in more detail below, the physical resources
620 may be embodied as high-performance processors in embodiments
in which the sled 400 is embodied as a compute sled, as accelerator
co-processors or circuits in embodiments in which the sled 400 is
embodied as an accelerator sled, storage controllers in embodiments
in which the sled 400 is embodied as a storage sled, or a set of
memory devices in embodiments in which the sled 400 is embodied as
a memory sled.
[0043] The sled 400 also includes one or more additional physical
resources 630 mounted to the top side 650 of the chassis-less
circuit board substrate 602. In the illustrative embodiment, the
additional physical resources include a network interface
controller (NIC) as discussed in more detail below. Of course,
depending on the type and functionality of the sled 400, the
physical resources 630 may include additional or other electrical
components, circuits, and/or devices in other embodiments.
[0044] The physical resources 620 are communicatively coupled to
the physical resources 630 via an input/output (I/O) subsystem 622.
The I/O subsystem 622 may be embodied as circuitry and/or
components to facilitate input/output operations with the physical
resources 620, the physical resources 630, and/or other components
of the sled 400. For example, the I/O subsystem 622 may be embodied
as, or otherwise include, memory controller hubs, input/output
control hubs, integrated sensor hubs, firmware devices,
communication links (e.g., point-to-point links, bus links, wires,
cables, light guides, printed circuit board traces, etc.), and/or
other components and subsystems to facilitate the input/output
operations. In the illustrative embodiment, the I/O subsystem 622
is embodied as, or otherwise includes, a double data rate 4 (DDR4)
data bus or a DDRS data bus.
[0045] In some embodiments, the sled 400 may also include a
resource-to-resource interconnect 624. The resource-to-resource
interconnect 624 may be embodied as any type of communication
interconnect capable of facilitating resource-to-resource
communications. In the illustrative embodiment, the
resource-to-resource interconnect 624 is embodied as a high-speed
point-to-point interconnect (e.g., faster than the I/O subsystem
622). For example, the resource-to-resource interconnect 624 may be
embodied as a QuickPath Interconnect (QPI), an UltraPath
Interconnect (UPI), or other high-speed point-to-point interconnect
dedicated to resource-to-resource communications.
[0046] The sled 400 also includes a power connector 640 configured
to mate with a corresponding power connector of the rack 240 when
the sled 400 is mounted in the corresponding rack 240. The sled 400
receives power from a power supply of the rack 240 via the power
connector 640 to supply power to the various electrical components
of the sled 400. That is, the sled 400 does not include any local
power supply (i.e., an on-board power supply) to provide power to
the electrical components of the sled 400. The exclusion of a local
or on-board power supply facilitates the reduction in the overall
footprint of the chassis-less circuit board substrate 602, which
may increase the thermal cooling characteristics of the various
electrical components mounted on the chassis-less circuit board
substrate 602 as discussed above. In some embodiments, power is
provided to the processors 820 through vias directly under the
processors 820 (e.g., through the bottom side 750 of the
chassis-less circuit board substrate 602), providing an increased
thermal budget, additional current and/or voltage, and better
voltage control over typical boards.
[0047] In some embodiments, the sled 400 may also include mounting
features 642 configured to mate with a mounting arm, or other
structure, of a robot to facilitate the placement of the sled 600
in a rack 240 by the robot. The mounting features 642 may be
embodied as any type of physical structures that allow the robot to
grasp the sled 400 without damaging the chassis-less circuit board
substrate 602 or the electrical components mounted thereto. For
example, in some embodiments, the mounting features 642 may be
embodied as non-conductive pads attached to the chassis-less
circuit board substrate 602. In other embodiments, the mounting
features may be embodied as brackets, braces, or other similar
structures attached to the chassis-less circuit board substrate
602. The particular number, shape, size, and/or make-up of the
mounting feature 642 may depend on the design of the robot
configured to manage the sled 400.
[0048] Referring now to FIG. 7, in addition to the physical
resources 630 mounted on the top side 650 of the chassis-less
circuit board substrate 602, the sled 400 also includes one or more
memory devices 720 mounted to a bottom side 750 of the chassis-less
circuit board substrate 602. That is, the chassis-less circuit
board substrate 602 is embodied as a double-sided circuit board.
The physical resources 620 are communicatively coupled to the
memory devices 720 via the I/O subsystem 622. For example, the
physical resources 620 and the memory devices 720 may be
communicatively coupled by one or more vias extending through the
chassis-less circuit board substrate 602. Each physical resource
620 may be communicatively coupled to a different set of one or
more memory devices 720 in some embodiments. Alternatively, in
other embodiments, each physical resource 620 may be
communicatively coupled to each memory devices 720.
[0049] The memory devices 720 may be embodied as any type of memory
device capable of storing data for the physical resources 620
during operation of the sled 400, such as any type of volatile
(e.g., dynamic random access memory (DRAM), etc.) or non-volatile
memory. Volatile memory may be a storage medium that requires power
to maintain the state of data stored by the medium. Non-limiting
examples of volatile memory may include various types of random
access memory (RAM), such as dynamic random access memory (DRAM) or
static random access memory (SRAM). One particular type of DRAM
that may be used in a memory module is synchronous dynamic random
access memory (SDRAM). In particular embodiments, DRAM of a memory
component may comply with a standard promulgated by JEDEC, such as
JESD79F for DDR SDRAM, JESD79-2F for DDR2 SDRAM, JESD79-3F for DDR3
SDRAM, JESD79-4A for DDR4 SDRAM, JESD209 for Low Power DDR (LPDDR),
JESD209-2 for LPDDR2, JESD209-3 for LPDDR3, and JESD209-4 for
LPDDR4 (these standards are available at www.jedec.org). Such
standards (and similar standards) may be referred to as DDR-based
standards and communication interfaces of the storage devices that
implement such standards may be referred to as DDR-based
interfaces.
[0050] In one embodiment, the memory device is a block addressable
memory device, such as those based on NAND or NOR technologies. A
memory device may also include next-generation nonvolatile devices,
such as Intel 3D XPoint.TM. memory or other byte addressable
write-in-place nonvolatile memory devices. In one embodiment, the
memory device may be or may include memory devices that use
chalcogenide glass, multi-threshold level NAND flash memory, NOR
flash memory, single or multi-level Phase Change Memory (PCM), a
resistive memory, nanowire memory, ferroelectric transistor random
access memory (FeTRAM), anti-ferroelectric memory, magnetoresistive
random access memory (MRAM) memory that incorporates memristor
technology, resistive memory including the metal oxide base, the
oxygen vacancy base and the conductive bridge Random Access Memory
(CB-RAM), or spin transfer torque (STT)-MRAM, a spintronic magnetic
junction memory based device, a magnetic tunneling junction (MTJ)
based device, a DW (Domain Wall) and SOT (Spin Orbit Transfer)
based device, a thyristor based memory device, or a combination of
any of the above, or other memory. The memory device may refer to
the die itself and/or to a packaged memory product. In some
embodiments, the memory device may comprise a transistor-less
stackable cross point architecture in which memory cells sit at the
intersection of word lines and bit lines and are individually
addressable and in which bit storage is based on a change in bulk
resistance.
[0051] Referring now to FIG. 8, in some embodiments, the sled 400
may be embodied as a compute sled 800. The compute sled 800 is
optimized, or otherwise configured, to perform compute tasks. Of
course, as discussed above, the compute sled 800 may rely on other
sleds, such as acceleration sleds and/or storage sleds, to perform
such compute tasks. The compute sled 800 includes various physical
resources (e.g., electrical components) similar to the physical
resources of the sled 400, which have been identified in FIG. 8
using the same reference numbers. The description of such
components provided above in regard to FIGS. 6 and 7 applies to the
corresponding components of the compute sled 800 and is not
repeated herein for clarity of the description of the compute sled
800.
[0052] In the illustrative compute sled 800, the physical resources
620 are embodied as processors 820. Although only two processors
820 are shown in FIG. 8, it should be appreciated that the compute
sled 800 may include additional processors 820 in other
embodiments. Illustratively, the processors 820 are embodied as
high-performance processors 820 and may be configured to operate at
a relatively high power rating. Although the processors 820
generate additional heat operating at power ratings greater than
typical processors (which operate at around 155-230 W), the
enhanced thermal cooling characteristics of the chassis-less
circuit board substrate 602 discussed above facilitate the higher
power operation. For example, in the illustrative embodiment, the
processors 820 are configured to operate at a power rating of at
least 250 W. In some embodiments, the processors 820 may be
configured to operate at a power rating of at least 350 W.
[0053] In some embodiments, the compute sled 800 may also include a
processor-to-processor interconnect 842. Similar to the
resource-to-resource interconnect 624 of the sled 400 discussed
above, the processor-to-processor interconnect 842 may be embodied
as any type of communication interconnect capable of facilitating
processor-to-processor interconnect 842 communications. In the
illustrative embodiment, the processor-to-processor interconnect
842 is embodied as a high-speed point-to-point interconnect (e.g.,
faster than the I/O subsystem 622). For example, the
processor-to-processor interconnect 842 may be embodied as a
QuickPath Interconnect (QPI), an UltraPath Interconnect (UPI), or
other high-speed point-to-point interconnect dedicated to
processor-to-processor communications.
[0054] The compute sled 800 also includes a communication circuit
830. The illustrative communication circuit 830 includes a network
interface controller (NIC) 832, which may also be referred to as a
host fabric interface (HFI). The NIC 832 may be embodied as, or
otherwise include, any type of integrated circuit, discrete
circuits, controller chips, chipsets, add-in-boards, daughtercards,
network interface cards, other devices that may be used by the
compute sled 800 to connect with another compute device (e.g., with
other sleds 400). In some embodiments, the NIC 832 may be embodied
as part of a system-on-a-chip (SoC) that includes one or more
processors, or included on a multichip package that also contains
one or more processors. In some embodiments, the NIC 832 may
include a local processor (not shown) and/or a local memory (not
shown) that are both local to the NIC 832. In such embodiments, the
local processor of the NIC 832 may be capable of performing one or
more of the functions of the processors 820. Additionally or
alternatively, in such embodiments, the local memory of the NIC 832
may be integrated into one or more components of the compute sled
at the board level, socket level, chip level, and/or other
levels.
[0055] The communication circuit 830 is communicatively coupled to
an optical data connector 834. The optical data connector 834 is
configured to mate with a corresponding optical data connector of
the rack 240 when the compute sled 800 is mounted in the rack 240.
Illustratively, the optical data connector 834 includes a plurality
of optical fibers which lead from a mating surface of the optical
data connector 834 to an optical transceiver 836. The optical
transceiver 836 is configured to convert incoming optical signals
from the rack-side optical data connector to electrical signals and
to convert electrical signals to outgoing optical signals to the
rack-side optical data connector. Although shown as forming part of
the optical data connector 834 in the illustrative embodiment, the
optical transceiver 836 may form a portion of the communication
circuit 830 in other embodiments.
[0056] In some embodiments, the compute sled 800 may also include
an expansion connector 840. In such embodiments, the expansion
connector 840 is configured to mate with a corresponding connector
of an expansion chassis-less circuit board substrate to provide
additional physical resources to the compute sled 800. The
additional physical resources may be used, for example, by the
processors 820 during operation of the compute sled 800. The
expansion chassis-less circuit board substrate may be substantially
similar to the chassis-less circuit board substrate 602 discussed
above and may include various electrical components mounted
thereto. The particular electrical components mounted to the
expansion chassis-less circuit board substrate may depend on the
intended functionality of the expansion chassis-less circuit board
substrate. For example, the expansion chassis-less circuit board
substrate may provide additional compute resources, memory
resources, and/or storage resources. As such, the additional
physical resources of the expansion chassis-less circuit board
substrate may include, but is not limited to, processors, memory
devices, storage devices, and/or accelerator circuits including,
for example, field programmable gate arrays (FPGA),
application-specific integrated circuits (ASICs), security
co-processors, graphics processing units (GPUs), machine learning
circuits, or other specialized processors, controllers, devices,
and/or circuits.
[0057] Referring now to FIG. 9, an illustrative embodiment of the
compute sled 800 is shown. As shown, the processors 820,
communication circuit 830, and optical data connector 834 are
mounted to the top side 650 of the chassis-less circuit board
substrate 602. Any suitable attachment or mounting technology may
be used to mount the physical resources of the compute sled 800 to
the chassis-less circuit board substrate 602. For example, the
various physical resources may be mounted in corresponding sockets
(e.g., a processor socket), holders, or brackets. In some cases,
some of the electrical components may be directly mounted to the
chassis-less circuit board substrate 602 via soldering or similar
techniques.
[0058] As discussed above, the individual processors 820 and
communication circuit 830 are mounted to the top side 650 of the
chassis-less circuit board substrate 602 such that no two
heat-producing, electrical components shadow each other. In the
illustrative embodiment, the processors 820 and communication
circuit 830 are mounted in corresponding locations on the top side
650 of the chassis-less circuit board substrate 602 such that no
two of those physical resources are linearly in-line with others
along the direction of the airflow path 608. It should be
appreciated that, although the optical data connector 834 is
in-line with the communication circuit 830, the optical data
connector 834 produces no or nominal heat during operation.
[0059] The memory devices 720 of the compute sled 800 are mounted
to the bottom side 750 of the of the chassis-less circuit board
substrate 602 as discussed above in regard to the sled 400.
Although mounted to the bottom side 750, the memory devices 720 are
communicatively coupled to the processors 820 located on the top
side 650 via the I/O subsystem 622. Because the chassis-less
circuit board substrate 602 is embodied as a double-sided circuit
board, the memory devices 720 and the processors 820 may be
communicatively coupled by one or more vias, connectors, or other
mechanisms extending through the chassis-less circuit board
substrate 602. Of course, each processor 820 may be communicatively
coupled to a different set of one or more memory devices 720 in
some embodiments. Alternatively, in other embodiments, each
processor 820 may be communicatively coupled to each memory device
720. In some embodiments, the memory devices 720 may be mounted to
one or more memory mezzanines on the bottom side of the
chassis-less circuit board substrate 602 and may interconnect with
a corresponding processor 820 through a ball-grid array.
[0060] Each of the processors 820 includes a heatsink 850 secured
thereto. Due to the mounting of the memory devices 720 to the
bottom side 750 of the chassis-less circuit board substrate 602 (as
well as the vertical spacing of the sleds 400 in the corresponding
rack 240), the top side 650 of the chassis-less circuit board
substrate 602 includes additional "free" area or space that
facilitates the use of heatsinks 850 having a larger size relative
to traditional heatsinks used in typical servers. Additionally, due
to the improved thermal cooling characteristics of the chassis-less
circuit board substrate 602, none of the processor heatsinks 850
include cooling fans attached thereto. That is, each of the
heatsinks 850 is embodied as a fan-less heatsinks.
[0061] Referring now to FIG. 10, in some embodiments, the sled 400
may be embodied as an accelerator sled 1000. The accelerator sled
1000 is optimized, or otherwise configured, to perform specialized
compute tasks, such as machine learning, encryption, hashing, or
other computational-intensive task. In some embodiments, for
example, a compute sled 800 may offload tasks to the accelerator
sled 1000 during operation. The accelerator sled 1000 includes
various components similar to components of the sled 400 and/or
compute sled 800, which have been identified in FIG. 10 using the
same reference numbers. The description of such components provided
above in regard to FIGS. 6, 7, and 8 apply to the corresponding
components of the accelerator sled 1000 and is not repeated herein
for clarity of the description of the accelerator sled 1000.
[0062] In the illustrative accelerator sled 1000, the physical
resources 620 are embodied as accelerator circuits 1020. Although
only two accelerator circuits 1020 are shown in FIG. 10, it should
be appreciated that the accelerator sled 1000 may include
additional accelerator circuits 1020 in other embodiments. For
example, as shown in FIG. 11, the accelerator sled 1000 may include
four accelerator circuits 1020 in some embodiments. The accelerator
circuits 1020 may be embodied as any type of processor,
co-processor, compute circuit, or other device capable of
performing compute or processing operations. For example, the
accelerator circuits 1020 may be embodied as, for example, field
programmable gate arrays (FPGA), application-specific integrated
circuits (ASICs), security co-processors, graphics processing units
(GPUs), machine learning circuits, or other specialized processors,
controllers, devices, and/or circuits.
[0063] In some embodiments, the accelerator sled 1000 may also
include an accelerator-to-accelerator interconnect 1042. Similar to
the resource-to-resource interconnect 624 of the sled 600 discussed
above, the accelerator-to-accelerator interconnect 1042 may be
embodied as any type of communication interconnect capable of
facilitating accelerator-to-accelerator communications. In the
illustrative embodiment, the accelerator-to-accelerator
interconnect 1042 is embodied as a high-speed point-to-point
interconnect (e.g., faster than the I/O subsystem 622). For
example, the accelerator-to-accelerator interconnect 1042 may be
embodied as a QuickPath Interconnect (QPI), an UltraPath
Interconnect (UPI), or other high-speed point-to-point interconnect
dedicated to processor-to-processor communications. In some
embodiments, the accelerator circuits 1020 may be daisy-chained
with a primary accelerator circuit 1020 connected to the NIC 832
and memory 720 through the I/O subsystem 622 and a secondary
accelerator circuit 1020 connected to the NIC 832 and memory 720
through a primary accelerator circuit 1020.
[0064] Referring now to FIG. 11, an illustrative embodiment of the
accelerator sled 1000 is shown. As discussed above, the accelerator
circuits 1020, communication circuit 830, and optical data
connector 834 are mounted to the top side 650 of the chassis-less
circuit board substrate 602. Again, the individual accelerator
circuits 1020 and communication circuit 830 are mounted to the top
side 650 of the chassis-less circuit board substrate 602 such that
no two heat-producing, electrical components shadow each other as
discussed above. The memory devices 720 of the accelerator sled
1000 are mounted to the bottom side 750 of the of the chassis-less
circuit board substrate 602 as discussed above in regard to the
sled 600. Although mounted to the bottom side 750, the memory
devices 720 are communicatively coupled to the accelerator circuits
1020 located on the top side 650 via the I/O subsystem 622 (e.g.,
through vias). Further, each of the accelerator circuits 1020 may
include a heatsink 1070 that is larger than a traditional heatsink
used in a server. As discussed above with reference to the
heatsinks 870, the heatsinks 1070 may be larger than tradition
heatsinks because of the "free" area provided by the memory devices
750 being located on the bottom side 750 of the chassis-less
circuit board substrate 602 rather than on the top side 650.
[0065] Referring now to FIG. 12, in some embodiments, the sled 400
may be embodied as a storage sled 1200. The storage sled 1200 is
optimized, or otherwise configured, to store data in a data storage
1250 local to the storage sled 1200. For example, during operation,
a compute sled 800 or an accelerator sled 1000 may store and
retrieve data from the data storage 1250 of the storage sled 1200.
The storage sled 1200 includes various components similar to
components of the sled 400 and/or the compute sled 800, which have
been identified in FIG. 12 using the same reference numbers. The
description of such components provided above in regard to FIGS. 6,
7, and 8 apply to the corresponding components of the storage sled
1200 and is not repeated herein for clarity of the description of
the storage sled 1200.
[0066] In the illustrative storage sled 1200, the physical
resources 620 are embodied as storage controllers 1220. Although
only two storage controllers 1220 are shown in FIG. 12, it should
be appreciated that the storage sled 1200 may include additional
storage controllers 1220 in other embodiments. The storage
controllers 1220 may be embodied as any type of processor,
controller, or control circuit capable of controlling the storage
and retrieval of data into the data storage 1250 based on requests
received via the communication circuit 830. In the illustrative
embodiment, the storage controllers 1220 are embodied as relatively
low-power processors or controllers. For example, in some
embodiments, the storage controllers 1220 may be configured to
operate at a power rating of about 75 watts.
[0067] In some embodiments, the storage sled 1200 may also include
a controller-to-controller interconnect 1242. Similar to the
resource-to-resource interconnect 624 of the sled 400 discussed
above, the controller-to-controller interconnect 1242 may be
embodied as any type of communication interconnect capable of
facilitating controller-to-controller communications. In the
illustrative embodiment, the controller-to-controller interconnect
1242 is embodied as a high-speed point-to-point interconnect (e.g.,
faster than the I/O subsystem 622). For example, the
controller-to-controller interconnect 1242 may be embodied as a
QuickPath Interconnect (QPI), an UltraPath Interconnect (UPI), or
other high-speed point-to-point interconnect dedicated to
processor-to-processor communications.
[0068] Referring now to FIG. 13, an illustrative embodiment of the
storage sled 1200 is shown. In the illustrative embodiment, the
data storage 1250 is embodied as, or otherwise includes, a storage
cage 1252 configured to house one or more solid state drives (SSDs)
1254. To do so, the storage cage 1252 includes a number of mounting
slots 1256, each of which is configured to receive a corresponding
solid state drive 1254. Each of the mounting slots 1256 includes a
number of drive guides 1258 that cooperate to define an access
opening 1260 of the corresponding mounting slot 1256. The storage
cage 1252 is secured to the chassis-less circuit board substrate
602 such that the access openings face away from (i.e., toward the
front of) the chassis-less circuit board substrate 602. As such,
solid state drives 1254 are accessible while the storage sled 1200
is mounted in a corresponding rack 204. For example, a solid state
drive 1254 may be swapped out of a rack 240 (e.g., via a robot)
while the storage sled 1200 remains mounted in the corresponding
rack 240.
[0069] The storage cage 1252 illustratively includes sixteen
mounting slots 1256 and is capable of mounting and storing sixteen
solid state drives 1254. Of course, the storage cage 1252 may be
configured to store additional or fewer solid state drives 1254 in
other embodiments. Additionally, in the illustrative embodiment,
the solid state drivers are mounted vertically in the storage cage
1252, but may be mounted in the storage cage 1252 in a different
orientation in other embodiments. Each solid state drive 1254 may
be embodied as any type of data storage device capable of storing
long term data. To do so, the solid state drives 1254 may include
volatile and non-volatile memory devices discussed above.
[0070] As shown in FIG. 13, the storage controllers 1220, the
communication circuit 830, and the optical data connector 834 are
illustratively mounted to the top side 650 of the chassis-less
circuit board substrate 602. Again, as discussed above, any
suitable attachment or mounting technology may be used to mount the
electrical components of the storage sled 1200 to the chassis-less
circuit board substrate 602 including, for example, sockets (e.g.,
a processor socket), holders, brackets, soldered connections,
and/or other mounting or securing techniques.
[0071] As discussed above, the individual storage controllers 1220
and the communication circuit 830 are mounted to the top side 650
of the chassis-less circuit board substrate 602 such that no two
heat-producing, electrical components shadow each other. For
example, the storage controllers 1220 and the communication circuit
830 are mounted in corresponding locations on the top side 650 of
the chassis-less circuit board substrate 602 such that no two of
those electrical components are linearly in-line with other along
the direction of the airflow path 608.
[0072] The memory devices 720 of the storage sled 1200 are mounted
to the bottom side 750 of the of the chassis-less circuit board
substrate 602 as discussed above in regard to the sled 400.
Although mounted to the bottom side 750, the memory devices 720 are
communicatively coupled to the storage controllers 1220 located on
the top side 650 via the I/O subsystem 622. Again, because the
chassis-less circuit board substrate 602 is embodied as a
double-sided circuit board, the memory devices 720 and the storage
controllers 1220 may be communicatively coupled by one or more
vias, connectors, or other mechanisms extending through the
chassis-less circuit board substrate 602. Each of the storage
controllers 1220 includes a heatsink 1270 secured thereto. As
discussed above, due to the improved thermal cooling
characteristics of the chassis-less circuit board substrate 602 of
the storage sled 1200, none of the heatsinks 1270 include cooling
fans attached thereto. That is, each of the heatsinks 1270 is
embodied as a fan-less heatsink.
[0073] Referring now to FIG. 14, in some embodiments, the sled 400
may be embodied as a memory sled 1400. The storage sled 1400 is
optimized, or otherwise configured, to provide other sleds 400
(e.g., compute sleds 800, accelerator sleds 1000, etc.) with access
to a pool of memory (e.g., in two or more sets 1430, 1432 of memory
devices 720) local to the memory sled 1200. For example, during
operation, a compute sled 800 or an accelerator sled 1000 may
remotely write to and/or read from one or more of the memory sets
1430, 1432 of the memory sled 1200 using a logical address space
that maps to physical addresses in the memory sets 1430, 1432. The
memory sled 1400 includes various components similar to components
of the sled 400 and/or the compute sled 800, which have been
identified in FIG. 14 using the same reference numbers. The
description of such components provided above in regard to FIGS. 6,
7, and 8 apply to the corresponding components of the memory sled
1400 and is not repeated herein for clarity of the description of
the memory sled 1400.
[0074] In the illustrative memory sled 1400, the physical resources
620 are embodied as memory controllers 1420. Although only two
memory controllers 1420 are shown in FIG. 14, it should be
appreciated that the memory sled 1400 may include additional memory
controllers 1420 in other embodiments. The memory controllers 1420
may be embodied as any type of processor, controller, or control
circuit capable of controlling the writing and reading of data into
the memory sets 1430, 1432 based on requests received via the
communication circuit 830. In the illustrative embodiment, each
storage controller 1220 is connected to a corresponding memory set
1430, 1432 to write to and read from memory devices 720 within the
corresponding memory set 1430, 1432 and enforce any permissions
(e.g., read, write, etc.) associated with sled 400 that has sent a
request to the memory sled 1400 to perform a memory access
operation (e.g., read or write).
[0075] In some embodiments, the memory sled 1400 may also include a
controller-to-controller interconnect 1442. Similar to the
resource-to-resource interconnect 624 of the sled 400 discussed
above, the controller-to-controller interconnect 1442 may be
embodied as any type of communication interconnect capable of
facilitating controller-to-controller communications. In the
illustrative embodiment, the controller-to-controller interconnect
1442 is embodied as a high-speed point-to-point interconnect (e.g.,
faster than the I/O subsystem 622). For example, the
controller-to-controller interconnect 1442 may be embodied as a
QuickPath Interconnect (QPI), an UltraPath Interconnect (UPI), or
other high-speed point-to-point interconnect dedicated to
processor-to-processor communications. As such, in some
embodiments, a memory controller 1420 may access, through the
controller-to-controller interconnect 1442, memory that is within
the memory set 1432 associated with another memory controller 1420.
In some embodiments, a scalable memory controller is made of
multiple smaller memory controllers, referred to herein as
"chiplets", on a memory sled (e.g., the memory sled 1400). The
chiplets may be interconnected (e.g., using EMIB (Embedded
Multi-Die Interconnect Bridge)). The combined chiplet memory
controller may scale up to a relatively large number of memory
controllers and I/O ports, (e.g., up to 16 memory channels). In
some embodiments, the memory controllers 1420 may implement a
memory interleave (e.g., one memory address is mapped to the memory
set 1430, the next memory address is mapped to the memory set 1432,
and the third address is mapped to the memory set 1430, etc.). The
interleaving may be managed within the memory controllers 1420, or
from CPU sockets (e.g., of the compute sled 800) across network
links to the memory sets 1430, 1432, and may improve the latency
associated with performing memory access operations as compared to
accessing contiguous memory addresses from the same memory
device.
[0076] Further, in some embodiments, the memory sled 1400 may be
connected to one or more other sleds 400 (e.g., in the same rack
240 or an adjacent rack 240) through a waveguide, using the
waveguide connector 1480. In the illustrative embodiment, the
waveguides are 64 millimeter waveguides that provide 16 Rx (i.e.,
receive) lanes and 16 Rt (i.e., transmit) lanes. Each lane, in the
illustrative embodiment, is either 16 Ghz or 32 Ghz. In other
embodiments, the frequencies may be different. Using a waveguide
may provide high throughput access to the memory pool (e.g., the
memory sets 1430, 1432) to another sled (e.g., a sled 400 in the
same rack 240 or an adjacent rack 240 as the memory sled 1400)
without adding to the load on the optical data connector 834.
[0077] Referring now to FIG. 15, a system for executing one or more
workloads (e.g., applications) may be implemented in accordance
with the data center 100. In the illustrative embodiment, the
system 1510 includes an orchestrator server 1520, which may be
embodied as a managed node comprising a compute device (e.g., a
compute sled 800) executing management software (e.g., a cloud
operating environment, such as OpenStack) that is communicatively
coupled to multiple sleds 400 including a large number of compute
sleds 1530 (e.g., each similar to the compute sled 800), memory
sleds 1540 (e.g., each similar to the memory sled 1400),
accelerator sleds 1550 (e.g., each similar to the memory sled
1000), and storage sleds 1560 (e.g., each similar to the storage
sled 1200). One or more of the sleds 1530, 1540, 1550, 1560 may be
grouped into a managed node 1570, such as by the orchestrator
server 1520, to collectively perform a workload (e.g., an
application 1532 executed in a virtual machine or in a container).
The managed node 1570 may be embodied as an assembly of physical
resources 620, such as processors 820, memory resources 720,
accelerator circuits 1020, or data storage 1250, from the same or
different sleds 400. Further, the managed node may be established,
defined, or "spun up" by the orchestrator server 1520 at the time a
workload is to be assigned to the managed node or at any other
time, and may exist regardless of whether any workloads are
presently assigned to the managed node. In the illustrative
embodiment, the orchestrator server 1520 may selectively allocate
and/or deallocate physical resources 620 from the sleds 400 and/or
add or remove one or more sleds 400 from the managed node 1570 as a
function of quality of service (QoS) targets (e.g., performance
targets associated with a throughput, latency, instructions per
second, etc.) associated with a service level agreement for the
workload (e.g., the application 1532). In doing so, the
orchestrator server 1520 may receive telemetry data indicative of
performance conditions (e.g., throughput, latency, instructions per
second, etc.) in each sled 400 of the managed node 1570 and compare
the telemetry data to the quality of service targets to determine
whether the quality of service targets are being satisfied. If the
so, the orchestrator server 1520 may additionally determine whether
one or more physical resources may be deallocated from the managed
node 1570 while still satisfying the QoS targets, thereby freeing
up those physical resources for use in another managed node (e.g.,
to execute a different workload). Alternatively, if the QoS targets
are not presently satisfied, the orchestrator server 1520 may
determine to dynamically allocate additional physical resources to
assist in the execution of the workload (e.g., the application
1532) while the workload is executing
[0078] Additionally, in some embodiments, the orchestrator server
1520 may identify trends in the resource utilization of the
workload (e.g., the application 1532), such as by identifying
phases of execution (e.g., time periods in which different
operations, each having different resource utilizations
characteristics, are performed) of the workload (e.g., the
application 1532) and pre-emptively identifying available resources
in the data center 100 and allocating them to the managed node 1570
(e.g., within a predefined time period of the associated phase
beginning). In some embodiments, the orchestrator server 1520 may
model performance based on various latencies and a distribution
scheme to place workloads among compute sleds and other resources
(e.g., accelerator sleds, memory sleds, storage sleds) in the data
center 100. For example, the orchestrator server 1520 may utilize a
model that accounts for the performance of resources on the sleds
400 (e.g., FPGA performance, memory access latency, etc.) and the
performance (e.g., congestion, latency, bandwidth) of the path
through the network to the resource (e.g., FPGA). As such, the
orchestrator server 1520 may determine which resource(s) should be
used with which workloads based on the total latency associated
with each potential resource available in the data center 100
(e.g., the latency associated with the performance of the resource
itself in addition to the latency associated with the path through
the network between the compute sled executing the workload and the
sled 400 on which the resource is located).
[0079] In some embodiments, the orchestrator server 1520 may
generate a map of heat generation in the data center 100 using
telemetry data (e.g., temperatures, fan speeds, etc.) reported from
the sleds 400 and allocate resources to managed nodes as a function
of the map of heat generation and predicted heat generation
associated with different workloads, to maintain a target
temperature and heat distribution in the data center 100.
Additionally or alternatively, in some embodiments, the
orchestrator server 1520 may organize received telemetry data into
a hierarchical model that is indicative of a relationship between
the managed nodes (e.g., a spatial relationship such as the
physical locations of the resources of the managed nodes within the
data center 100 and/or a functional relationship, such as groupings
of the managed nodes by the customers the managed nodes provide
services for, the types of functions typically performed by the
managed nodes, managed nodes that typically share or exchange
workloads among each other, etc.). Based on differences in the
physical locations and resources in the managed nodes, a given
workload may exhibit different resource utilizations (e.g., cause a
different internal temperature, use a different percentage of
processor or memory capacity) across the resources of different
managed nodes. The orchestrator server 1520 may determine the
differences based on the telemetry data stored in the hierarchical
model and factor the differences into a prediction of future
resource utilization of a workload if the workload is reassigned
from one managed node to another managed node, to accurately
balance resource utilization in the data center 100.
[0080] To reduce the computational load on the orchestrator server
1520 and the data transfer load on the network, in some
embodiments, the orchestrator server 1520 may send self- test
information to the sleds 400 to enable each sled 400 to locally
(e.g., on the sled 400) determine whether telemetry data generated
by the sled 400 satisfies one or more conditions (e.g., an
available capacity that satisfies a predefined threshold, a
temperature that satisfies a predefined threshold, etc.). Each sled
400 may then report back a simplified result (e.g., yes or no) to
the orchestrator server 1520, which the orchestrator server 1520
may utilize in determining the allocation of resources to managed
nodes.
[0081] Referring now to FIG. 16, a system 1600 for bandwidth
allocation may be implemented in accordance with the data center
100 described above with reference to FIGS. 1-15. As shown, the
system 1600 includes a resource manager server 1602 and multiple
sleds 1610, 1612, 1614, 1616, 1618, 1620 in communication over a
network using multiple switches 1604, 1606, 1608. Each of the
resource manager server 1602 and the sleds 1610, 1612, 1614, 1616,
1618, 1620 may be embodied as server computer, a rack server, a
blade server, a compute node, and/or a sled in a data center, such
as a sled 400 as described above in connection with FIGS. 1-15 or
another sled of the data center.
[0082] The network elements of the system 1600 are organized into a
network topology. As shown, the sleds 1610, 1612, 1614 may be
organized into a rack and each connected to the switch 1606, which
may be embodied as a top-of-rack switch, middle-of-rack switch,
end-of-row switch, or other switch device. Similarly, the sleds
1616, 1618, 1620 are connected to the switch 1608. The switches
1606, 1608 are in turn connected to the switch 1604, which may be
embodied as a data center domain switch or other upstream switch.
The resource manager server 1602 is illustrated as being connected
to the upstream switch 1604, however, in other embodiments it may
be connected to any other location in the network topology. Thus,
as shown in FIG. 16, the switches 1604, 1606, 1608 are organized
into multiple layers, and sending data across layers may add
switching latency, queuing latency, or other latencies.
[0083] Additionally, although the resource manager server 1602 is
illustrated as a single server computing device, in some
embodiments, the resource manager server 1602 may be embodied as a
"virtual server" formed from multiple computing devices distributed
across the system 1600 and/or operating in a public or private
cloud. Accordingly, although the resource manager server 1602 is
illustrated in FIG. 16 and described below as embodied as a single
server computing device, it should be appreciated that the resource
manager server 1602 may be embodied as multiple devices cooperating
together to facilitate the functionality described below.
[0084] In use, as described further below, the resource manager
server 1602 may discover the network topology of the system 1600
and construct a model of resource oversubscription in the system
1600. Resource oversubscription may include network uplink
oversubscription, storage resource oversubscription, or any other
circumstance in which the aggregate bandwidth or other demand
generated by the sleds exceeds the available bandwidth or other
capacity of the system 1600. The resource manager server 1602 may
determine bandwidth limits for each sled or other network element
of the system 1600 and program those bandwidth limits to the
network elements. Each network element enforces the programmed
bandwidth limits, which may reduce network congestion. By reducing
congestion, the system 1600 may eliminate or reduce queuing latency
for each layer of switches. For example, bandwidth limits for a
storage sled 1610 may ensure that non-volatile memory express
(NVMe) over Ethernet data traffic generated by the storage sled
1610 (and other storage sleds) does not exceed available upstream
bandwidth. Accordingly, the system 1600 may improve network latency
and reduce network congestion, without implementing expensive
bandwidth reservation mechanisms at the switch level.
[0085] Referring now to FIG. 17, an illustrative computing device
1700 is shown. The computing device 1700 may be the resource
manager server 1602, a sled 400, a storage sled 1200, 1610, 1614,
1616, 1620, an accelerator sled 1000, a memory sled 1400, a compute
sled 800, 1612, 1618, and/or a similar server computing device. As
shown in FIG. 17, the computing device 1700 illustratively includes
a processor 1720, an input/output subsystem 1722, a memory 1724, a
data storage device 1726, a communication subsystem 1728, and/or
other components and devices commonly found in a sled 400, a
storage sled 1200, 1610, 1614, 1616, 1620, an accelerator sled
1000, a memory sled 1400, a compute sled 800, 1612, 1618, and/or a
similar server computing device. Of course, the computing device
1700 may include other or additional components, such as those
commonly found in a server computer (e.g., various input/output
devices), in other embodiments. Additionally, in some embodiments,
one or more of the illustrative components may be incorporated in,
or otherwise form a portion of, another component. For example, the
memory 1724, or portions thereof, may be incorporated in the
processor 1720 in some embodiments.
[0086] The processor 1720 may be embodied as any type of processor
capable of performing the functions described herein. For example,
the processor 1720 may be embodied as a single or multi-core
processor(s), digital signal processor, microcontroller, or other
processor or processing/controlling circuit. Similarly, the memory
1724 may be embodied as any type of volatile or non-volatile memory
or data storage capable of performing the functions described
herein. In operation, the memory 1724 may store various data and
software used during operation of the computing device 1700 such
operating systems, applications, programs, libraries, and drivers.
The memory 1724 is communicatively coupled to the processor 1720
via the I/O subsystem 1722, which may be embodied as circuitry
and/or components to facilitate input/output operations with the
processor 1720, the memory 1724, and other components of the
computing device 1700. For example, the I/O subsystem 1722 may be
embodied as, or otherwise include, memory controller hubs,
input/output control hubs, sensor hubs, firmware devices,
communication links (i.e., point-to-point links, bus links, wires,
cables, light guides, printed circuit board traces, etc.) and/or
other components and subsystems to facilitate the input/output
operations. In some embodiments, the I/O subsystem 1722 may form a
portion of a system-on-a-chip (SoC) and be incorporated, along with
the processor 1720, the memory 1724, and other components of the
computing device 1700, on a single integrated circuit chip.
[0087] The data storage device 1726 may be embodied as any type of
device or devices configured for short-term or long-term storage of
data such as, for example, memory devices and circuits, memory
cards, hard disk drives, solid-state drives, non-volatile flash
memory, or other data storage devices. The computing device 1700
may also include a communications subsystem 1728, which may be
embodied as any communication circuit, device, or collection
thereof, capable of enabling communications between the computing
device 1700 and other remote devices over a computer network (not
shown). The communications subsystem 1728 may be configured to use
any one or more communication technology (e.g., wired or wireless
communications) and associated protocols (e.g., Ethernet,
InfiniBand.RTM., Bluetooth.RTM., Wi-Fi.RTM., WiMAX, 3G, 4G LTE,
etc.) to effect such communication. As shown, the communication
subsystem 1728 may include a network interface controller (NIC)
1330.
[0088] The illustrative communications subsystem 1728 includes a
network interface controller (NIC) 1330. The NIC 1730 may be
embodied as one or more add-in-boards, daughtercards, controller
chips, chipsets, circuits, or other devices that may be used by the
computing device 1700 for network communications with remote
devices. For example, the NIC 1730 may be embodied as an expansion
card coupled to the I/O subsystem 1722 over an expansion bus such
as PCI Express. As another example, in some embodiments the NIC
1730 may be embodied as a network controller, host fabric
interface, or other component integrated with the I/O subsystem
1722, the processor 1720, an SoC, and/or one or more other
components of the computing device 1700.
[0089] As shown, the computing device 1700 may also include one or
more peripheral devices 1732. The peripheral devices 1732 may
include any number of additional input/output devices, interface
devices, and/or other peripheral devices. For example, in some
embodiments, the peripheral devices 1732 may include a display,
touch screen, graphics circuitry, keyboard, mouse, speaker system,
microphone, network interface, and/or other input/output devices,
interface devices, and/or peripheral devices.
[0090] Referring now to FIG. 18, in an illustrative embodiment, the
resource manager server 1602 establishes an environment 1800 during
operation. The illustrative environment 1800 includes a topology
manager 1802, a model constructor 1804, a bandwidth limit
determiner 1806, a bandwidth limit programmer 1808, and a
utilization manager 1810. The various components of the environment
1800 may be embodied as hardware, firmware, software, or a
combination thereof. As such, in some embodiments, one or more of
the components of the environment 1800 may be embodied as circuitry
or collection of electrical devices (e.g., topology manager
circuitry 1802, model constructor circuitry 1804, bandwidth limit
determiner circuitry 1806, bandwidth limit programmer circuitry
1808, and/or utilization manager circuitry 1810). It should be
appreciated that, in such embodiments, one or more of the topology
manager circuitry 1802, the model constructor circuitry 1804, the
bandwidth limit determiner circuitry 1806, the bandwidth limit
programmer circuitry 1808, and/or the utilization manager circuitry
1810 may form a portion of the processor 1720, the I/O subsystem
1722, the NIC 1730, and/or other components of the resource manager
server 1602. Additionally, in some embodiments, one or more of the
illustrative components may form a portion of another component
and/or one or more of the illustrative components may be
independent of one another.
[0091] The topology manager 1802 is configured to discover the
topology of the sleds coupled to a layer of switches that are
communicatively coupled to the resource manager server 1602. The
model constructor 1804 is configured to construct a model of
network connectivity between the plurality of sleds and the layer
of switches based on the topology. Constructing the model may
include identifying which sleds of the plurality of sleds are
connected to a particular switch of the layer of switches.
[0092] The bandwidth limit determiner 1806 is configured to
determine an oversubscription of the network based on the model of
network connectivity. The oversubscription is based on an available
bandwidth for the layer of switches and a maximum bandwidth of the
sleds. The bandwidth limit determiner 1806 may determine a network
uplink oversubscription for the layer of switches or may determine
a storage resource oversubscription of the sleds. The bandwidth
limit determiner 1806 is further configured to determine a
bandwidth limit for each sled based on the oversubscription. The
bandwidth limit programmer 1808 is configured to program each sled
with the corresponding bandwidth limit. The bandwidth limit
programmer 1808 may communicate the bandwidth limit to the NIC 1730
of the corresponding sled.
[0093] The utilization manager 1810 is configured to monitor a
bandwidth utilization of the sleds. Monitoring the bandwidth
utilization may include receiving telemetry data from the sleds
that is indicative of the bandwidth utilized by each sled. The
utilization manager 1810 is further configured to determine whether
the network is congested based on the bandwidth utilization of the
plurality of sleds. For example, determining whether the network is
congested may include determining whether a queue depth of the
network exceeds a predetermined queue depth limit for a
predetermined amount of time. In some embodiments, determining
whether the network is congested may include monitoring bandwidth
per class of network traffic, such as NVMe over Ethernet traffic,
field-programmable gate array (FPGA) over Ethernet traffic, storage
traffic, and/or other traffic classes. Each traffic class may be
independently monitored with its own queue depth controls. Further,
bandwidth may be limited at the source or target, or in some
embodiments based on source and target pair combinations. The
utilization manager 1810 is further configured to modify a
bandwidth limit in response to determining that the network is
congested. The bandwidth limit may be reduced for each sled that is
associated with a high input rate flow.
[0094] Referring now to FIG. 19, in an illustrative embodiment, a
storage sled 1610 establishes an environment 1900 during operation.
It should be understood that the environment 1900 may also be
established by other sleds of the system 1600. The illustrative
environment 1900 includes a bandwidth limit manager 1904, a
bandwidth programmer 1906, and a telemetry data manager 1908. The
various components of the environment 1900 may be embodied as
hardware, firmware, software, or a combination thereof. As such, in
some embodiments, one or more of the components of the environment
1900 may be embodied as circuitry or collection of electrical
devices (e.g., bandwidth limit manager circuitry 1904, bandwidth
programmer circuitry 1906, and/or telemetry data manager circuitry
1908). It should be appreciated that, in such embodiments, one or
more of the bandwidth limit manager circuitry 1904, the bandwidth
programmer circuitry 1906, and/or the telemetry data manager
circuitry 1908 may form a portion of the processor 1720, the I/O
subsystem 1722, the NIC 1730, and/or other components of the
storage sled 1610. Additionally, in some embodiments, one or more
of the illustrative components may form a portion of another
component and/or one or more of the illustrative components may be
independent of one another.
[0095] The bandwidth programmer 1906 is configured to receive a
bandwidth limit for the sled from the resource manager server 1602
and to program the bandwidth limit to the NIC 1730 of the sled. The
bandwidth limit manager 1904 is configured to enforce, by the NIC
1730, the bandwidth limit in response to programming the bandwidth
limit.
[0096] The telemetry data manager 1908 is configured to send
telemetry data indicative of utilization of the NIC 1730 to the
resource manager server 1602. The telemetry data may be sent by the
NIC 1730. The telemetry data may indicative of a NIC queue depth
and/or or a network stack queue depth.
[0097] Referring now to FIG. 20, in use, the resource manager
server 1602 may execute a method 2000 for bandwidth allocation. It
should be appreciated that, in some embodiments, the operations of
the method 2000 may be performed by one or more components of the
environment 1800 of the resource manager server 1602 as shown in
FIG. 18. The method 2000 begins in block 2002, in which the
resource manager server 1602 discovers the network topology of the
components of the system 1600. The topology may be predetermined at
design time of the system 1600 or, in some embodiments, may be
discovered using a topology discovery protocol or other discovery
technique. In some embodiments, in block 2004 the resource manager
server 1602 may discover sleds, racks, switches, and network
connections of the system 1600. For example, the resource manager
server 1602 may identify that a sled is connected to a particular
port of a switch. As another example, the resource manager server
1602 may identify that a port of a switch is connected to a
particular port of an upstream switch.
[0098] In block 2006, the resource manager server 1602 constructs a
model of network connectivity between the components of the system
1600. The model may identify network connections and the associated
available bandwidth between sleds, switches, and other network
elements of the system 1600.
[0099] In block 2008, the resource manager server 1602 determines
oversubscription of the system 1600 based on the model of network
connectivity. As described above, the system 1600 may be organized
in layers, and each layer may have a maximum amount of available
bandwidth or other resources. Oversubscription may exist if the
total maximum bandwidth or other resource demand of a layer exceeds
the available bandwidth or other resources of a higher layer. In
some embodiments, in block 2010, the resource manager server 1602
may determine network uplink oversubscription. For example, as
shown in FIG. 16, the sleds 1610, 1612, 1614 are connected to the
switch 1606. Oversubscription may exist if the maximum bandwidth
used by the sleds 1610, 1612, 1614 in combination exceeds the
available bandwidth of the uplink from the switch 1606 to the
switch 1604. Similarly, oversubscription may exist if the maximum
bandwidth used by the sleds 1616, 1618, 1620 exceeds the available
bandwidth of the uplink from the switch 1608 to the switch 1604. In
some embodiments, in block 2012, the resource manager server 1602
may determine storage resource oversubscription. For example,
oversubscription may exist if demand for storage resources of a
sled (e.g., the storage sled 1610) exceeds the available bandwidth
or other resources of that sled.
[0100] In block 2014, the resource manager server 1602 determines
bandwidth limits for each sled in the system 1600 based on the
oversubscription. The bandwidth limits may be determined in order
to prevent or reduce network congestion in the system 1600. For
example, again referring to FIG. 16, the bandwidth limits for sleds
1610, 1612, 1614 may be set so that the combined bandwidth limits
are less than or equal to the uplink bandwidth from the switch 1606
to the switch 1604.
[0101] In block 2016, the resource manager server 1602 programs
each sled with the corresponding bandwidth limit. After being
programmed, each sled enforces the bandwidth limits, as described
further below in connection with FIG. 21. The resource manager
server 1602 may use any technique to program the sled. In some
embodiments, in block 2018 the resource manager server 1602 may
program the NIC 1730 of the sled with the bandwidth limit. For
example, the resource manager server 1602 may communicate
out-of-band or otherwise communicate with the NIC 1730 without
invoking the operating system or other software networking stack of
the sled.
[0102] In block 2020, the resource manager server 1602 may receive
bandwidth telemetry from the sleds of the system 1600. The
bandwidth telemetry may indicate the current bandwidth usage of the
sled and/or whether the associated network connection is congested.
For example, the bandwidth telemetry may indicate queue depth of
the NIC 1730, the associated switch port, and/or the networking
stack of the sled.
[0103] In block 2022, the resource manager server 1602 identifies
network congestion based on the telemetry. The resource manager
server 1602 may use any appropriate algorithm to identify dropped
packets, increased latency, or otherwise identify the network
congestion. In some embodiments, in block 2024, the resource
manager server 1602 may determine whether any queue depth in the
system exceeds a predetermined threshold queue depth for longer
than a predetermined time. For example, the resource manager server
1602 may analyze the queue depth of a NIC 1730, a switch port,
and/or a networking stack of a sled. In block 2026, the resource
manager server 1602 determines whether congestion has been
detected. If not, the method 2000 loops back to block 2020 to
continue monitoring network utilization. If congestion is detected,
the method 2000 advances to block 2028.
[0104] In block 2028, the resource manager server 1602 modifies one
or more bandwidth limits to reduce or eliminate the congestion. In
some embodiments, in block 2030, the resource manager server 1602
may identify one or more high-input rate flows in the system 1600.
For example, one or more storage sleds 1610 generating NVMe over
Ethernet data may generate high-input rate flows. The resource
manager server 1602 may reduce the input rate bandwidth limit
associated with the high-input rate flows. Additionally or
alternatively, in some embodiments the resource manager server 1602
may generate one or more alerts concerning the congestion, and a
network administrator may provide modified bandwidth limits. In
some embodiments, alternate network routes may be possible. If
alternate routes are possible, based on the congestion telemetry
data, different bandwidth limits may be set for different routes to
reduce the congestion rate. After modifying the bandwidth limits,
the method 2000 loops back to block 2016 to program the sleds with
the modified bandwidth limits and continue monitoring network
utilization.
[0105] Referring now to FIG. 21, in use, a storage sled 1610 may
execute a method 2100 for bandwidth allocation. It should be
appreciated that, in some embodiments, the operations of the method
2100 may be performed by one or more components of the environment
1900 of the storage sled 1610 as shown in FIG. 19. The method 2100
begins in block 2102, in which the storage sled 1610 determines
whether an update to a bandwidth limit has been received from the
resource manager server 1602. As described above in connection with
FIG. 20, the resource manager server 1602 may program the bandwidth
limit to the storage sled 1610 in response to modeling network
connectivity and determining an oversubscription of the system 1600
and/or in response to detecting network congestion based on
telemetry data. If an update to the bandwidth limit has not been
received, the method 2100 branches ahead to block 2108, described
below. If an update to the bandwidth limit has been received, the
method 2100 advances to block 2104.
[0106] In block 2104, the storage sled 1610 programs one or more
network interface controllers (NICs) 1330 of the storage sled with
the new bandwidth limit. After being programmed, the NIC 1730 may
throttle or otherwise limit bandwidth used by the storage sled 1610
to below the bandwidth limit. In particular, in some embodiments in
block 2106 the storage sled 1610 may set a maximum input bandwidth
for the NIC 1730. Thus, the bandwidth limits may limit the amount
of data (e.g., NVMe over Ethernet data) generated by the storage
sled 1610 and submitted to the switch 1606. Although illustrated as
being enforced by the NIC 1730, it should be understood that in
some embodiments, the bandwidth limits may be enforced by other
components of the storage sled 1610, such as an operating system,
software networking stack, NVMe over Ethernet subsystem, or other
component.
[0107] In block 2108, the storage sled 1610 determines whether to
send telemetry data to the resource manager server 1602. For
example, the storage sled 1610 may be configured by an
administrator to send telemetry data. In some embodiments, the
storage sled 1610 may send telemetry data in response to certain
events, for example in response to detected network congestion. If
the storage sled 1610 determines not to send telemetry data, the
method 2100 loops back to block 2102 to continue monitoring for
updated bandwidth limits. If the storage sled 1610 determines to
send telemetry data, the method 2100 advances to block 2110.
[0108] In block 2110, the storage sled 1610 sends bandwidth
telemetry data to the resource manager server 1602. As described
above, the bandwidth telemetry may indicate the current bandwidth
usage of the sled and/or whether the associated network connection
is congested. For example, the bandwidth telemetry may indicate
queue depth of the NIC 1730, the associated switch port, and/or the
network stack of the sled. In some embodiments, in block 2112 the
storage sled 1610 may retrieve the telemetry data from the NIC 1730
of the storage sled 1610. For example, an operating system,
software networking stack, or other component of the storage sled
1610 may retrieve telemetry data from the NIC 1730. In some
embodiments, in block 2114 the storage sled 1610 may send the
telemetry data from the NIC 1730 to the resource manager server
1602. The NIC 1730 may send the telemetry data out-of-band or
otherwise without the involvement of the operating system, software
networking stack, or other components of the storage sled 1610.
After sending the telemetry data, the method 2100 loops back to
block 2102 to continue monitoring for updated bandwidth limits.
EXAMPLES
[0109] Illustrative examples of the technologies disclosed herein
are provided below. An embodiment of the technologies may include
any one or more, and any combination of, the examples described
below.
[0110] Example 1 includes a resource manager server for bandwidth
allocation, the resource manager server comprising: one or more
processors; and one or more memory devices having stored therein a
plurality of instructions that, when executed by the one or more
processors, cause the resource manager server to: discover a
topology of a plurality of sleds coupled to a layer of switches
that are communicatively coupled to the resource manager server;
construct a model of network connectivity between the plurality of
sleds and the layer of switches based on the topology; determine an
oversubscription of a network based on the model of network
connectivity, wherein the oversubscription is based on an available
bandwidth for the layer of switches and a maximum bandwidth of the
plurality of sleds; determine a bandwidth limit for each sled of
the plurality of sleds based on the oversubscription; and program
each sled of the plurality of sleds with the corresponding
bandwidth limit.
[0111] Example 2 includes the subject matter of Example 1, and
wherein to construct the model of network connectivity comprises to
identify which sleds of the plurality of sleds are connected to a
particular switch of the layer of switches.
[0112] Example 3 includes the subject matter of any of Examples 1
and 2, and wherein to determine the oversubscription comprises to
determine a network uplink oversubscription for the layer of
switches.
[0113] Example 4 includes the subject matter of any of Examples
1-3, and wherein to determine the oversubscription comprises to
determine a storage resource oversubscription of the plurality of
sleds.
[0114] Example 5 includes the subject matter of any of Examples
1-4, and wherein to program the bandwidth limit for each sled
comprises to communicate the bandwidth limit to a network interface
controller of the corresponding sled.
[0115] Example 6 includes the subject matter of any of Examples
1-5, and wherein the one or more memory devices have stored therein
a plurality of instructions that, when executed by the one or more
processors, further cause the resource manager server to: monitor a
bandwidth utilization of the plurality of sleds; determine whether
the network is congested based on the bandwidth utilization of the
plurality of sleds; and modify a bandwidth limit in response to a
determination that the network is congested.
[0116] Example 7 includes the subject matter of any of Examples
1-6, and wherein to monitor the bandwidth utilization of the
plurality of sleds comprises to receive telemetry data from the
plurality of sleds indicative of the bandwidth utilized by each
sled.
[0117] Example 8 includes the subject matter of any of Examples
1-7, and wherein to determine whether the network is congested
comprises to determine whether a queue depth of the network exceeds
a predetermined queue depth limit for a predetermined amount of
time.
[0118] Example 9 includes the subject matter of any of Examples
1-8, and wherein the queue depth comprises a switch port queue
depth, a network interface controller queue depth, or a network
stack queue depth.
[0119] Example 10 includes the subject matter of any of Examples
1-9, and wherein to modify the bandwidth limit comprises to:
identify a first sled of the plurality of sleds associated with a
high input rate flow; and reduce an input rate of the bandwidth
limit for the first sled.
[0120] Example 11 includes a sled for bandwidth allocation, the
sled communicatively coupled to a layer of switches that are
communicatively coupled to a resource manager server on a network,
the sled comprising: one or more processors; and one or more memory
devices having stored therein a plurality of instructions that,
when executed by the one or more processors, cause the sled to:
receive a bandwidth limit for the sled from the resource manager
server; program the bandwidth limit to a network interface
controller of the sled; and enforce, by the network interface
controller, the bandwidth limit in response to programming of the
bandwidth limit.
[0121] Example 12 includes the subject matter of Example 11, and
wherein the one or more memory devices have stored therein a
plurality of instructions that, when executed by the one or more
processors, further cause the sled to send telemetry data
indicative of a utilization of the network interface controller to
the resource manager server of the network.
[0122] Example 13 includes the subject matter of any of Examples 11
and 12, and wherein to send the telemetry data comprises to send
the telemetry data by the network interface controller.
[0123] Example 14 includes the subject matter of any of Examples
11-13, and wherein the telemetry data is indicative of a network
interface controller queue depth, or a network stack queue
depth.
[0124] Example 15 includes a method for bandwidth allocation, the
method comprising: discovering, by a resource manager server of a
network, a topology of a plurality of sleds coupled to a layer of
switches that are communicatively coupled to the resource manager
server; constructing, by the resource manager server, a model of
network connectivity between the plurality of sleds and the layer
of switches based on the topology; determining, by the resource
manager server, an oversubscription of the network based on the
model of network connectivity, wherein the oversubscription is
based on an available bandwidth for the layer of switches and a
maximum bandwidth of the plurality of sleds; determining, by the
resource manager server, a bandwidth limit for each sled of the
plurality of sleds based on the oversubscription; and programming,
by the resource manager server, each sled of the plurality of sleds
with the corresponding bandwidth limit.
[0125] Example 16 includes the subject matter of Example 15, and
wherein constructing the model of network connectivity comprises
identifying which sleds of the plurality of sleds are connected to
a particular switch of the layer of switches.
[0126] Example 17 includes the subject matter of any of Examples 15
and 16, and wherein determining the oversubscription comprises
determining a network uplink oversubscription for the layer of
switches.
[0127] Example 18 includes the subject matter of any of Examples
15-17, and wherein determining the oversubscription comprises
determining a storage resource oversubscription of the plurality of
sleds.
[0128] Example 19 includes the subject matter of any of Examples
15-18, and wherein programming the bandwidth limit for each sled
comprises communicating the bandwidth limit to a network interface
controller of the corresponding sled.
[0129] Example 20 includes the subject matter of any of Examples
15-19, and further comprising: monitoring, by the resource manager
server, a bandwidth utilization of the plurality of sleds;
determining, by the resource manager server, whether the network is
congested based on the bandwidth utilization of the plurality of
sleds; and modifying, by the resource manager server, a bandwidth
limit in response to determining that the network is congested.
[0130] Example 21 includes the subject matter of any of Examples
15-20, and wherein monitoring the bandwidth utilization of the
plurality of sleds comprises receiving telemetry data from the
plurality of sleds indicative of the bandwidth utilized by each
sled.
[0131] Example 22 includes the subject matter of any of Examples
15-21, and wherein determining whether the network is congested
comprises determining whether a queue depth of the network exceeds
a predetermined queue depth limit for a predetermined amount of
time.
[0132] Example 23 includes the subject matter of any of Examples
15-22, and wherein the queue depth comprises a switch port queue
depth, a network interface controller queue depth, or a network
stack queue depth.
[0133] Example 24 includes the subject matter of any of Examples
15-23, and wherein modifying the bandwidth limit comprises:
identifying a first sled of the plurality of sleds associated with
a high input rate flow; and reducing an input rate of the bandwidth
limit for the first sled.
[0134] Example 25 includes a method for bandwidth allocation, the
method comprising: receiving, by a sled of a plurality of sleds
communicatively coupled to a layer of switches that are
communicatively coupled to a resource manager server in a network,
a bandwidth limit for the sled from the resource manager server;
programming, by the sled, the bandwidth limit to a network
interface controller of the sled; and enforcing, by the network
interface controller of the sled, the bandwidth limit in response
to programming the bandwidth limit.
[0135] Example 26 includes the subject matter of Example 25, and
further comprising sending, by the sled, telemetry data indicative
of a utilization of the network interface controller to the
resource manager server of the network.
[0136] Example 27 includes the subject matter of any of Examples 25
and 26, and wherein sending the telemetry data comprises sending
the telemetry data by the network interface controller.
[0137] Example 28 includes the subject matter of any of Examples
25-27, and wherein the telemetry data is indicative of a network
interface controller queue depth, or a network stack queue
depth.
[0138] Example 29 includes a computing device comprising: a
processor; and a memory having stored therein a plurality of
instructions that when executed by the processor cause the
computing device to perform the method of any of Examples
15-28.
[0139] Example 30 includes one or more non-transitory, computer
readable storage media comprising a plurality of instructions
stored thereon that in response to being executed result in a
computing device performing the method of any of Examples
15-28.
[0140] Example 31 includes a computing device comprising means for
performing the method of any of Examples 15-28.
[0141] Example 32 includes a resource manager server for bandwidth
allocation, the resource manager server comprising: topology
manager circuitry to discover a topology of a plurality of sleds
coupled to a layer of switches that are communicatively coupled to
the resource manager server; model constructer circuitry to
construct a model of network connectivity between the plurality of
sleds and the layer of switches based on the topology; bandwidth
limit determiner circuitry to (i) determine an oversubscription of
a network based on the model of network connectivity, wherein the
oversubscription is based on an available bandwidth for the layer
of switches and a maximum bandwidth of the plurality of sleds, and
(ii) determine a bandwidth limit for each sled of the plurality of
sleds based on the oversubscription; and bandwidth limit programmer
circuitry to program each sled of the plurality of sleds with the
corresponding bandwidth limit.
[0142] Example 33 includes the subject matter of Example 32, and
wherein to construct the model of network connectivity comprises to
identify which sleds of the plurality of sleds are connected to a
particular switch of the layer of switches.
[0143] Example 34 includes the subject matter of any of Examples 32
and 33, and wherein to determine the oversubscription comprises to
determine a network uplink oversubscription for the layer of
switches.
[0144] Example 35 includes the subject matter of any of Examples
32-34, and wherein to determine the oversubscription comprises to
determine a storage resource oversubscription of the plurality of
sleds.
[0145] Example 36 includes the subject matter of any of Examples
32-35, and wherein to program the bandwidth limit for each sled
comprises to communicate the bandwidth limit to a network interface
controller of the corresponding sled.
[0146] Example 37 includes the subject matter of any of Examples
32-36, and further comprising utilization manager circuitry to:
monitor a bandwidth utilization of the plurality of sleds;
determine whether the network is congested based on the bandwidth
utilization of the plurality of sleds; and modify a bandwidth limit
in response to a determination that the network is congested.
[0147] Example 38 includes the subject matter of any of Examples
32-37, and wherein to monitor the bandwidth utilization of the
plurality of sleds comprises to receive telemetry data from the
plurality of sleds indicative of the bandwidth utilized by each
sled.
[0148] Example 39 includes the subject matter of any of Examples
32-38, and wherein to determine whether the network is congested
comprises to determine whether a queue depth of the network exceeds
a predetermined queue depth limit for a predetermined amount of
time.
[0149] Example 40 includes the subject matter of any of Examples
32-39, and wherein the queue depth comprises a switch port queue
depth, a network interface controller queue depth, or a network
stack queue depth.
[0150] Example 41 includes the subject matter of any of Examples
32-40, and wherein to modify the bandwidth limit comprises to:
identify a first sled of the plurality of sleds associated with a
high input rate flow; and reduce an input rate of the bandwidth
limit for the first sled.
[0151] Example 42 includes a sled for bandwidth allocation, the
sled communicatively coupled to a layer of switches that
communicatively coupled to a resource manager server on a network,
the sled comprising: bandwidth programmer circuitry to: (i) receive
a bandwidth limit for the sled from the resource manager server,
and (ii) program the bandwidth limit to a network interface
controller of the sled; and bandwidth limit manager circuitry to
enforce, by the network interface controller, the bandwidth limit
in response to programming of the bandwidth limit.
[0152] Example 43 includes the subject matter of Example 42, and
further comprising telemetry data manager circuitry to send
telemetry data indicative of a utilization of the network interface
controller to the resource manager server of the network.
[0153] Example 44 includes the subject matter of any of Examples 42
and 43, and wherein to send the telemetry data comprises to send
the telemetry data by the network interface controller.
[0154] Example 45 includes the subject matter of any of Examples
42-44, and wherein the telemetry data is indicative of a network
interface controller queue depth, or a network stack queue
depth.
[0155] Example 46 includes a resource manager server for bandwidth
allocation, the resource manager server comprising: means for
discovering a topology of a plurality of sleds coupled to a layer
of switches that are communicatively coupled to the resource
manager server in a network; means for constructing a model of
network connectivity between the plurality of sleds and the layer
of switches based on the topology; means for determining an
oversubscription of the network based on the model of network
connectivity, wherein the oversubscription is based on an available
bandwidth for the layer of switches and a maximum bandwidth of the
plurality of sleds; means for determining a bandwidth limit for
each sled of the plurality of sleds based on the oversubscription;
and means for programming each sled of the plurality of sleds with
the corresponding bandwidth limit.
[0156] Example 47 includes the subject matter of Example 46, and
wherein the means for constructing the model of network
connectivity comprises means for identifying which sleds of the
plurality of sleds are connected to a particular switch of the
layer of switches.
[0157] Example 48 includes the subject matter of any of Examples 46
and 47, and wherein the means for determining the oversubscription
comprises means for determining a network uplink oversubscription
for the layer of switches.
[0158] Example 49 includes the subject matter of any of Examples
46-48, and wherein the means for determining the oversubscription
comprises means for determining a storage resource oversubscription
of the plurality of sleds.
[0159] Example 50 includes the subject matter of any of Examples
46-49, and wherein the means for programming the bandwidth limit
for each sled comprises circuitry for communicating the bandwidth
limit to a network interface controller of the corresponding
sled.
[0160] Example 51 includes the subject matter of any of Examples
46-50, and further comprising: means for monitoring a bandwidth
utilization of the plurality of sleds; means for determining
whether the network is congested based on the bandwidth utilization
of the plurality of sleds; and means for modifying a bandwidth
limit in response to determining that the network is congested.
[0161] Example 52 includes the subject matter of any of Examples
46-51, and wherein the means for monitoring the bandwidth
utilization of the plurality of sleds comprises circuitry for
receiving telemetry data from the plurality of sleds indicative of
the bandwidth utilized by each sled.
[0162] Example 53 includes the subject matter of any of Examples
46-52, and wherein the means for determining whether the network is
congested comprises means for determining whether a queue depth of
the network exceeds a predetermined queue depth limit for a
predetermined amount of time.
[0163] Example 54 includes the subject matter of any of Examples
46-53, and wherein the queue depth comprises a switch port queue
depth, a network interface controller queue depth, or a network
stack queue depth.
[0164] Example 55 includes the subject matter of any of Examples
46-54, and wherein the means for modifying the bandwidth limit
comprises: means for identifying a first sled of the plurality of
sleds associated with a high input rate flow; and means for
reducing an input rate of the bandwidth limit for the first
sled.
[0165] Example 56 includes a sled for bandwidth allocation, the
sled communicatively coupled to a layer of switches that are
communicatively coupled to a resource manager server on a network,
the sled comprising: circuitry for receiving a bandwidth limit for
the sled from the resource manager server; means for programming
the bandwidth limit to a network interface controller of the sled;
and means for enforcing, by the network interface controller of the
sled, the bandwidth limit in response to programming the bandwidth
limit.
[0166] Example 57 includes the subject matter of Example 56, and
further comprising means for sending telemetry data indicative of a
utilization of the network interface controller to the resource
manager server of the network.
[0167] Example 58 includes the subject matter of any of Examples 56
and 57, and wherein the means for sending the telemetry data
comprises means for sending the telemetry data by the network
interface controller.
[0168] Example 59 includes the subject matter of any of Examples
56-58, and wherein the telemetry data is indicative of a network
interface controller queue depth, or a network stack queue
depth.
* * * * *
References