The present invention relates generally to data communications, and particularly to high-speed, large-scale computer networks.
High-speed computer networks, such as data center networks and High-Performance Computing (HPC) compute-node clusters, comprise switches that are linked together in a selected interconnection topology. Such topologies include, for example, mesh, Fat-Tree (FT) and Dragonfly (DF) topologies. The term “switches” is used broadly in the context of the present description and in the claims to refer to all sorts of network switching nodes, including, without limitation, bridges, and routers.
The Dragonfly topology is described, for example, by Kim et al., in “Technology-Driven, Highly-Scalable Dragonfly Topology,” Proceedings of the 2008 International Symposium on Computer Architecture (2008), pages 77-88. U.S. Patent Application Publication 2010/0049942 describes a Dragonfly processor interconnect network that comprises a plurality of processor nodes, a plurality of routers, each router directly coupled to a plurality of terminal nodes, the routers coupled to one another and arranged into a group, and a plurality of groups of routers, such that each group is connected to each other group via at least one direct connection.
As another example, U.S. Pat. No. 9,699,067, whose disclosure is incorporated herein by reference, describes a topology referred to as “Dragonfly Plus.” In this topology, a communication network includes multiple nodes, which are arranged in groups such that the nodes in each group are interconnected in a bipartite topology and the groups are interconnected in a mesh topology. The nodes are configured to convey traffic between source hosts and respective destination hosts by routing packets among the nodes on paths that do not traverse any intermediate hosts other than the source and destination hosts.
“Expander” network topologies have been proposed as a more optimal alternative to traditional data center networks, based on principles of graph theory. Topologies of this sort are described, for example, by Valadarsky et al., in “Xpander: Towards Optimal-Performance Datacenters,” presented at CoNEXT '16 (December 2016, Irvine, Calif.). The authors show by theoretical computations and simulation that Xpander achieves “near-optimal performance” in terms of throughput, bandwidth guarantees, robustness to traffic variations, resiliency to failures, incremental expandability, and path lengths.
Embodiments of the present invention that are described hereinbelow provide improved systems and methods for data communications.
There is therefore provided, in accordance with an embodiment of the invention, a data communication system, including a plurality of mutually-disjoint sets of switches, each set including multiple mutually-disjoint subsets of the switches in the set. Local links interconnect the switches in each of the subsets in a fully-connected topology, such that all the switches in any given subset of any given set of the switches are connected by the local links to all other switches in the given subset, while none of the switches in the given subset are connected in a single hop to any of the switches in any other subset within the given set. Global links interconnect the sets of the switches. Each global link connects a respective first switch in one of the sets to a respective second switch in another one of the sets, such that each of the subsets in any given one of the sets of the switches is connected in a single hop by at least one of the global links to at least one of the subsets of every other one of the sets of the switches.
In one embodiment, within each subset of the switches, a first one of the switches in the subset is connected by a first global link to a first one of the switches in a first one of the other sets, and a second one of the switches in the subset is connected by a second global link to a second one of the switches in a second one of the other sets.
Additionally or alternatively, different ones of the subsets in any given one of the sets are connected by respective ones of the global links in single hops to different, respective ones of the subsets of the other sets of the switches.
Further additionally or alternatively, at least some of the subsets in any given one of the sets of the switches are not connected in a single hop by the global links to all the subsets in every other one of the sets of the switches. In one embodiment, each of the subsets in each of the sets of the switches is connected in a single hop by a respective one of the global links to a single respective one of the subsets in every other one of the sets of the switches.
In another embodiment, all the subsets in each of the sets of the switches are connected in a single hop by respective ones of the global links to all the subsets in every other one of the sets of the switches.
In some embodiments, the system includes a routing manager, which is configured to define paths for transmission of packets among the switches in the system over the local and global links, wherein the paths are limited to a predefined maximal number of hops. In a disclosed embodiment, the switches are configured to transmit the packets over the paths using a number of virtual channels that is equal to the predefined maximal number of hops, while transitioning through the virtual channels in a predefined sequence on each hop of each of the paths.
There is also provided, in accordance with an embodiment of the invention, a method for communication, which includes partitioning switches in a network among a plurality of mutually-disjoint sets of switches, each set including multiple mutually-disjoint subsets of the switches in the set. The switches in each of the subsets are interconnected using local links in a fully-connected topology, such that all the switches in any given subset of any given set of the switches are connected by the local links to all other switches in the given subset, while none of the switches in the given subset are connected in a single hop to any of the switches in any other subset within the given set. The sets of the switches are interconnected using global links, such that each global link connects a respective first switch in one of the sets to a respective second switch in another one of the sets, and such that each of the subsets in any given one of the sets of the switches is connected in a single hop by at least one of the global links to at least one of the subsets of every other one of the sets of the switches.
There is additionally provided, in accordance with an embodiment of the invention, a data communication system, including a plurality of mutually-disjoint sets of switches, each set including multiple mutually-disjoint subsets of the switches in the set. Local links interconnect the switches within each of the subsets in a fully-connected topology, while none of the switches in any given subset are connected in a single hop to any of the switches in any other subset within the same set. Global links interconnect the sets of the switches. Each global link connects one switch in one of the sets to another switch in another one of the sets, such that each of the subsets in any given set of the switches is connected in a single hop by at least one global link to at least one of the subsets of every other set of the switches.
The present invention will be more fully understood from the following detailed description of the embodiments thereof, taken together with the drawings in which:
The cost-effectiveness of a network topology can be measured in terms of its “port utilization,” which is defined as PU=num of hosts/num of switches*Radix. The port utilization, in other words, specifies the number of cables that must be used to connect a given number of hosts. As cables are a major factor in the cost of high-speed networks, it is desirable that the port utilization be as high as possible, while still meeting performance requirements in terms of low communication latency and high reliability. Dragonfly topologies are popular in data center networks and HPC clusters because they offer high connectivity and simplicity of routing among network nodes. In comparison with newer topologies, however, such as the above-mentioned “Xpander” topology, Dragonfly networks are inferior in terms of port utilization.
Embodiments of the present invention that are described herein provide novel network topologies that offer low communication latency and ease of routing that are comparable to Dragonfly networks, while achieving much higher port utilization. The present embodiments are based on fully-connected local subsets of the switches in the network, as in Dragonfly networks, but make sparser, more optimal use of global links among these subsets.
In the disclosed embodiments, the switches in a data communication system are partitioned into multiple mutually-disjoint sets, and the switches in each such set are partitioned into multiple mutually-disjoint subsets. Within each subset, local links interconnect the switches in a fully-connected topology, meaning that all the switches in any given subset are connected in a single hop to all other switches in the subset. Within any given set, however, none of the switches in any given subset are connected in a single hop to any of the switches in any other subset within the given set.
The different sets of switches are interconnected by global links, i.e., each global link connects a switch in one of the sets to a switch in another set. The global links are laid out so each of the subsets in any given set of the switches is connected in a single hop by at least one global link to at least one of the subsets of every other one of the sets of the switches. The number and connectivity of the global links are selected so as to optimize port utilization while meeting performance targets such as low transmission latency and high resilience against failures.
The term “hop,” as used in the context of the present description and in the claims, refers to a single link between a pair of network devices that is traversed by a packet on its path through the network. In other words, if a packet traverses N nodes on its path through the network (including the source and destination nodes), it will cover N−1 hops. In some embodiments, to achieve high port utilization, at least some of the subsets in a given set of the switches are connected in a single hop by a global link only to certain subsets within the other sets of the switches, but not to all subsets. To maintain low latency and ease of routing, however, a given subset in a given set of the switches may be connected in single hops by global links to multiple subsets of each other set. In one embodiment, each of the subsets of the switches is connected in a single hop by a global link to one of the subsets in every other set of the switches.
Reference is now made to
System 20 comprises a network of switches 30, which are divided into multiple mutually-disjoint sets 22, 24, 26, 28. Each of these sets is divided into a number of mutually-disjoint subsets 32, 34, 36. Although network 20 in this example comprises four sets of switches with three subsets of three switches each in each set, the principles of the present embodiment may similarly be applied to larger or smaller networks, with larger or smaller numbers of switches in each subset (but no less than two switches in each subset) and larger or smaller numbers of subsets in each set. Furthermore, although symmetrical configurations, such as that shown in
As shown in
In each subset 32, 34, 36 of any one of sets 22, 24, 26, 28, local links 40 interconnect switches 30 within the subset in a fully-connected topology, meaning that all the switches in any given subset of any given set of the switches are connected by local links 40 in a single hop to all the other switches in the same subset. On the other hand, none of the switches in any given subset 32, 34 or 36 is connected in a single hop to any of the switches in any other subset within the same set. Thus, for example, in set 24, all of switches 30 in subset 32 are connected by local links 40 to the other switches in subset 32, but none of these switches are connected in a single hop to any of the switches in subsets 34 and 36 of set 24. Therefore, to route a packet from a source in subset 32 in set 24 to a destination in subset 34 in set 24, it is necessary to transmit the packet from subset 32 to a switch in a different set (22, 26 or 28), which then forwards the packet over one or more additional hops to the destination.
Global links 44 interconnect the different sets 22, 24, 26 and 28 of switches 30. Each global link connects a respective switch in one of the sets to a switch in another one of the sets. Global links 44 are arranged such that each of subsets 32, 34 and 36 in any given set of the switches is connected in a single hop by at least one global link 44 to at least one of the subsets of every other one of the sets of the switches. With this minimal level of connectivity, each set 22, 24, 26, 28 will be connected to each other set of the switches by multiple global links 44, each connecting to a different one of the subsets in the set. This topology enables packets to be routed throughout system 20 with high port utilization, as defined above.
Furthermore, in the topology that is shown in
For similar reasons, in some embodiments, at least some of subsets 32, 34, 36 in any given set 22, 24, 26, 28 of switches 30 are not connected in a single hop by global links to all the subsets in every other set of the switches. In one embodiment, each of the subsets in a given set of the switches is connected in a single hop by a global link to a single respective subset in every other set of the switches. Thus, two or more hops may be required to transmit a packet from a given subset in one set of the switches to one or more of the subsets in another set of the switches. The global links are laid out, however, so that connections (including multi-hop connections) exist between all subsets of the switches. Within each subset, switches 30 are fully connected by local links 40, as noted earlier.
Alternatively, as shown in
Once the network topology has been defined, a routing manager 54 (
Routing manager 54 sets a maximal path length for all flows that are to be routed in system 20, at a length setting step 70. This maximal path length specifies the maximal number of hops that will be permitted on any path between a source and a destination node in system 20 and is set to a value large enough to ensure that all nodes in the system are able to communicate with one another. Increasing the maximal path lengths enables more uniform spreading of traffic across the network, but at the expense of greater latency and possibly increased memory requirements in switches 30 to accommodate a larger number of virtual channels (as explained below).
Routing manager 54 selects pairs of source and destination nodes in system 20, at a pair selection step. For each pair, routing manager 54 applies a routing algorithm in order to identify all paths between the source and destination nodes having a path length that is less than or equal to the maximum, at a path identification step 74. The paths are classified by length, at a path classification step 76, from the shortest path(s) connecting the selected pair of source and destination nodes up to the maximum permitted path length. This routing procedure continues until all pairs of source and destination nodes have been covered, at a pair coverage step 78.
Based on the set of paths defined at step 76, routing manager 54 builds routing tables for all switches 30, at a routing step 80. The routing tables typically include multiple alternative paths to at least some of the destinations, thus enabling switches 30 to select the next hop for each packet adaptively, for example based on reports of network congestion. In this manner, switches 30 will distribute traffic evenly across links 40 and 44 in system 20. In building the routing tables, routing manager 54 prioritizes shorter paths while avoiding overburdening any of the links. The routing information is stored by switches 30 in respective forwarding tables 52 (
In order to avoid possible deadlocks, routing manager 54 instructs switches 30 to use a different virtual channel (VC) on each hop of each of the paths in the routing tables, at a VC assignment step 82. For this purpose, for example, packets are transmitted over the first hop on each path using a default VC, which is denoted VC0. At each successive hop, the VC is incremented, meaning that the packet is transmitted using VC1 on the second hop, VC2 on the third hop, and so forth. Thus, on each hop along any given path, each VC transitions deterministically to the next VC in the sequence, and there is no VC that transitions back to VC0. The number of virtual channels (including VC0) that is required in this scheme is equal to the maximal path length that was set at step 70. The deterministic, unidirectional progression of the virtual channels along each path ensures that no credit loops will arise on any of the paths.
It will be appreciated that the embodiments described above are cited by way of example, and that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention includes both combinations and subcombinations of the various features described hereinabove, as well as variations and modifications thereof which would occur to persons skilled in the art upon reading the foregoing description and which are not disclosed in the prior art.
Number | Name | Date | Kind |
---|---|---|---|
4312064 | Bench et al. | Jan 1982 | A |
6115385 | Vig | Sep 2000 | A |
6169741 | Lemaire et al. | Jan 2001 | B1 |
6480500 | Erimli et al. | Nov 2002 | B1 |
6532211 | Rathonyi et al. | Mar 2003 | B1 |
6553028 | Tang et al. | Apr 2003 | B1 |
6614758 | Wong | Sep 2003 | B2 |
6665297 | Harigochi et al. | Dec 2003 | B1 |
6775268 | Wang et al. | Aug 2004 | B1 |
6795886 | Nguyen | Sep 2004 | B1 |
6804532 | Moon et al. | Oct 2004 | B1 |
6807175 | Jennings | Oct 2004 | B1 |
6831918 | Kavak | Dec 2004 | B1 |
6912589 | Jain et al. | Jun 2005 | B1 |
6912604 | Tzeng et al. | Jun 2005 | B1 |
6950428 | Horst et al. | Sep 2005 | B1 |
7010607 | Bunton | Mar 2006 | B1 |
7076569 | Bailey et al. | Jul 2006 | B1 |
7221676 | Green et al. | May 2007 | B2 |
7234001 | Simpson et al. | Jun 2007 | B2 |
7274869 | Pan et al. | Sep 2007 | B1 |
7286535 | Ishikawa et al. | Oct 2007 | B2 |
7401157 | Costantino et al. | Jul 2008 | B2 |
7590110 | Beshai | Sep 2009 | B2 |
7676597 | Kagan et al. | Mar 2010 | B2 |
7746854 | Ambe et al. | Jun 2010 | B2 |
7899930 | Turner et al. | Mar 2011 | B1 |
7924837 | Shabtay et al. | Apr 2011 | B1 |
7936770 | Frattura et al. | May 2011 | B1 |
7969980 | Florit et al. | Jun 2011 | B1 |
8094569 | Gunukula et al. | Jan 2012 | B2 |
8175094 | Bauchot et al. | May 2012 | B2 |
8195989 | Lu et al. | Jun 2012 | B1 |
8213315 | Crupnicoff et al. | Jul 2012 | B2 |
8401012 | Underwood et al. | Mar 2013 | B2 |
8489718 | Brar et al. | Jul 2013 | B1 |
8495194 | Brar et al. | Jul 2013 | B1 |
8570865 | Goldenberg et al. | Oct 2013 | B2 |
8576715 | Bloch et al. | Nov 2013 | B2 |
8605575 | Gunukula et al. | Dec 2013 | B2 |
8621111 | Marr et al. | Dec 2013 | B2 |
8625427 | Terry et al. | Jan 2014 | B1 |
8681641 | Sajassi et al. | Mar 2014 | B1 |
8737269 | Zhou | May 2014 | B1 |
8755389 | Poutievski et al. | Jun 2014 | B1 |
8774063 | Beecroft | Jul 2014 | B2 |
8867356 | Bloch et al. | Oct 2014 | B2 |
8873567 | Mandal et al. | Oct 2014 | B1 |
8908510 | Sela et al. | Dec 2014 | B2 |
8908704 | Koren et al. | Dec 2014 | B2 |
9014006 | Haramaty et al. | Apr 2015 | B2 |
9042234 | Liljenstolpe et al. | May 2015 | B1 |
9137143 | Parker et al. | Sep 2015 | B2 |
9231888 | Bogdanski et al. | Jan 2016 | B2 |
9264382 | Bogdanski et al. | Feb 2016 | B2 |
9385949 | Vershkov et al. | Jul 2016 | B2 |
9544185 | Yadav et al. | Jan 2017 | B1 |
9548960 | Haramaty et al. | Jan 2017 | B2 |
9571400 | Mandal et al. | Feb 2017 | B1 |
9584429 | Haramaty et al. | Feb 2017 | B2 |
9699067 | Haramaty | Jul 2017 | B2 |
9699095 | Elias et al. | Jul 2017 | B2 |
9729473 | Haramaty et al. | Aug 2017 | B2 |
9876727 | Gaist et al. | Jan 2018 | B2 |
9985910 | Gafni et al. | May 2018 | B2 |
10009277 | Goldenberg et al. | Jun 2018 | B2 |
10079782 | Haramaty et al. | Sep 2018 | B2 |
10200294 | Shpiner et al. | Feb 2019 | B2 |
10205683 | Elias et al. | Feb 2019 | B2 |
10218642 | Mula et al. | Feb 2019 | B2 |
10230652 | Haramaty et al. | Mar 2019 | B2 |
10389646 | Zdornov et al. | Aug 2019 | B2 |
10554556 | Haramaty et al. | Feb 2020 | B2 |
10574546 | Levi et al. | Feb 2020 | B2 |
10644995 | Levy et al. | May 2020 | B2 |
11005724 | Shpigelman et al. | May 2021 | B1 |
11310163 | Lo et al. | Apr 2022 | B1 |
20010043564 | Bloch et al. | Nov 2001 | A1 |
20010043614 | Viswanadham et al. | Nov 2001 | A1 |
20020009073 | Furukawa et al. | Jan 2002 | A1 |
20020013844 | Garrett et al. | Jan 2002 | A1 |
20020026525 | Armitage | Feb 2002 | A1 |
20020039357 | Lipasti et al. | Apr 2002 | A1 |
20020067693 | Kodialam et al. | Jun 2002 | A1 |
20020071439 | Reeves et al. | Jun 2002 | A1 |
20020085586 | Tzeng | Jul 2002 | A1 |
20020136163 | Kawakami et al. | Sep 2002 | A1 |
20020138645 | Shinomiya et al. | Sep 2002 | A1 |
20020141412 | Wong | Oct 2002 | A1 |
20020165897 | Kagan et al. | Nov 2002 | A1 |
20020176363 | Durinovic-Johri et al. | Nov 2002 | A1 |
20030016624 | Bare | Jan 2003 | A1 |
20030039260 | Fujisawa | Feb 2003 | A1 |
20030065856 | Kagan et al. | Apr 2003 | A1 |
20030079005 | Myers et al. | Apr 2003 | A1 |
20030097438 | Bearden et al. | May 2003 | A1 |
20030223453 | Stoler et al. | Dec 2003 | A1 |
20040024903 | Costatino et al. | Feb 2004 | A1 |
20040062242 | Wadia et al. | Apr 2004 | A1 |
20040111651 | Mukherjee et al. | Jun 2004 | A1 |
20040202473 | Nakamura et al. | Oct 2004 | A1 |
20050013245 | Sreemanthula | Jan 2005 | A1 |
20050154790 | Nagata et al. | Jul 2005 | A1 |
20050157641 | Roy | Jul 2005 | A1 |
20050259588 | Preguica | Nov 2005 | A1 |
20060126627 | Diouf | Jun 2006 | A1 |
20060143300 | See et al. | Jun 2006 | A1 |
20060182034 | Klinker et al. | Aug 2006 | A1 |
20060215645 | Kangyu | Sep 2006 | A1 |
20060291480 | Cho et al. | Dec 2006 | A1 |
20070030817 | Arunachalam et al. | Feb 2007 | A1 |
20070058536 | Vaananen et al. | Mar 2007 | A1 |
20070058646 | Hermoni | Mar 2007 | A1 |
20070070998 | Sethuram et al. | Mar 2007 | A1 |
20070091911 | Watanabe et al. | Apr 2007 | A1 |
20070104192 | Yoon et al. | May 2007 | A1 |
20070147362 | Beshai | Jun 2007 | A1 |
20070183418 | Riddoch et al. | Aug 2007 | A1 |
20070223470 | Stahl | Sep 2007 | A1 |
20070237083 | Oh et al. | Oct 2007 | A9 |
20080002690 | Ver Steeg et al. | Jan 2008 | A1 |
20080101378 | Krueger | May 2008 | A1 |
20080112413 | Pong | May 2008 | A1 |
20080165797 | Aceves | Jul 2008 | A1 |
20080186981 | Seto et al. | Aug 2008 | A1 |
20080189432 | Abali et al. | Aug 2008 | A1 |
20080267078 | Farinacci et al. | Oct 2008 | A1 |
20080298248 | Roeck et al. | Dec 2008 | A1 |
20090010159 | Brownell et al. | Jan 2009 | A1 |
20090022154 | Kiribe et al. | Jan 2009 | A1 |
20090097496 | Nakamura et al. | Apr 2009 | A1 |
20090103534 | Malledant et al. | Apr 2009 | A1 |
20090119565 | Park et al. | May 2009 | A1 |
20090262741 | Jungck et al. | Oct 2009 | A1 |
20100020796 | Park et al. | Jan 2010 | A1 |
20100039959 | Gilmartin | Feb 2010 | A1 |
20100049942 | Kim et al. | Feb 2010 | A1 |
20100111529 | Zeng et al. | May 2010 | A1 |
20100141428 | Mildenberger et al. | Jun 2010 | A1 |
20100216444 | Mariniello et al. | Aug 2010 | A1 |
20100284404 | Gopinath et al. | Nov 2010 | A1 |
20100290385 | Ankaiah et al. | Nov 2010 | A1 |
20100290458 | Assarpour et al. | Nov 2010 | A1 |
20100315958 | Luo et al. | Dec 2010 | A1 |
20110019673 | Fernandez | Jan 2011 | A1 |
20110080913 | Liu et al. | Apr 2011 | A1 |
20110085440 | Owens et al. | Apr 2011 | A1 |
20110085449 | Jeyachandran et al. | Apr 2011 | A1 |
20110090784 | Gan | Apr 2011 | A1 |
20110164496 | Loh et al. | Jul 2011 | A1 |
20110164518 | Daraiseh et al. | Jul 2011 | A1 |
20110225391 | Burroughs et al. | Sep 2011 | A1 |
20110249679 | Lin et al. | Oct 2011 | A1 |
20110255410 | Yamen et al. | Oct 2011 | A1 |
20110265006 | Morimura et al. | Oct 2011 | A1 |
20110299529 | Olsson et al. | Dec 2011 | A1 |
20120020207 | Corti et al. | Jan 2012 | A1 |
20120075999 | Ko et al. | Mar 2012 | A1 |
20120082057 | Welin et al. | Apr 2012 | A1 |
20120144065 | Parker et al. | Jun 2012 | A1 |
20120147752 | Ashwood-Smith et al. | Jun 2012 | A1 |
20120163797 | Wang | Jun 2012 | A1 |
20120170582 | Abts et al. | Jul 2012 | A1 |
20120207175 | Raman et al. | Aug 2012 | A1 |
20120250500 | Liu | Oct 2012 | A1 |
20120250679 | Judge | Oct 2012 | A1 |
20120287791 | Xi et al. | Nov 2012 | A1 |
20120300669 | Zahavi | Nov 2012 | A1 |
20120314706 | Liss | Dec 2012 | A1 |
20130044636 | Koponen et al. | Feb 2013 | A1 |
20130071116 | Ong | Mar 2013 | A1 |
20130083701 | Tomic et al. | Apr 2013 | A1 |
20130114599 | Arad | May 2013 | A1 |
20130114619 | Wakumoto | May 2013 | A1 |
20130159548 | Vasseur et al. | Jun 2013 | A1 |
20130170451 | Krause et al. | Jul 2013 | A1 |
20130182604 | Moreno et al. | Jul 2013 | A1 |
20130204933 | Cardona et al. | Aug 2013 | A1 |
20130208720 | Ellis et al. | Aug 2013 | A1 |
20130242745 | Umezuki | Sep 2013 | A1 |
20130259033 | Hefty | Oct 2013 | A1 |
20130297757 | Han et al. | Nov 2013 | A1 |
20130315237 | Kagan et al. | Nov 2013 | A1 |
20130322256 | Bader et al. | Dec 2013 | A1 |
20130329727 | Rajagopalan et al. | Dec 2013 | A1 |
20130336116 | Vasseur et al. | Dec 2013 | A1 |
20130336164 | Yang et al. | Dec 2013 | A1 |
20140016457 | Enyedi et al. | Jan 2014 | A1 |
20140022942 | Han et al. | Jan 2014 | A1 |
20140043959 | Owens et al. | Feb 2014 | A1 |
20140059440 | Sasaki et al. | Feb 2014 | A1 |
20140105034 | Sun | Apr 2014 | A1 |
20140140341 | Bataineh et al. | May 2014 | A1 |
20140169173 | Naouri et al. | Jun 2014 | A1 |
20140192646 | Mir et al. | Jul 2014 | A1 |
20140198636 | Thayalan et al. | Jul 2014 | A1 |
20140211808 | Koren et al. | Jul 2014 | A1 |
20140269305 | Nguyen | Sep 2014 | A1 |
20140313880 | Lu et al. | Oct 2014 | A1 |
20140328180 | Kim et al. | Nov 2014 | A1 |
20140343967 | Baker | Nov 2014 | A1 |
20150030033 | Vasseur et al. | Jan 2015 | A1 |
20150052252 | Gilde et al. | Feb 2015 | A1 |
20150092539 | Sivabalan et al. | Apr 2015 | A1 |
20150124815 | Beliveau et al. | May 2015 | A1 |
20150127797 | Attar et al. | May 2015 | A1 |
20150131663 | Brar et al. | May 2015 | A1 |
20150163144 | Koponen et al. | Jun 2015 | A1 |
20150172070 | Csaszar | Jun 2015 | A1 |
20150194215 | Douglas et al. | Jul 2015 | A1 |
20150195204 | Haramaty et al. | Jul 2015 | A1 |
20150249590 | Gusat et al. | Sep 2015 | A1 |
20150295858 | Chrysos et al. | Oct 2015 | A1 |
20150372916 | Haramaty et al. | Dec 2015 | A1 |
20160012004 | Arimilli et al. | Jan 2016 | A1 |
20160014636 | Bahr et al. | Jan 2016 | A1 |
20160028613 | Haramaty | Jan 2016 | A1 |
20160043933 | Gopalarathnam | Feb 2016 | A1 |
20160080120 | Unger et al. | Mar 2016 | A1 |
20160080321 | Pan et al. | Mar 2016 | A1 |
20160182378 | Basavaraja et al. | Jun 2016 | A1 |
20160294715 | Raindel et al. | Oct 2016 | A1 |
20160380893 | Chopra et al. | Dec 2016 | A1 |
20170054445 | Wang | Feb 2017 | A1 |
20170054591 | Hyoudou et al. | Feb 2017 | A1 |
20170068669 | Levy et al. | Mar 2017 | A1 |
20170070474 | Haramaty et al. | Mar 2017 | A1 |
20170180243 | Haramaty et al. | Jun 2017 | A1 |
20170187614 | Haramaty et al. | Jun 2017 | A1 |
20170195758 | Schrans | Jul 2017 | A1 |
20170244630 | Levy et al. | Aug 2017 | A1 |
20170270119 | Kfir et al. | Sep 2017 | A1 |
20170286292 | Levy et al. | Oct 2017 | A1 |
20170331740 | Levy et al. | Nov 2017 | A1 |
20170358111 | Madsen | Dec 2017 | A1 |
20180026878 | Zahavi et al. | Jan 2018 | A1 |
20180062990 | Kumar et al. | Mar 2018 | A1 |
20180089127 | Flajslik et al. | Mar 2018 | A1 |
20180139132 | Edsall et al. | May 2018 | A1 |
20180302288 | Schmatz | Oct 2018 | A1 |
20200042667 | Swaminathan et al. | Feb 2020 | A1 |
20200067822 | Malhotra et al. | Feb 2020 | A1 |
20200136956 | Neshat | Apr 2020 | A1 |
20220014607 | Pilnik et al. | Jan 2022 | A1 |
20220045972 | Aibester et al. | Feb 2022 | A1 |
20220182309 | Bataineh | Jun 2022 | A1 |
Number | Date | Country |
---|---|---|
2012037494 | Mar 2012 | WO |
2016105446 | Jun 2016 | WO |
Entry |
---|
Leiserson, “Fat-Trees: Universal Networks for Hardware Efficient Supercomputing”, IEEE Transactions on Computers, vol. C-34, pp. 892-901, Oct. 1985. |
Oehring et al., “On Generalized Fat Trees”, Proceedings of the 9th International Symposium on Parallel Processing, Santa Barbara, USA, pp. 37-44, Apr. 1995. |
Zahavi, “D-Mod-K Routing Providing Non-Blocking Traffic for Shift Permutations on Real Life Fat Trees”, CCIT Technical Report #776, Technion—Israel Institute of Technology, Haifa, Israel, pp. 1-7, Aug. 2010. |
Yuan et al., “Oblivious Routing for Fat-Tree Based System Area Networks with Uncertain Traffic Demands”, Proceedings of ACM Sigmetrics—the International Conference on Measurement and Modeling of Computer Systems, pp. 337-348, San Diego, USA, pp. 337-348, Jun. 2007. |
Matsuoka, “You Don't Really Need Big Fat Switches Anymore—Almost”, IPSJ SIG Technical Reports, vol. 2003, No. 83, pp. 157-162, year 2003. |
Kim et al., “Technology-Driven, Highly-Scalable Dragonfly Topology”, 35th International Symposium on Computer Architecture, pp. 77-78, Beijing, China, pp. 77-88, Jun. 2008. |
Jiang et al., “Indirect Adaptive Routing on Large Scale Interconnection Networks”, 36th International Symposium on Computer Architecture, Austin, USA, pp. 220-231, Jun. 2009. |
Minkenberg et al., “Adaptive Routing in Data Center Bridges”, Proceedings of 17th IEEE Symposium on High Performance Interconnects, New York, USA, pp. 33-41, Aug. 2009. |
Kim et al., “Adaptive Routing in High-Radix Clos Network”, Proceedings of the 2006 ACM/IEEE Conference on Supercomputing (SC2006), Tampa, USA, pp. 1-11, Nov. 2006. |
Infiniband Trade Association, “InfiniBand™ Architecture Specification vol. 1”, Release 1.2.1, pp. 1-1727, Nov. 2007. |
Culley et al., “Marker PDU Aligned Framing for TCP Specification”, IETF Network Working Group, RFC 5044, pp. 1-74, Oct. 2007. |
Shah et al., “Direct Data Placement over Reliable Transports”, IETF Network Working Group, RFC 5041, pp. 1-38, Oct. 2007. |
Martinez et al., “Supporting fully adaptive routing in Infiniband networks”, Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS'03), pp. 1-10, Apr. 2003. |
Joseph, “Adaptive routing in distributed decentralized systems: NeuroGrid, Gnutella & Freenet”, Proceedings of Workshop on Infrastructure for Agents, MAS and Scalable MAS, Montreal, Canada, pp. 1-11, year 2001. |
Gusat et al., “R3C2: Reactive Route & Rate Control for CEE”, Proceedings of 18th IEEE Symposium on High Performance Interconnects, New York, USA, pp. 50-57, Aug. 2010. |
Wu et al., “DARD: Distributed adaptive routing datacenter networks”, Proceedings of IEEE 32nd International Conference Distributed Computing Systems, pp. 32-41, Jun. 2012. |
Ding et al., “Level-wise scheduling algorithm for fat tree interconnection networks”, Proceedings of the 2006 ACM/IEEE Conference on Supercomputing (SC 2006), pp. 1-9, Nov. 2006. |
Prisacari et al., “Performance implications of remote-only load balancing under adversarial traffic in Dragonflies”, Proceedings of the 8th International Workshop on Interconnection Network Architecture: On-Chip, Multi-Chip, pp. 1-4, Jan. 2014. |
Li et al., “Multicast Replication Using Dual Lookups in Large Packet-Based Switches”, 2006 IET International Conference on Wireless, Mobile and Multimedia Networks, pp. 1-3, Nov. 2006. |
Nichols et al., “Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers”, Network Working Group, RFC 2474, pp. 1-20, Dec. 1998. |
Microsoft., “How IPv4 Multicasting Works”, pp. 1-22, Mar. 28, 2003. |
Suchara et al., “Network Architecture for Joint Failure Recovery and Traffic Engineering”, Proceedings of the ACM Sigmetrics joint international conference on Measurement and modeling of computer systems, pp. 97-108, Jun. 2011. |
IEEE 802.1Q, “IEEE Standard for Local and metropolitan area networks Virtual Bridged Local Area Networks”, IEEE Computer Society, pp. 1-303, May 19, 2006. |
Plummer, D., “An Ethernet Address Resolution Protocol,” Network Working Group, Request for Comments (RFC) 326, pp. 1-10, Nov. 1982. |
Hinden et al., “IP Version 6 Addressing Architecture,” Network Working Group ,Request for Comments (RFC) 2373, pp. 1-26, Jul. 1998. |
Garcia et al., “On-the-Fly 10 Adaptive Routing in High-Radix Hierarchical Networks,” Proceedings of the 2012 International Conference on Parallel Processing (ICPP), pp. 279-288, Sep. 2012. |
Dally et al., “Deadlock-Free Message Routing in Multiprocessor Interconnection Networks”, IEEE Transactions on Computers, vol. C-36, No. 5, pp. 547-553, May 1987. |
Nkposong et al., “Experiences with BGP in Large Scale Data Centers:Teaching an old protocol new tricks”, pp. 1-44, Jan. 31, 2014. |
“Equal-cost multi-path routing”, Wikipedia, pp. 1-2, Oct. 13, 2014. |
Thaler et al., “Multipath Issues in Unicast and Multicast Next-Hop Selection”, Network Working Group, RFC 2991, pp. 1-9, Nov. 2000. |
Glass et al., “The turn model for adaptive routing”, Journal of the ACM, vol. 41, No. 5, pp. 874-902, Sep. 1994. |
Mahalingam et al., “VXLAN: A Framework for Overlaying Virtualized Layer 2 Networks over Layer 3 Networks”, Internet Draft, pp. 1-20, Aug. 22, 2012. |
Sinha et al., “Harnessing TCP's Burstiness with Flowlet Switching”, 3rd ACM SIGCOMM Workshop on Hot Topics in Networks (HotNets), pp. 1-6, Nov. 11, 2004. |
Vishnu et al., “Hot-Spot Avoidance With Multi-Pathing Over InfiniBand: An MPI Perspective”, Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid'07), pp. 1-8, year 2007. |
NOWLAB—Network Based Computing Lab, pp. 1-2, years 2002-2015, as downloaded from http://nowlab.cse.ohio-state.edu/publications/conf-presentations/2007/vishnu-ccgrid07.pdf. |
Alizadeh et al.,“CONGA: Distributed Congestion-Aware Load Balancing for Datacenters”, Cisco Systems, pp. 1-12, Aug. 9, 2014. |
Geoffray et al., “Adaptive Routing Strategies for Modem High Performance Networks”, 16th IEEE Symposium on High Performance Interconnects (HOTI '08), pp. 165-172, Aug. 2008. |
Anderson et al., “On the Stability of Adaptive Routing in the Presence of Congestion Control”, IEEE Infocom, pp. 1-11, year 2003. |
Perry et al., “Fastpass: A Centralized “Zero-Queue” Datacenter Network”, M.I.T. Computer Science & Artificial Intelligence Lab, pp. 1-12, year 2014. |
Afek et al., “Sampling and Large Flow Detection in SDN”, SIGCOMM '15, London, UK, pp. 345-346, Aug. 2015. |
Amante et al., “IPv6 Flow Label Specification”, Request for Comments: 6437, pp. 1-15, Nov. 2011. |
Yallouz et al., U.S. Appl. No. 17/016,464, filed Sep. 10, 2020. |
Shpiner et al., “Dragonfly+: Low Cost Topology for Scaling Datacenters”, IEEE 3rd International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB), pp. 1-9, Feb. 2017. |
Zahavi et al., “Distributed Adaptive Routing for Big-Data Applications Running on Data Center Networks,” Proceedings of the Eighth ACM/IEEE Symposium on Architectures for Networking and Communication Systems, New York, USA, pp. 99-110, Oct. 2012. |
MELLANOX White Paper, “The SHIELD: Self-Healing Interconnect,” pp. 1-2, year 2019. |
Cao et al., “Implementation Method for High-radix Fat-tree Deterministic Source-routing Interconnection Network”, Computer Science, vol. 39, issue 12, pp. 33-37, year 2012. |
U.S. Appl. No. 17/353,869 Office Action dated Jan. 12, 2023. |
U.S. Appl. No. 17/079,543 Office Action dated Mar. 16, 2022. |
EP Application #21204582.7 Search Report dated Mar. 18, 2022. |
U.S. Appl. No. 17/016,464 Office Action dated May 10, 2022. |
Cisco, “Cisco ACI Remote Leaf Architecture—White Paper,” pp. 1-83, updated Jan. 22, 2020. |
Nkposong et al., “Experiences with BGP in Large Scale Data Centers: Teaching an Old Protocol New Tricks”, pp. 1-47, JANOG33 Meeting (Japan Network Operators' Group), Beppu City, Japan, Jan. 23-24, 2014. |
Infiniband Trade Association, “Supplement to Infiniband Architecture Specification,” vol. 1, release 1.2.1—Annex A17: RoCEv2, pp. 1-23, Sep. 2, 2014. |
Infiniband Trade Association, “InfiniBand Architecture Specification,” vol. 1, Release 1.5, Jun. 2, 2021, Draft, Table 6 (Base Transport Header Fields), pp. 1-2, year 2021. |
Thulasiraman et al., “Logical Topology Augmentation for Guaranteed Survivability Under Multiple Failures in IP-over-WDM Optical Network,” 2009 IEEE 3rd International Symposium on Advanced Networks and Telecommunication Systems (ANTS), pp. 1-3, year 2009. |
Nastiti et al., “Link Failure Emulation with Dijkstra and Bellman-Ford Algorithm in Software Defined Network Architecture,” Abstract of Case Study: Telkom University—Topology, 2018 6th IEEE Conference on Information and Communication Technology (ICoICT), pp. 135-140, year 2018. |
Kamiyama et al., “Network Topology Design Considering Detour Traffic Caused by Link Failure,” Networks 2008—The 13th International Telecommunications Network Strategy and Planning Symposium, pp. 1-8, year 2008. |
Levi et al., U.S. Appl. No. 17/079,543, filed Oct. 26, 2020. |
Ronen et al., U.S. Appl. No. 17/353,869, filed Jun. 22, 2021. |
Valadarsky et al., “Xpander: Towards Optimal-Performance Datacenters,” Proceedings of CoNEXT '16, pp. 205-219, Dec. 2016. |
Bilu et al., “Lifts, Discrepancy and Nearly Optimal Spectral Gap*,” Combinatorica, vol. 26, No. 5, Bolyai Society—Springer-Verlag, pp. 495-519, year 2006. |
Number | Date | Country | |
---|---|---|---|
20230171206 A1 | Jun 2023 | US |