Kim H. McMahon’s scientific contributions

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Publications (2)


Fig. 6: Bisection and MPI_Alltoall bandwidth on all the 1 024 nodes of SHANDY, for different processes per node (PPN) and message sizes. The x-axis is in logarithmic scale.
Fig. 7: Different victim/aggressor allocations.
Fig. 8: Time distribution of Tailbench applications, with and without endpoint congestion. The labels on the top of each plot denote the 99th and 95th percentile.
An In-Depth Analysis of the Slingshot Interconnect
  • Conference Paper
  • Full-text available

November 2020

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626 Reads

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122 Citations

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Kim H. McMahon

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Fig. 6: Bisection and MPI_Alltoall bandwidth on all the 1 024 nodes of SHANDY, for different processes per node (PPN) and message sizes. The x-axis is in logarithmic scale.
Fig. 7: Different victim/aggressor allocations.
Fig. 8: Time distribution of Tailbench applications, with and without endpoint congestion. The labels on the top of each plot denote the 99th and 95th percentile.
An In-Depth Analysis of the Slingshot Interconnect

August 2020

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588 Reads

The interconnect is one of the most critical components in large scale computing systems, and its impact on the performance of applications is going to increase with the system size. In this paper, we will describe Slingshot, an interconnection network for large scale computing systems. Slingshot is based on high-radix switches, which allow building exascale and hyperscale datacenters networks with at most three switch-to-switch hops. Moreover, Slingshot provides efficient adaptive routing and congestion control algorithms, and highly tunable traffic classes. Slingshot uses an optimized Ethernet protocol, which allows it to be interoperable with standard Ethernet devices while providing high performance to HPC applications. We analyze the extent to which Slingshot provides these features, evaluating it on microbenchmarks and on several applications from the datacenter and AI worlds, as well as on HPC applications. We find that applications running on Slingshot are less affected by congestion compared to previous generation networks.

Citations (1)


... These are the candidates, and the algorithm compares against the deterministic output port which one of these has the lowest congestion, based on the buffer occupancy, and selects that port to route the traffic. HPE Slingshot routes packets dynamically according to load [38]. The congestion is estimated by considering the total depth of the request queues of each output port. ...

Reference:

Congestion Management in High-Performance Interconnection Networks Using Adaptive Routing Notifications
An In-Depth Analysis of the Slingshot Interconnect