SCHEDULE: NOV 10-16, 2012

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Design of a Scalable InfiniBand Topology Service to Enable Network-Topology-Aware Placement of Processes

SESSION: Networks

EVENT TYPE: Papers, Best Paper Finalists, Best Student Paper Finalists

TIME: 4:30PM - 5:00PM

SESSION CHAIR: Sadaf R. Alam

AUTHOR(S):Hari Subramoni, Sreeram Potluri, Krishna Kandalla, Bill Barth, Jerome Vienne, Jeff Keasler, Karen Tomko, Karl Schulz, Adam Moody, Dhabaleswar Panda

ROOM:255-BC

ABSTRACT:
Over the last decade, InfiniBand has become an increasingly popular interconnect for deploying modern supercomputing systems. However, there exists no detection service that can discover the underlying network topology in a scalable manner and expose this information to runtime libraries and users of the high performance computing systems in a convenient way. In this paper, we design a novel and scalable method to detect the InfiniBand network topology by using Neighbor- Joining techniques (NJ). To the best of our knowledge, this is the first instance where the neighbor joining algorithm has been applied to solve the problem of detecting InfiniBand network topology. We also design a network-topology-aware MPI library that takes advantage of the network topology service. The library places processes taking part in the MPI job in a network-topology-aware manner with the dual aim of increasing intra-node communication and reducing the long distance inter-node communication across the InfiniBand fabric.

Chair/Author Details:

Sadaf R. Alam (Chair) - Swiss National Supercomputing Centre

Hari Subramoni - Ohio State University

Sreeram Potluri - Ohio State University

Krishna Kandalla - Ohio State University

Bill Barth - University of Texas at Austin

Jerome Vienne - Ohio State University

Jeff Keasler - Lawrence Livermore National Laboratory

Karen Tomko - Ohio Supercomputer Center

Karl Schulz - University of Texas at Austin

Adam Moody - Lawrence Livermore National Laboratory

Dhabaleswar Panda - Ohio State University

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Design of a Scalable InfiniBand Topology Service to Enable Network-Topology-Aware Placement of Processes

SESSION: Networks

EVENT TYPE: , Best Paper Finalists, Best Student Paper Finalists

TIME: 4:30PM - 5:00PM

SESSION CHAIR: Sadaf R. Alam

AUTHOR(S):Hari Subramoni, Sreeram Potluri, Krishna Kandalla, Bill Barth, Jerome Vienne, Jeff Keasler, Karen Tomko, Karl Schulz, Adam Moody, Dhabaleswar Panda

ROOM:255-BC

ABSTRACT:
Over the last decade, InfiniBand has become an increasingly popular interconnect for deploying modern supercomputing systems. However, there exists no detection service that can discover the underlying network topology in a scalable manner and expose this information to runtime libraries and users of the high performance computing systems in a convenient way. In this paper, we design a novel and scalable method to detect the InfiniBand network topology by using Neighbor- Joining techniques (NJ). To the best of our knowledge, this is the first instance where the neighbor joining algorithm has been applied to solve the problem of detecting InfiniBand network topology. We also design a network-topology-aware MPI library that takes advantage of the network topology service. The library places processes taking part in the MPI job in a network-topology-aware manner with the dual aim of increasing intra-node communication and reducing the long distance inter-node communication across the InfiniBand fabric.

Chair/Author Details:

Sadaf R. Alam (Chair) - Swiss National Supercomputing Centre

Hari Subramoni - Ohio State University

Sreeram Potluri - Ohio State University

Krishna Kandalla - Ohio State University

Bill Barth - University of Texas at Austin

Jerome Vienne - Ohio State University

Jeff Keasler - Lawrence Livermore National Laboratory

Karen Tomko - Ohio Supercomputer Center

Karl Schulz - University of Texas at Austin

Adam Moody - Lawrence Livermore National Laboratory

Dhabaleswar Panda - Ohio State University

  Click here to download .ics calendar file

  Click here to download .vcs calendar file

  Click here to add event to your Google Calendar