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  1. Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model (PGAS '10)
  2. Hybrid PGAS runtime support for multicore nodes
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Predicting remote reuse distance patterns in UPC applications
Introducing OpenSHMEM: SHMEM for the PGAS community
Hybrid PGAS runtime support for multicore nodes
Asynchronous PGAS runtime for Myrinet networks
Unifying UPC and MPI runtimes: experience with MVAPICH
Introducing mNUMA: an extended PGAS architecture
Performance modeling for multilevel communication in SHMEM+
Improving UPC productivity via integrated development tools
X10-enabled MapReduce
Development and performance analysis of a UPC Particle-in-Cell code
XcalableMP implementation and performance of NAS Parallel Benchmarks
Extensible PGAS semantics for C++
An open-source compiler and runtime implementation for Coarray Fortran
Hiding latency in Coarray Fortran 2.0
Numerical Python for scalable architectures

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Hybrid PGAS runtime support for multicore nodes

Content Provider ACM Digital Library
Author Hargrove, Paul Iancu, Costin Blagojević, Filip Yelick, Katherine
Abstract With multicore processors as the standard building block for high performance systems, parallel runtime systems need to provide excellent performance on shared memory, distributed memory, and hybrids. Conventional wisdom suggests that threads should be used as the runtime mechanism within shared memory, and two runtime versions for shared and distributed memory are often designed and implemented separately, retrofitting after the fact for hybrid systems. In this paper we consider the problem of implementing a runtime layer for Partitioned Global Address Space (PGAS) languages, which offer a uniform programming abstraction for hybrid machines. We present a new process-based shared memory runtime and compare it to our previous pthreads implementation. Both are integrated with the GASNet communication layer, and they can co-exist with one another. We evaluate the shared memory runtime approaches, showing that they interact in important and sometimes surprising ways with the communication layer. Using a set of microbenchmarks and application level benchmarks on an IBM BG/P, Cray XT, and InfiniBand cluster, we show that threads, processes and combinations of both are needed for maximum performance. Our new runtime shows speedups of over 60% for application benchmarks and 100% for collective communication benchmarks, when compared to the previous implementation. Our work primarily targets PGAS languages, but some of the lessons are relevant to other parallel runtime systems and libraries.
Starting Page 1
Ending Page 10
Page Count 10
File Format PDF
ISBN 9781450304610
DOI 10.1145/2020373.2020376
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-10-12
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Multi-core Upc Pgas Shared memory
Content Type Text
Resource Type Article
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