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  1. Transactions on Parallel Computing (TOPC)
  2. ACM Transactions on Parallel Computing (TOPC) : Volume 2
  3. Issue 4(Special Issue on PPOPP 2014), March 2016
  4. X10 and APGAS at Petascale
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ACM Transactions on Parallel Computing (TOPC) : Volume 3
ACM Transactions on Parallel Computing (TOPC) : Volume 2
Issue 4(Special Issue on PPOPP 2014), March 2016
Introduction to the Special Issue on PPoPP’14
Well-Structured Futures and Cache Locality
Concurrency Testing Using Controlled Schedulers: An Empirical Study
Leveraging Hardware Message Passing for Efficient Thread Synchronization
X10 and APGAS at Petascale
Low-Rank Methods for Parallelizing Dynamic Programming Algorithms
On Folded-Clos Networks with Deterministic Single-Path Routing
MASA: A Multiplatform Architecture for Sequence Aligners with Block Pruning
Issue 3(Special Issue for SPAA 2013), October 2015
Issue 2, July 2015
Issue 1(Special Issue on SPAA 2012), May 2015
ACM Transactions on Parallel Computing (TOPC) : Volume 1

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X10 and APGAS at Petascale

Content Provider ACM Digital Library
Author Saraswat, Vijay Grove, David Kambadur, Prabhanjan Shinnar, Avraham Zhang, Wei Tardieu, Olivier Herta, Benjamin Takeuchi, Mikio Vaziri, Mandana Cunningham, David
Copyright Year 2016
Abstract X10 is a high-performance, high-productivity programming language aimed at large-scale distributed and shared-memory parallel applications. It is based on the Asynchronous Partitioned Global Address Space (APGAS) programming model, supporting the same fine-grained concurrency mechanisms within and across shared-memory nodes. We demonstrate that X10 delivers solid performance at petascale by running (weak scaling) eight application kernels on an IBM Power--775 supercomputer utilizing up to 55,680 Power7 cores (for 1.7Pflop/s of theoretical peak performance). For the four HPC Class 2 Challenge benchmarks, X10 achieves 41% to 87% of the system’s potential at scale (as measured by IBM’s HPCC Class 1 optimized runs). We also implement K-Means, Smith-Waterman, Betweenness Centrality, and Unbalanced Tree Search (UTS) for geometric trees. Our UTS implementation is the first to scale to petaflop systems. We describe the advances in distributed termination detection, distributed load balancing, and use of high-performance interconnects that enable X10 to scale out to tens of thousands of cores. We discuss how this work is driving the evolution of the X10 language, core class libraries, and runtime systems.
Starting Page 1
Ending Page 32
Page Count 32
File Format PDF
ISSN 23294949
e-ISSN 23294957
DOI 10.1145/2894746
Volume Number 2
Issue Number 4
Journal ACM Transactions on Parallel Computing (TOPC)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-03-15
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword APGAS X10 Performance Scalability
Content Type Text
Resource Type Article
Subject Hardware and Architecture Modeling and Simulation Computer Science Applications Software Computational Theory and Mathematics
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