LDRD final report : managing shared memory data distribution in hybrid HPC applications.

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MPI is the dominant programming model for distributed memory parallel computers, and is often used as the intra-node programming model on multi-core compute nodes. However, application developers are increasingly turning to hybrid models that use threading within a node and MPI between nodes. In contrast to MPI, most current threaded models do not require application developers to deal explicitly with data locality. With increasing core counts and deeper NUMA hierarchies seen in the upcoming LANL/SNL 'Cielo' capability supercomputer, data distribution poses an upper boundary on intra-node scalability within threaded applications. Data locality therefore has to be identified at runtime using ... continued below

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30 p.

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Merritt, Alexander M. (Georgia Institute of Technology, Atlanta, GA) & Pedretti, Kevin Thomas Tauke September 1, 2010.

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Description

MPI is the dominant programming model for distributed memory parallel computers, and is often used as the intra-node programming model on multi-core compute nodes. However, application developers are increasingly turning to hybrid models that use threading within a node and MPI between nodes. In contrast to MPI, most current threaded models do not require application developers to deal explicitly with data locality. With increasing core counts and deeper NUMA hierarchies seen in the upcoming LANL/SNL 'Cielo' capability supercomputer, data distribution poses an upper boundary on intra-node scalability within threaded applications. Data locality therefore has to be identified at runtime using static memory allocation policies such as first-touch or next-touch, or specified by the application user at launch time. We evaluate several existing techniques for managing data distribution using micro-benchmarks on an AMD 'Magny-Cours' system with 24 cores among 4 NUMA domains and argue for the adoption of a dynamic runtime system implemented at the kernel level, employing a novel page table replication scheme to gather per-NUMA domain memory access traces.

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30 p.

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  • Report No.: SAND2010-6262
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/1007320 | External Link
  • Office of Scientific & Technical Information Report Number: 1007320
  • Archival Resource Key: ark:/67531/metadc843636

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  • September 1, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

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  • Dec. 5, 2016, 10:57 p.m.

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Merritt, Alexander M. (Georgia Institute of Technology, Atlanta, GA) & Pedretti, Kevin Thomas Tauke. LDRD final report : managing shared memory data distribution in hybrid HPC applications., report, September 1, 2010; United States. (digital.library.unt.edu/ark:/67531/metadc843636/: accessed December 12, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.