Automated GPU support in LuNA fragmented programming system

Belyaev Nikolay, Vladislav Perepelkin

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

The paper is devoted to the problem of reduction of complexity of development of numerical parallel programs for distributed memory computers with hybrid (CPU+GPU) computing nodes. The basic idea is to employ a high-level representation of an application algorithm to allow its automated execution on multicomputers with hybrid nodes without a programmer having to do low-level programming. LuNA is a programming system for numerical algorithms, which implements the idea, but only for CPU. In the paper we propose a LuNA language extension, as well as necessary run-time algorithms to support GPU utilization. For that a user only has to provide a limited number of computational GPU procedures using CUDA, while the system will take care of such associated low-level problems, as jobs scheduling, CPU-GPU data transfer, network communications and others. The algorithms developed and implemented take advantage of concerning informational dependencies of an application and support automated tuning to available hardware configuration and application input data.

Original languageEnglish
Title of host publicationParallel Computing Technologies - 14th International Conference, PaCT 2017, Proceedings
Editors Malyshkin
PublisherSpringer-Verlag GmbH and Co. KG
Pages272-277
Number of pages6
Volume10421 LNCS
ISBN (Print)9783319629315
DOIs
Publication statusPublished - 1 Jan 2017
Event14th International Conference on Parallel Computing Technologies, PaCT 2017 - Nizhny Novgorod, Russian Federation
Duration: 4 Sep 20178 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10421 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Parallel Computing Technologies, PaCT 2017
CountryRussian Federation
CityNizhny Novgorod
Period04.09.201708.09.2017

Keywords

  • Fragmented programming
  • GPGPU
  • Hybrid multicomputers
  • LuNA system
  • Parallel programming automation

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