A Kernel Testbed for Parallel Architecture, Language, and Performance Research

Strohmaier, Erich; Williams, Samuel; Kaiser, Alex; Madduri, Kamesh; Ibrahim, Khaled Z.; Bailey, David H.; Demmel, James; Simos, Theodore E.; Psihoyios, George; Tsitouras, Ch.

doi:10.1063/1.3497950

Cited by 2 publications

(2 citation statements)

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“…A shorter version of this document without any details about specific kernels was previously published in [72]. An extended abstract of this paper was subsequently published in [97] by invitation.…”

Section: Previous Workmentioning

confidence: 99%

TORCH Computational Reference Kernels - A Testbed for Computer Science Research

Kaiser¹,

Williams²,

Madduri³

et al. 2010

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For decades, computer scientists have sought guidance on how to evolve architectures, languages, and programming models in order to improve application performance, efficiency, and productivity. Unfortunately, without overarching advice about future directions in these areas, individual guidance is inferred from the existing software/hardware ecosystem, and each discipline often conducts their research independently assuming all other technologies remain fixed. In today's rapidly evolving world of on-chip parallelism, isolated and iterative improvements to performance may miss superior solutions in the same way gradient descent optimization techniques may get stuck in local minima. To combat this, we present TORCH: A Testbed for Optimization ResearCH. These computational reference kernels define the core problems of interest in scientific computing without mandating a specific language, algorithm, programming model, or implementation. To compliment the kernel (problem) definitions, we provide a set of algorithmically-expressed verification tests that can be used to verify a hardware/software co-designed solution produces an acceptable answer. Finally, to provide some illumination as to how researchers have implemented solutions to these problems in the past, we provide a set of reference implementations in C and MATLAB.

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Section: Previous Workmentioning

confidence: 99%

TORCH Computational Reference Kernels - A Testbed for Computer Science Research

Kaiser¹,

Williams²,

Madduri³

et al. 2010

Self Cite

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show abstract

“…Sandia National Laboratories runs the Mantevo project aimed at studying mini-applications, which represent computational kernels for various scientific and engineering applications [6,7]. A similar approach is used by the TORCH project [8][9][10].…”

Section: Background and Related Workmentioning

confidence: 99%

AlgoWiki: an Open Encyclopedia of Parallel Algorithmic Features

Voevodin

Antonov

Dongarra³

2015

JSFI

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The main goal of this project is to formalize the mapping of algorithms onto the architecture of parallel computing systems. The basic idea is that features of algorithms are independent of any computing system. A detailed description of a given algorithm with a special emphasis on its parallel properties is made once, and after that it can be used repeatedly for various implementations of the algorithm on different computing platforms. Machine-dependent, part of this work is devoted to describing features of algorithms implementation for different parallel architectures. The proposed description of algorithms includes many non-trivial features such as: parallel algorithm complexity, resource of parallelism and its properties, features of the informational graph, computational cost of algorithms, data locality analysis as well as analysis of scalability potential, and many others. Descriptions of algorithms form the basis of AlgoWiki, which allows for collaboration with the computing community in order to produce different implementations and achieve improvement. Project website: http://algowiki-project.org/en/.

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A Kernel Testbed for Parallel Architecture, Language, and Performance Research

Cited by 2 publications

References 2 publications

TORCH Computational Reference Kernels - A Testbed for Computer Science Research

TORCH Computational Reference Kernels - A Testbed for Computer Science Research

AlgoWiki: an Open Encyclopedia of Parallel Algorithmic Features

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