Novo-G#: a multidimensional torus-based reconfigurable cluster for molecular dynamics
Summary Molecular dynamics (MD) is a large‐scale, communication‐intensive problem that has been the subject of high‐performance computing research and acceleration for years. Not surprisingly, the most success in accelerating MD comes from specialized systems such as the Anton machine. In this paper...
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Published in | Concurrency and computation Vol. 28; no. 8; pp. 2374 - 2393 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Blackwell Publishing Ltd
10.06.2016
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Subjects | |
Online Access | Get full text |
ISSN | 1532-0626 1532-0634 |
DOI | 10.1002/cpe.3565 |
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Summary: | Summary
Molecular dynamics (MD) is a large‐scale, communication‐intensive problem that has been the subject of high‐performance computing research and acceleration for years. Not surprisingly, the most success in accelerating MD comes from specialized systems such as the Anton machine. In this paper, we describe Novo‐G# (novo‐jee‐sharp), a multi‐node reconfigurable system designed for the acceleration of communication‐intensive scientific problems in general, and MD in particular. This system provides a high‐bandwidth, low‐latency 3D torus network to allow direct communication between kernels running on multiple field‐programmable gate arrays. We also present a performance model for Novo‐G# running the 3D Fast Fourier Transform (FFT) kernel that forms the core of MD simulations. We validate the model against published Anton performance data and through initial hardware experiments on Novo‐G#. Finally, through simulation studies, we show that this system at scale performs better than specialized systems like Anton and outperforms established CPU‐based clusters like Blue Gene/Q by an order of magnitude for the 3D FFT kernel, with greater flexibility and lower costs. Copyright © 2015 John Wiley & Sons, Ltd. |
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Bibliography: | istex:E501D220BEB1D43BDDD08918940DF577A207E228 ark:/67375/WNG-9CZWZ493-V Extension of Conference Paper: An earlier version of this work featured a conceptual design of the Novo-G# network and a performance model based on Anton . Since that publication, an initial deployment of 32 nodes of Novo-G# has been completed. In this paper, we present the architecture of the deployed system and the design of a three-layer network stack to support the 3D torus network. We also describe the hardware architecture of the 3D fast Fourier transform kernel on eight nodes. Data from this implementation are used to improve the specificity of the performance model presented earlier. In conjunction with other optimizations to the model, we can now present simulation runs and predictions up to 8 × 8×8 system size, the size of the largest Anton machine. ArticleID:CPE3565 Extension of Conference Paper: An earlier version of this work featured a conceptual design of the Novo‐G# network and a performance model based on Anton Since that publication, an initial deployment of 32 nodes of Novo‐G# has been completed. In this paper, we present the architecture of the deployed system and the design of a three‐layer network stack to support the 3D torus network. We also describe the hardware architecture of the 3D fast Fourier transform kernel on eight nodes. Data from this implementation are used to improve the specificity of the performance model presented earlier. In conjunction with other optimizations to the model, we can now present simulation runs and predictions up to 8 × 8×8 system size, the size of the largest Anton machine. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1532-0626 1532-0634 |
DOI: | 10.1002/cpe.3565 |