Fine-grain parallelism using multi-core, Cell/BE, and GPU Systems

被引：17
作者：
不详
机构：
[1] SiPS, INESC-ID/IST, Universidade Técnica de Lisboa, 1000-029 Lisbon
[2] CASPER, Department of Computer Science, University of Cyprus, CY 1678 Nicosia
[3] Exelixis Lab, Scientific Computing Group, Heidelberg Institute for Theoretical Studies, D-69118 Heidelberg
[4] National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801
来源：
PARALLEL COMPUTING | 2012年 / 38卷 / 08期
关键词：
Multi-core processors; Multi-core acelerators; Performance evaluation; Fine-grain parallelism; Scientific workloads; Database workloads; DNA-SEQUENCES; GRAPHICS; PERFORMANCE; INFERENCE; DYNAMICS;
D O I：
10.1016/j.parco.2011.08.002
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Currently, we are facing a situation where applications exhibit increasing computational demands and where a large variety of parallel processor systems are available. In this paper we focus on exploiting fine-grain parallelism for three applications with distinct characteristics: a Bioinformatics application (MrBayes), a Molecular Dynamics application (NAMD), and a database application (TPC-H). We assess, side-by-side, the performance of the three applications on general-purpose multi-core processors, the Cell Broadband Engine (Cell/BE), and Graphics Processing Units (GPU). Our results indicate that application performance depends on the characteristics of the parallel architectures and on the computational requirements of the core functions of the respective applications. For MrBayes the best overall performance is achieved on general-purpose multi-core processors, for NAMD on the Cell/BE, and for TPC-H on GPUs. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：365 / 390
页数：26
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