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Guest Editor's Introduction: Special Section on Challenges and Solutions in Multicore and Many‐Core Computing
Author(s) -
Zhou Shujia,
Qiu Judy,
Hawick Kenneth
Publication year - 2012
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1861
Subject(s) - multi core processor , computer science , ibm , parallel computing , cloud computing , graphics , parallelism (grammar) , computer architecture , operating system , materials science , nanotechnology
It is our honor to serve as guest editors of this special section of the journal of Concurrency and Computation: Practice and Experience on Frontiers of GPU, Multiand Many-Core Systems (FGMMS). We are pleased to present nine high-quality contributions in this special issue, where they were first presented at the Frontiers of GPU, Multiand Many-Core Systems Workshop in conjunction with the 10 IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2010), held from May 17 to 20, 2010, in Melbourne, Victoria, Australia. The invited papers in this special issue represent augmented works drafted at the beginning of 2010 that addressed the issues below. Multicore and many-core microprocessors are being deployed in a broad spectrum of applications including clusters, clouds, and grids. Both conventional multicore and many-core processors, such as Intel Nehalem and IBM Power7 processors, and unconventional many-core processors, such as NVIDIA Tesla and AMD FireStream graphics processing units (GPUs), hold the promise of increasing performance through parallelism. However, GPU approaches in parallelism are distinctly different from those of conventional multicore and many-core processors, which raises new challenges. For example, how do we optimize applications for conventional multicore and many-core processors? How do we re-engineer applications to take advantage of GPUs’ tremendous computing power in a reasonable cost–benefit ratio? What are effective ways of using GPUs as accelerators? Enormous and rapid progress has been made in accelerator computing over the last two years, but nevertheless we believe the themes developed for the FGMMS workshop and that are represented here in this special issue are still very important ones. In the last two years we have seen the continued rise of GPU computing and indeed its uptake as multi-GPU systems now dominates the top 10 entries within the Top 500 supercomputing systems list [1]. Although there has been something of a shakeout of the accelerator technologies that were prevalent three years ago, we have also seen the continued and steady rise of uptake of multicore conventional CPU devices, and an exciting future with combined multicore CPU and GPU devices seems likely. As the articles in this special issue suggest, there are still challenges ahead for application developers to make best use of these future and hybrid highly concurrent systems. There are however still many really important applications that will continue to drive interest, investment, and development of these technologies.