Multicore Processors and Systems by Michael B. Taylor, Walter Lee, Jason E. Miller (auth.),

By Michael B. Taylor, Walter Lee, Jason E. Miller (auth.), Stephen W. Keckler, Kunle Olukotun, H. Peter Hofstee (eds.)

Multicore Processors and Systems presents a complete assessment of rising multicore processors and structures. It covers know-how tendencies affecting multicores, multicore structure ideas, multicore software program concepts, and case experiences of cutting-edge advertisement multicore structures. Cross-cutting topics of the booklet are the demanding situations linked to scaling up multicore structures to hundreds and hundreds of cores. The structure chapters concentrate on leading edge multicore execution versions in addition to infrastructure for multicores, together with reminiscence structures, on-chip interconnections, and programming types. The case reports learn multicore implementations throughout diverse program domain names, together with basic goal, server, media/broadband, and sign processing. The authors of the chapters contain leaders within the learn of multicore architectures in addition to designers liable for the implementation of industrial multicore systems.

Researchers and practitioners will enjoy the projection of expertise traits and its anticipated influence on multicore process layout. The case stories during the ebook serve to supply perception into assorted techniques of designing multicore platforms that might supply the reader advantage of first-hand event from the unique innovators. due to its emphasis on either basics and on case experiences, this ebook can function a prime textbook for a complicated direction in parallel and multicore approach design.

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1 12 17 29 On these two applications, Raw is able to excel by exploiting fine-grain pipeline parallelism. To do this, the computations were spatially mapped across multiple tiles. Both applications benefited by more than 2× from Raw’s specialized bitlevel manipulation instructions, which reduce the latency of critical feedback loops. Another factor in Raw’s high performance on these applications is Raw’s exposed streaming I/O. This I/O model is in sharp contrast to having to move data through the cache hierarchy on a P3.

Stream Algorithms and Architecture. Technical Memo MIT-LCS-TM-636, MIT Laboratory for Computer Science, 2003. 18. H. P. Hofstee. Power efficient processor architecture and the Cell processor. In HPCA ’05: Proceedings of the 11th International Symposium on High Performance Computer Architecture, pages 258–262, 2005. 19. U. Kapasi, W. J. Dally, S. Rixner, J. D. Owens, and B. Khailany. The Imagine Stream Processor. In ICCD ’02: Proceedings of the 2002 IEEE International Conference on Computer Design, pages 282–288, 2002.

Thus far, our analysis of Raw’s flexibility has been qualitative. Given the recent interest in flexible, versatile, or polymorphic architectures such as Scale [23], Grid [33], and SmartMemories [27], which attempt to perform well over a wider range of applications than extant general-purpose processors, it is intriguing to search for a metric that can capture the notion of versatility. We would like to offer up a candidate and use it to evaluate the versatility of Raw quantitatively. 4 For the application set graphed in Fig.

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