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  1. Proceedings of the 9th workshop on MEmory performance (MEDEA '08)
  2. Evaluation of memory performance on the cell BE with the SARC programming model
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PFetch: software prefetching exploiting temporal predictability of memory access streams
Modeling of cache access behavior based on Zipf's law
Zero loads: canceling load requests by tracking zero values
A shared cache for a chip multi vector processor
A leakage-aware cache sharing technique for low-power chip multi-processors (CMPs) with private L2 caches
Predictable dynamic instruction scratchpad for simultaneous multithreaded processors
Exploiting multithreaded architectures to improve the hash join operation
Accurate system-level performance modeling and workload characterization for mobile internet devices
WormBench: a configurable workload for evaluating transactional memory systems
Version management alternatives for hardware transactional memory
Evaluation of memory performance on the cell BE with the SARC programming model

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Evaluation of memory performance on the cell BE with the SARC programming model

Content Provider ACM Digital Library
Author González, Marc Martorell, Xavier Ayguadé, Eduard Silla, Federico Ferrer, Roger
Abstract With the advent of multicore architectures, especially with the heterogeneous ones, both computational and memory top performance are difficult to obtain using traditional programming models. Usually, programmers have to fully reorganize the code and data of their applications in order to maximize resource usage, and work with the low-level interfaces offered by the vendor-provided SDKs, to obtain high computational and memory performances. In this paper, we present the evaluation of the SARC programming model on the Cell BE architecture, with respect to memory performance. We show how we have annotated the HPL STREAM and RandomAccess applications, and the memory bandwidth obtained. Results indicate that the programming model provides good productivity and competitive performance on this kind of architectures.
Starting Page 77
Ending Page 84
Page Count 8
File Format PDF
ISBN 9781605582436
DOI 10.1145/1509084.1509095
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2008-10-26
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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