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  1. Proceedings of the 9th workshop on MEmory performance (MEDEA '08)
  2. Predictable dynamic instruction scratchpad for simultaneous multithreaded processors
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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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Emulating Unimplemented Instructions in a Simultaneous Multithreaded Processor

Predictable dynamic instruction scratchpad for simultaneous multithreaded processors

Content Provider ACM Digital Library
Author Uhrig, Sascha Mische, Jörg Ungerer, Theo Metzlaff, Stefan
Abstract For precise timing analysis of hard-real applications a predictable memory system is of particular importance. Caches have a great impact on performance, but at the cost of reduced timing predictability. Conventional scratchpads, i.e. statically managed on-chip memories, provide predictable memory accesses, but they are usually badly utilized. Better memory utilization is allowed by dynamically managed scratchpads that are designed for predictability. In this paper we propose a function scratchpad that is dynamically managed in hardware and provides a predictable timing behavior. The function scratchpad exploits a simultaneous multithreaded architecture to increase the pipeline and memory bandwidth utilization while preserving predictability.
Starting Page 38
Ending Page 45
Page Count 8
File Format PDF
ISBN 9781605582436
DOI 10.1145/1509084.1509090
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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