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An Energy Reduction Scheduling Mechanism for a High-Performance SoC Architecture

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Embedded and Ubiquitous Computing – EUC 2005 (EUC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3824))

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Abstract

Continuous improvements in semiconductor technology are supporting new classes of System-on-a-Chip (SoC) architectures that combine extensive processing logic with high-density memory. Such architectures are generally called Processor-in-Memory (PIM) or Intelligent Memory (I-RAM) and can support high-performance computing by reducing the performance gap between the processor and the memory. The PIM architecture combines various processors in a single chip. These processors are characterized by their computation, memory-access and power consumption capabilities. Therefore, a novel parallelizing system, SAGE II, has been developed to identify their capabilities and dispatch the most appropriate jobs to them in order to exploit the advantages of PIM architectures. However, the SAGE II system only can deal with performance issues but power consumption is gradually becoming an important issue of current computing systems. This paper provides a new low-power transformation mechanism, called Energy-Oriented Power Reduction Scheduling (EOPRS), to extend the capability of SAGE II system. It can reduce the power consumption for the Processor-in-Memory system without losing execution performance. The detailed EOPRS transformation technique is presented later. The experimental results of several benchmarks are also discussed.

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© 2005 Springer-Verlag Berlin Heidelberg

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Chu, SL. (2005). An Energy Reduction Scheduling Mechanism for a High-Performance SoC Architecture. In: Yang, L.T., Amamiya, M., Liu, Z., Guo, M., Rammig, F.J. (eds) Embedded and Ubiquitous Computing – EUC 2005. EUC 2005. Lecture Notes in Computer Science, vol 3824. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596356_30

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  • DOI: https://doi.org/10.1007/11596356_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30807-2

  • Online ISBN: 978-3-540-32295-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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