Sha, Edwin Hsing-Mean‏

Permanent URI for this collectionhttps://hdl.handle.net/10735.1/4145

Edwin Shaw is a Professor in the Department of Computer Science. He is an affiliate faculty member of the Cyber Security Research and Education Institute. His research interests include:

  • Embedded Software and Systems
  • Computer and Network Security
  • Parallel Architectures and Systems
  • High-performance and Low-Power Real-Time Systems
  • Network Architectures
  • Compilers
  • Application Specific VLSI Design
  • Operating Systems
  • High-Level Synthesis.

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Recent Submissions

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    Optimizing Data Distribution for Loops on Embedded Multicore with Scratch-Pad Memory
    (Academy Publisher) Gao, Q.; Zhuge, Q.; Zhang, J.; Zhu, G.; Sha, Edwin Hsing-Mean; 0000 0000 3259 5943 (Sha, EHM); 2003002797‏ (Sha, EHM)
    Software-controlled Scratch-Pad Memory (SPM) is a desirable candidate for on-chip memory units in embedded multi-core systems due to its advantages of small die area and low power consumption. In particular, data placement on SPMs can be explicitly controlled by software. Therefore, the technique of data distribution on SPMs for multi-core system becomes critical in exploiting the advantages of SPM. Previous research efforts on data allocation did not consider the placement of array data accessed in loops. Loops are the most time-consuming and energy-consuming part for most of the computationintensive applications. In this paper, we propose a highperformance, low-overhead data distribution technique, the Iterational Optimal Loop Data Distribution Algorithm based on dynamic programming. It optimizes data allocation of both scalar and array data for embedded multi-core systems with SPMs. The experimental results show that the IOLDD algorithm reduces the energy consumption by 30.12% and 14.52% on average compared with random data distribution and greedy stretagy, respectively. It also reduces the memory access time by 18.45% and 18.38% on average compared with the random distribution strategy and the greedy strategy, respectively.

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