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Jie Tang, Pollawat Thanarungroj, Chen Liu, Shao-Shan Liu, Zhi-Min Gu, Jean-Luc Gaudiot. Pinned OS/Services: A Case Study of XML Parsing on Intel SCC[J]. Journal of Computer Science and Technology, 2013, 28(1): 3-13. DOI: 10.1007/s11390-013-1308-6
Citation: Jie Tang, Pollawat Thanarungroj, Chen Liu, Shao-Shan Liu, Zhi-Min Gu, Jean-Luc Gaudiot. Pinned OS/Services: A Case Study of XML Parsing on Intel SCC[J]. Journal of Computer Science and Technology, 2013, 28(1): 3-13. DOI: 10.1007/s11390-013-1308-6

Pinned OS/Services: A Case Study of XML Parsing on Intel SCC

Funds: This work is supported by the National Science Foundation of USA under Grant Nos. CCF-1065147, ECCS-1125762, the Scholarship Council of China, as well as the Beijing Institute of Technology Yu-Miao Ph.D. Scholarship of China. Any opinions, findings, and conclusions as well as recommendations expressed in this material are those of the authors and do not necessarily reflect the views neither of the National Science Foundation of USA nor of the Scholarship Council of China.
More Information
  • Received Date: December 30, 2011
  • Revised Date: May 09, 2012
  • Published Date: January 04, 2013
  • Nowadays, we are heading towards integrating hundreds to thousands of cores on a single chip. However, traditional system software and middleware are not well suited to manage and provide services at such large scale. To improve the scalability and adaptability of operating system and middleware services on future many-core platform, we propose the pinned OS/services. By porting each OS and runtime system (middleware) service to a separate core (special hardware acceleration), we expect to achieve maximal performance gain and energy efficiency in many-core environments. As a case study, we target on XML (Extensible Markup Language), the commonly used data transfer/store standard in the world. We have successfully implemented and evaluated the design of porting XML parsing service onto Intel 48-core Single-Chip Cloud Computer (SCC) platform. The results show that it can provide considerable energy saving. However, we also identified heavy performance penalties introduced from memory side, making the parsing service bloated. Hence, as a further step, we propose the memory-side hardware accelerator for XML parsing. With specified hardware design, we can further enhance the performance gain and energy efficiency, where the performance can be improved by 20% with 12.27% energy reduction.
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