Special Issue: Computer Architecture and Systems

• Architecture and High Performance Computer Systems • Previous Articles     Next Articles

Making Effective Decisions in Computer Architects Real-World: Lessons and Experiences with Godson-2 Processor Designs

Wei-Wu Hu1 and Jian Wang1,2   

  1. 1Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China 2Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2008-04-21 Revised:2008-05-19 Online:2008-07-10 Published:2008-07-10

Although the design of many kinds of microprocessors has been under developing for several decades, the computer architecture R\&D community lacks well documented lessons and experiences about design decisions in the research literature. In this paper, we systematically present the design decisions we made during the designing and prototyping of Godson-2 series processors. The 250MHz Godson-2B, 450MHz Godson-2C, and 1GHz Godson-2E processors that implement 64-bit, four-issue, out-of-order architecture were taped out in 2003, 2004, and 2005, respectively. Each processor triples its predecessor in the SPEC CPU2000 rates. Our first-hand experiences and lessons gained from these designs would provide unique perspectives and insights that are not available in any existing text books and/or published papers. We summarize 10 critical lessons and experiences based on hundreds of our attempts at architectural and design optimizations for performance improvement of Godson-2 series processors. The issues include silicon-simulation correlation, design balancing, performance optimizing, and pico-architecture tuning. We conclude that persistent improvement, attitude towards work-on-silicon design, and insightful understanding of software and fabrication process are the three most important factors for designing a high performance processor with low energy consumption.

Key words: multidimensional transaction database; data mining; Ndimensionalinter-transaction association rules (NDITAR); generalized multidimensional association rules (GMDAR);

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