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Calibrating Achievable Design Roundtable Discussion June 9, 2002. Wayne Dai, Andrew Kahng, Tsu-Jae King, Wojciech Maly, Igor Markov, Herman Schmit, Dennis Sylvester. Facilitator: Bill Joyner, IBM/SRC. Attendees. Faculty
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Calibrating Achievable Design Roundtable Discussion June 9, 2002 Wayne Dai, Andrew Kahng, Tsu-Jae King, Wojciech Maly, Igor Markov, Herman Schmit, Dennis Sylvester Facilitator: Bill Joyner, IBM/SRC
Attendees • Faculty • Herman Schmit, Wojciech Maly, Igor Markov, Dennis Sylvester, Andrew Kahng • Students • Michael Wang, Shuo Zhou, Bao Liu,, Stefanus Mantik, Yu Chen, Mike Oliver • Industry • Bill Joyner, Takahide Inoue, Simon Thomas, James Duley • Other Industry feedback • Sani Nassif
Discussion • What’s the big problem? • Cost tradeoffs need to be understood and modeled! • Comments: 5 cents / mm^2 cost with 90nm technology and 300mm wafers. Reference fab may be constructed and available; possibly available to GSRC? • Variability • What variability is tolerable? (This may be a sub-text to cost.) • Technology utilization • E.g., How to best use 100nm • Comment: we need a utilization vision, not just a technology vision (power? pin-limited?) • Sharing of information (across industry, across academia, across industry-academia) • E.g., shortage of qualified (analog) designers, and the issue of VLSI design education • Comment: Sometimes design is limited by design talent, but the product still gets out (available talent is applied as best it can…) • Is the solution education? (Re-education of old analog designers, education of digital designers in analog issues)
Discussion • What’s being done well? • Knowledge management for CAD and other concepts • Seeding and promoting ideas (collaboration, metrics, open-source) for the participants and within the GSRC and other centers • Motivating and justifying research directions for the other themes. • What could be improved? • Improved avenues for sharing data (esp. fab data) in addition to algorithms • Pushing others to use and adopt the Bookshelf • Become THE source of benchmark design examples and algorithm data • Explore and identify the future applications that will drive silicon consumption