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If you have a question about this talk, please contact Grigorios Mingas. Relaxing constraints of 100% accuracy in datapath can provide the freedom to create designs with better performance or energy efficiency. In this talk, I will describe the probabilistic models which are employed to explore these trade-offs for key arithmetic primitives. We show that because specific input patterns are required to cause timing violations and that these patterns arise rarely, a lower expected error can be attained by allowing some timing violations to occur, instead of reducing the precision of a circuit to meet a target latency. This talk is part of the CAS Talks series. This talk is included in these lists:
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