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The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way ...
The floating-point unit is one of the most common building block in any computing system and is used for a huge number of applications. By combining two state-of-the-art techniques of imprecise hardware, namely Gate-Level Pruning and Inexact Speculative Ad ...
Designing digital circuits well is notoriously difficult. This difficulty stems in part from the very
many degrees of freedom inherent in circuit design, typically coupled with the need to satisfy
various constraints. In this thesis, we demonstrate how for ...
Software robustness is an ever-challenging problem in the face of today's evolving software and hardware that has undergone recent shifts. Instruction-grain monitoring is a powerful approach for improved software robustness that affords comprehensive runti ...