Luis Ceze
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Neural Acceleration For General-Purpose Approximate Programs
This paper describes a new approach that uses machine learning-based transformations to accelerate approximation-tolerant programs.
The Bulk Multicore Architecture For Improved Programmability
Easing the programmer's burden does not compromise system performance or increase the complexity of hardware implementation.
Two Hardware-Based Approaches For Deterministic Multiprocessor Replay
Modern computer systems are inherently nondeterministic due to a variety of events that occur during an execution. The lack of repeatability that arises from this nondeterminism can make it difficult to develop and maintain correct software.
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