M
Martin Rinard
Researcher at Massachusetts Institute of Technology
Publications - 381
Citations - 19269
Martin Rinard is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Data structure & Compiler. The author has an hindex of 70, co-authored 372 publications receiving 18126 citations. Previous affiliations of Martin Rinard include University of California, Santa Barbara & Stanford University.
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A Hardware Platform for Efficient Multi-Modal Sensing with Adaptive Approximation
TL;DR: The design of Warp is presented and an evaluation of the hardware implementation is presented to show how Warp's design enables performance and energy efficiency versus ac- curacy tradeoffs.
Book ChapterDOI
A language for role specifications
TL;DR: A programming model which allows the developer to specify the roles of objects at different points in the computation and the effect of each operation at the granularity of role changes that occur in identified regions of the heap is provided.
Proceedings ArticleDOI
Encoder logic for reducing serial I/O power in sensors and sensor hubs
TL;DR: Communicating data from sensors such as gyroscopes and accelerometers, to processors, typically occurs over printed circuit board traces, often costing up to 40 µW at data rates of 1 Mb/s.
Efficient Specification-Assisted Error Localization and Correction
TL;DR: A new error localization tool, Archie, is presented that accepts a specification of key data structure consistency constraints, then generates an algorithm that checks if the data structures satisfy the constraints, and a set of specification analyses and optimizations are presented that improve the performance of the generated checking algorithm.
Proceedings ArticleDOI
Time Dilation and Contraction for Programmable Analog Devices with Jaunt
Sara Achour,Martin Rinard +1 more
TL;DR: Jaunt is presented, a new solver that scales the values that configure the analog device to ensure the resulting analog computation executes within the operating constraints of the device, preserves the recoverable dynamics of the original simulation, and executes slowly enough to observe these dynamics at the sampled digital outputs.