PI
Core/Dual

Saman Amarasinghe

Professor

Phone

253-8879

Room

32-G744

Saman P. Amarasinghe is a Professor in the Department of Electrical Engineering and Computer Science. He leads the Commit compiler group. His research interests are in discovering novel approaches to improve the performance of modern computer systems and make them more secure without unduly increasing the complexity faced by the end users, application developers, compiler writers, or computer architects. Saman received his BS in Electrical Engineering and Computer Science from Cornell University in 1988, and his MSEE and Ph.D from Stanford University in 1990 and 1997, respectively.

Projects

Project

Program Performance Prediction with Deep Learning

Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady-state (the throughput) is important for both compiler designers and performance engineers.

However, building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC) machines with sophisticated processor microarchitectures in that it is tedious, error-prone, and must be performed from scratch for each processor generation.

Ithemal is the first tool that learns to predict the throughput of a set of instructions. It does so more accurately than state-of-the-art hand-written tools currently used in compiler backends and static machine code analyzers. In particular, Ithemal has less than half the error of state-of-the-art analytical models (LLVM's llvm-mca and Intel's IACA).

 3 More

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