SHF: Small: Minimal Multithreading - Exploiting Redundancy in Parallel Systems

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

Due to technology and industry trends, parallelism and energy efficiency have emerged as critical considerations in future computing systems. The investigators observe that many convenient models for writing parallel programs can lead to significant redundancy in computation and data. This redundancy can be used to improve performance and reduce energy consumption. The investigators observe that many parallel software models (e.g. data parallelism, Single-Program Multiple Data (SPMD), multi-programming, and high-throughput computing) consist of multiple threads of computation with very similar instructions streams and working sets of data. The trick, however, is to design efficient mechanisms that both exploit this similarity and effectively support the differences. This project will follow two research thrusts to eliminate redundancy across five application domains. First, the research will explore multi-threaded processor core designs that eliminate redundant instruction fetch and/or execution. Second, the research will explore content-aware caching techniques that reduce redundant storage of identical data across parallel threads and processes.