Performance analysis of cache oblivious Algorithms in the Fresh Breeze memory model

[摘要] The Fresh Breeze program execution model was designed for easy, reliable and massively scalable parallel performance. The model achieves these goals by combining a radical memory model with efficient fine-grain parallelsim and managing both in hardware. This presents a unique opportunity for studying program execution in a system whose memory behavior is not well understood. In this thesis, I studied the behavior of cache-oblivious algorithms within the Fresh Breeze model by designing and implementing a cache-oblivious matrix multiply within the Fresh Breeze programming framework, as well as a cache-naive algorithm for comparison. The algorithms were implemented in C, using the Fresh Breeze run-time libraries, and profiled on a simulated Fresh Breeze processor. I profiled both programs across a range of problem sizes, memory speeds and memory types in order to best understand their behavior and accurately characterize their performance.

[发布机构] Massachusetts Institute of Technology