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Spatial Memory Streaming

Tuesday February 7, 2006
Hamerschlag Hall D-210
4:00 pm

Stephen Somogyi
Carnegie Mellon University

Prior research indicates that there is much spatial variation in an application's memory access patterns. Modern memory systems, however, use small fixed-size cache blocks and as such cannot exploit the variation, because increasing the block size would prohibitively increase bandwidth demands. In this talk, I will show that memory access patterns in commercial workloads are spatially correlated over large memory regions (e.g., several kB), and that such patterns are repetitive and predictable through code-based correlation. I propose a hardware mechanism, called Spatial Memory Streaming, that learns repetitive patterns and streams cache blocks ahead of demand misses. I evaluate this design on commercial and scientific workloads, demonstrating speedups of 19% on average and 282% at best.

Stephen Somogyi is a fourth year graduate student in the Computer Architecture Lab at Carnegie Mellon, working with Prof. Babak Falsafi. Stephen's research involves techniques to accelerate multiprocessor commercial servers through improvements to the memory system.


Department of Electrical and Computer EngineeringCarnegie Mellon UniversitySchool of Computer Science