Resource-Aware Compiler Prefetching for Many-Cores

—Super-scalar, out-of-order processors that can have tens of read and write requests in the execution window place significant demands on Memory Level Parallelism (MLP). Multi- and many-cores with shared parallel caches further increase MLP demand. Current cache hierarchies however have been unable to keep up with this trend, with modern designs allowing only 4-16 concurrent cache misses. This disconnect is exacerbated by recent highly parallel architectures (e.g. GPUs) where power and area per-core budget favor lighter cores with less resources. Support for hardware and software prefetch increase MLP pressure since these techniques overlap multiple memory requests with existing computation. In this paper, we propose and evaluate a novel Resource-Aware Prefetching (RAP) compiler algorithm that is aware of the number of simultaneous prefetches supported, and optimized for the same. We show that in situations where not enough resources are available to issue prefetch instructions for ...

• Type: Journal
• Year: 2010
• Where: ISPDC
• Authors: George C. Caragea, Alexandros Tzannes, Fuat Keceli, Rajeev Barua, Uzi Vishkin
• Keywords: Algorithm, Distributed And Parallel Computing, ISPDC 2010, Memory Level Parallelism, RAP Algorithm