Characterizing and improving the use of demand-fetched caches in GPUs
Wenhao Jia, Kelly A. Shaw, Margaret Martonosi · 2012
Initially introduced as special-purpose accelerators for games and graphics code, graphics processing units (GPUs) have emerged as widely-used high-performance parallel computing platforms. GPUs traditionally provided only software-managed local memories (or scratchpads) instead of demand-fetched caches. Increasingly, however, GPUs are being used in broader application domains where memory access patterns are both harder to analyze and harder to manage in software-controlled caches. In response, GPU vendors have included sizable demand-fetched caches in recent chip designs. Nonetheless, several problems remain. First, since these hardware caches are quite new and highly-configurable, it can be difficult to know when and how to use them; they sometimes degrade performance instead of improving it. Second, since GPU programming is quite distinct from general-purpose programming, application programmers do not yet have solid intuition about which memory reference patterns are amenable to demand-fetched caches.