Improving GPU Cache Hierarchy Performance with a Fetch and Replacement Cache

In the last few years, GPGPU computing has become one of the most popular computing paradigms in high-performance computers due to its excellent performance to power ratio. The memory requirements of GPGPU applications widely differ from the requirements of CPU counterparts. The amount of memory accesses is several orders of magnitude higher in GPU applications than in CPU applications, and they present disparate access patterns. Because of this fact, large and highly associative Last-Level Caches (LLCs) bring much lower performance gains in GPUs than in CPUs.