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Abstract
Throughput processors, such as GPGPUs, rely on massive multithreading to hide long memory latency. However, the high number of active threads GPGPU executes concurrently leads to severe cache thrashing and conflict misses. In this work, we propose a low-cost thrashing-resistant conflict-avoiding streaming-aware GPGPU cache management scheme that efficiently utilizes the GPGPU cache resources and addresses all the problems associated with GPGPU caches. The proposed method employs three orthogonal techniques. First, it dynamically detects and bypasses streaming applications. Second, a Dynamic Warp Throttling via Cores Sampling (DWT-CS) is proposed to alleviate cache thrashing. DWT-CS runs an exhaustive searching over cores to find the best number of warps that achieves the highest performance. Third, we employ a better cache indexing function, Pseudo Random Interleaving Cache (PRIC), that is based on polynomial modulus mapping, to mitigate associativity stalls and eliminate conflict misses. Our proposed method improves the average performance of streaming and contention applications by 1.2X and 2.3X respectively