Selectively GPU Cache Bypassing for Un-Coalesced Loads

摘要

GPUs are widely used to accelerate general purpose applications, and could hide memory latency through massive multithreading. But multithreading can increase contention for the L1 data caches (L1D). This problem is exacerbated when an application contains irregular memory references which would lead to un-coalesced memory accesses. In this paper, we propose a simple yet effective GPU cache Bypassing scheme for Un-Coalesced Loads (BUCL). BUCL makes bypassing decisions at two granularities. At the instruction-level, when the number of memory accesses generated by a non-coalesced load instruction is bigger than a threshold, referred as the threshold of un-coalescing degree (TUCD), all the accesses generated from this load will bypass L1D. The reason is that the cache data filled by un-coalesced loads typically have low probabilities to be reused. At the level of each individual memory access, when the L1D is stalled, the accessed data is likely with low locality, and the utilization of the target memory sub-partition is not high, this memory access may also bypass L1D. Our experiments show that BUCL achieves 36% and 5% performance improvement over the baseline GPU for memory un-coalesced and memory coherent benchmarks, respectively, and also significantly outperforms prior GPU cache bypassing and warp throttling schemes.