TEMP: Thread batch enabled memory partitioning for GPU
As massive multi-threading in GPU imposes tremendous pressure on memory subsystems, efficient bandwidth utilization becomes a key factor affecting the GPU throughput. In this work, we propose thread batch enabled memory partitioning (TEMP), to improve GPU performance through the improvement of memory bandwidth utilization. In particular, TEMP clusters multiple thread blocks sharing the same set of pages into a thread batch and dispatches the entire thread batch to a stream multiprocessor. TEMP separates the memory access streams of different thread batches by OS memory management, preserving the intrinsic locality of thread batches and increasing the memory access parallelism. Experimental results show that TEMP can obtain up to 10.3% performance improvement and 14.6% DRAM energy reduction compared to a state-of-the-art scheduler without any memory-side optimizations.
