DRAM access reduction in GPUs by thread-block scheduling for overlapped data reuse

General Purpose Graphics Processing Units (GPG-PUs) show very high throughput when executing parallel programs. However, they usually demand very large DRAM bandwidth and consume much power for memory access. Although recent high performance GPGPUs equip L2 cache to absorb some of DRAM accesses, the cache hit ratio can hardly be very high because of the limited cache size. We propose a GPU thread-block scheduling method that can better utilize L2 cache and reduce the DRAM memory access. This scheduling method exploits the inter-block locality in the scheduling of GPU thread-blocks. This method can easily be implemented by modifying application programs. This technique is applied to the Hotspot benchmark programs, and reduces the DRAM access by up to 39%.