Contemporary GPU architectures have multiple shader cores and a scheduler that distributes work (threads) among them, focusing on load balancing. These load balancing techniques favor thread distributions that are detrimental to texture memory locality for graphics applications in the L1 Texture Caches. Texture memory accesses make up the majority of the traffic to the memory hierarchy in typical low power graphics architectures. This paper focuses on improving the L1 Texture cache locality by focusing on a new workload scheduler by exploring various methods to group the threads, assign the groups to shader cores and also to reorder threads without violating the correctness of the pipeline. To overcome the resulting load imbalance, we also propose a minor modification in the GPU architecture that helps translate the improvement in cache locality to an improvement in the GPU’s performance. We propose DTexL that envelops these ideas and evaluate it over a benchmark suite of ten commercial games, to obtain a 46.8% decrease in L2 Accesses, a 19.3% increase in performance and a 6.3% decrease in total GPU energy. All this with a negligible overhead.

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This work has been supported by the CoCoUnit ERC Advanced Grant of the EU’s Horizon 2020 program (grant No 833057), the Spanish State Research Agency (MCIN/AEI) under grant PID2020-113172RB-I00, the ICREA Academia program and the AGAUR grant 2020-FISDU-00287.

Peer Reviewed