Literature is plentiful in works exploiting cache locality for GPUs. A majority of them explore replacement or bypassing policies. In this paper, however, we surpass this exploration by fabricating a formal proof for a no-overhead quasi-optimal caching technique for caching textures in graphics workloads. Textures make up a significant part of main memory traffic in mobile GPUs, which contributes to the total GPU energy consumption. Since texture accesses use a shared L2 cache, improving the L2 texture caching efficiency would decrease main memory traffic, thus improving energy efficiency, which is crucial for mobile GPUs. Our proposal reaches quasi-optimality by exploiting the frame-to-frame reuse of textures in graphics. We do this by traversing frames in a boustrophedonic11Boustrophedon is a style of writing in which alternate lines of writing are reversed in order. This is in contrast to most modern languages, where the order of lines is the same, usually left-to-right. manner w.r.t. the frame-to-frame tile order. We first approximate the texture access trace to a circular trace and then forge a formal proof for our proposal being optimal for such traces. We also complement the proof with empirical data that demonstrates the quasi-optimality of our no-cost proposal.

Cache Replacement Policies are known to have an important impact on hit rates. The OPT replacement policy [27] has been formally proven as optimal for minimizing misses. Due to its need to look far ahead for future memory accesses, it is often reduced to a yardstick for measuring the efficacy of other practical caches. In this paper, we bring the OPT to life, in architectures for mobile GPUs, for which energy efficiency is of great consequence. We also mold other factors in the memory hierarchy to enhance its impact. The end results are a 13.8% decrease in the memory hierarchy energy consumption and an increased throughput in the Tiling Engine. We also observe a 5.5% decrease in the total GPU energy and a 3.7% increase in frames per second (FPS).

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.