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Daisen: A Framework for Visualizing Detailed GPU Execution
Graphics Processing Units~(GPUs) have been widely used to accelerate artificial intelligence, physics simulation, medical imaging, and information visualization applications. To improve GPU performance, GPU hardware designers need to identify performance issues by inspecting a huge amount of simulator-generated traces. Visualizing the execution traces can reduce the cognitive burden of users and facilitate making sense of behaviors of GPU hardware components. In this paper, we first formalizedoi:10.31219/osf.io/73ry8 fatcat:vkviut57ljdrflyigcfawd6pci