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View all- Castro RAndrade DFraguela B(2024)STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep LearningIEEE Access10.1109/ACCESS.2024.340232612(70581-70599)Online publication date: 2024
GPUs, with their high bandwidths and computational capabilities are an increasingly popular target for scientific computing. Unfortunately, to date, harnessing the power of the GPU has required use of a GPU-specific programming model ...
With fast development of GPU hardware and software, using GPUs to accelerate non-graphics CPU applications is becoming inevitable trend. GPUs are good at performing ALU-intensive computation and feature high peak performance; however, how to harness ...
Graphics Processing Units have emerged as powerful accelerators for massively parallel, numerically intensive workloads. The two dominant software models for these devices are NVIDIA’s CUDA and the cross-platform OpenCL standard. Until now, there has ...
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