ListarGrupos de investigación por tema "SpMM"
Mostrando ítems 1-2 de 2
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Probing the Efficacy of Hardware-Aware Weight Pruning to Optimize the SpMM routine on Ampere GPUs
(Institute of Electrical and Electronics Engineers, 2022)[Abstract]: The Deep Learning (DL) community found in pruning techniques a good way to reduce the models' resource and energy consumption. These techniques lead to smaller sparse models, but sparse computations in GPUs ... -
STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning
(Institute of Electrical and Electronics Engineers, 2024-05)[Abstract]: The relentless growth of modern Machine Learning models has spurred the adoption of sparsification techniques to simplify their architectures and reduce the computational demands. Network pruning has demonstrated ...
