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DTSTAMP:20230124T170804Z
LOCATION:C1-2-3
DTSTART;TZID=America/Chicago:20221116T083000
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UID:submissions.supercomputing.org_SC22_sess274_rpost146@linklings.com
SUMMARY:Efficient Sparse Deep Neural Network Computation on GPU with TVM
DESCRIPTION:Posters, Research Posters\n\nEfficient Sparse Deep Neural Netw
 ork Computation on GPU with TVM\n\nWang, Malladi, Ji\n\nThis poster presen
 ts GPU optimizations for Sparse Deep Neural Networks using Apache TVM. Alt
 hough various deep neural network models exist, SpDNNs have shown great im
 provements in the size and memory of neural networks. SpDNNs provide uniqu
 e scalability difficulties in which optimizations and advancements can be 
 made. Apache TVM is a machine learning compiler framework for CPUs and GPU
 s. It has been shown to have promising improvements for the performance, d
 eployment, and optimizations of the networks. To evaluate its effectivenes
 s for SpDNNs, this work builds SpDNNs with Apache TVM and compares with cu
 rrent SpDNNs. When testing with various datasets, TVM-based implementation
  can achieve faster and more efficient optimizations.\n\nRegistration Cate
 gory: Tech Program Reg Pass, Exhibits Reg Pass
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