Fast Sparse Deep Neural Network Inference with Flexible SpMM Optimization Space Exploration

Deep neural networks (DNN) have been widely used in many fields. With the ever-increasing model size, the DNN scalability suffers. Sparse deep neural networks (SpDNN) are promising to resolve this problem, but the sparse data makes it difficult to execute efficiently on GPUs due to load imbalance and irregular memory accesses. The recent MIT/IEEE/Amazon GraphChallenge has shown several big advance...