D-Matrix says its chips can run inference workloads 10 times faster and using five times less energy than a standalone graphics processing unit from Nvidia. Like Cerebras, D-Matrix is trying to prove ...
Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...
Abstract: Sparsity is becoming arguably the most critical dimension to explore for efficiency and scalability as deep learning models grow significantly larger. Particularly, pruning is a common ...
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