oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation

arXiv:2301.01333v3 Announce Type: replace
Abstract: With the rapid development of deep learning models and hardware support for dense computing, the deep learning workload characteristics changed significantly from a few hot spots on compute-intensive operations to a broad range of operations scattered across the models. Accelerating a few compute-intensive operations using the expert-tuned implementation of primitives does not fully exploit the performance potential of AI hardware. Various efforts have been made to compile a full deep neural network (DNN) graph. One …

abstract arxiv compilation compiler compute computing cs.lg cs.pf deep learning development graph hardware hot hybrid hybrid approach operations performance support type