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cs.LG2024
Optimizing Tensor Computation Graphs with Equality Saturation and Monte Carlo Tree Search
Jakob Hartmann, Guoliang He, Eiko Yoneki
The real-world effectiveness of deep neural networks often depends on their latency, thereby necessitating optimization techniques that can reduce a model's inference time while pr…
cs.LG2023★ 2 cited
X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation
Guoliang He, Sean Parker, Eiko Yoneki
Tensor graph superoptimisation systems perform a sequence of subgraph substitution to neural networks, to find the optimal computation graph structure. Such a graph transformation…