PyTorch’s compiler achieves significant speedups through kernel fusion, a technique that combines dependent operations into single, efficient kernels. By fusing multiple operations together, the compiler eliminates intermediate memory writes and reads, reducing memory bandwidth usage by up to 50% while decreasing kernel launch overhead. A pointwise fusion example shows three separate kernels (multiply, add, sigmoid) combined into one, alongside other fusion types including reduction fusion, GEMM epilogue fusion, and horizontal fusion. These optimizations can be applied automatically using torch.compile() without modifying existing code.
