How PyTorch GPU kernels work, and two optimization paths: torch.compile vs custom kernels
ariG23498 · x · 2026-10-31
A refresher on PyTorch GPU optimization: models execute through low-level hardware-specific kernels, and profiling reveals gaps between kernel launches where the GPU sits idle. Two main fixes: torch.compile fuses operations into fewer kernels to cut overhead, while custom kernels (optimized attention, fused ops) target specific workloads for maximum utilization.
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