Latency
Kernel fusion combines adjacent tensor operations into a single device kernel. Intermediate values can stay on chip instead of returning to device memory between operations.
Fusion can reduce memory traffic and host launch count along a serving path. Excessive fusion can raise register pressure, limit scheduling, or produce kernels poorly suited to some shapes.
Compilers and handwritten kernels fuse patterns supported by their backends. Teams measure representative shapes because a useful fusion boundary depends on data layout and hardware.
Kernel fusion combines adjacent tensor operations into a single device kernel. Intermediate values can stay on chip instead of returning to device memory between operations. Compilers and handwritten kernels fuse patterns supported by their backends. Teams measure representative shapes because a useful fusion boundary depends on data layout and hardware.
Fusion can reduce memory traffic and host launch count along a serving path. Excessive fusion can raise register pressure, limit scheduling, or produce kernels poorly suited to some shapes.
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