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首先，Diverging from previous approaches that addressed kernels individually, AutoKernel begins with complete PyTorch models. It utilizes profiling tools with shape recording to measure individual kernel duration, then prioritizes optimization targets using computational efficiency principles—the mathematical concept that potential acceleration is constrained by a component's proportion of total runtime. Accelerating a kernel representing 60% of total duration by 1.5× yields 1.25× overall improvement, while identical acceleration of a 5% component produces merely 1.03× gain.
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此外，pThere's an element of "nobody was ever dismissed for choosing IBM." More cynically, some desire a vendor with sufficient resources to sue if failures occur. I hear this from the industry.
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另外值得一提的是，Design: The Combined LIV Framework
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