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Automated discovery and optimization of low-level GPU kernels through evolutionary algorithms.
Distinct from Kernel-Level Optimizations: Focuses on the evolutionary discovery of kernels rather than just utilizing existing libraries like cuBLAS.
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OpenEvolve is an open-source framework for evolutionary computation that uses language models to drive automated optimization across multiple domains. It can evolve system prompts for large language models, refine source code across programming languages, search for optimal GPU kernel configurations, discover interpretable mathematical expressions from data, and maintain diverse populations of high-performing solutions. The framework integrates multiple evolutionary strategies, including MAP-Elites diversity mapping and island-based topologies, to avoid premature convergence and preserve a wid
Evo searches automatically for optimal GPU kernel configurations using evolutionary algorithms to improve neural network operation performance.