FlexFlow
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About
FlexFlow is a Deep Neural Network (DNN) framework designed to automatically discover fast parallelization strategies for distributed DNN training. It goes beyond manually designed parallelization strategies (e.g., data and model parallelism) by exploring opportunities across different Samples, Operators, Attributes, and Parameters. FlexFlow includes a novel execution simulator to evaluate the runtime performance of various strategies and employs an automated search algorithm to discover highly optimized strategies, which generally outperform today's manually designed approaches. Key capabilities include joint optimization of algebraic transformations and parallelization, flexible parallelization across multiple dimensions, and acceleration of generative LLM inference with speculative inference.
Platform
Features
• automatically discovers fast parallelization strategies for distributed dnn training
• automated search algorithm for highly optimized strategies
• novel execution simulator to evaluate runtime performance
• speculative inference for generative llm acceleration
• flexible parallelization across sample, operator, attribute, and parameter dimensions
• joint optimization of algebraic transformations and parallelization
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