FlexFlow
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About
FlexFlow is a DNN framework that automatically discovers fast parallelization strategies for distributed deep neural network training. It goes beyond manually designed strategies by exploring parallelization opportunities across Samples, Operators, Attributes, and Parameters. It uses a novel execution simulator and automated search algorithm to find highly optimized strategies. FlexFlow also features joint optimization of algebraic transformations and parallelization, flexible parallelization across various dimensions, and speculative inference to accelerate generative LLM inference.
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Task
Features
• accelerates generative llm inference with speculative inference and token tree verification
• uses an automated search algorithm to discover highly optimized strategies
• includes a novel execution simulator to evaluate runtime performance
• explores parallelization opportunities across different samples, operators, attributes, and parameters
• generalizes and goes beyond today's manually designed parallelization strategies
• automatically discovers fast parallelization strategies for distributed dnn training
• flexible parallelization through combinations of sample, operator, attribute, and parameter dimensions
• joint optimization of algebraic transformations and parallelization
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