FlexFlow
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About
FlexFlow is a DNN framework that automatically discovers fast parallelization strategies for distributed DNN training. It generalizes and goes beyond today's manually designed parallelization strategies (e.g., data and model parallelism) for distributed DNN training by exploring parallelization opportunities across different Samples, Operators, Attributes, and Parameters. FlexFlow includes a novel execution simulator to evaluate the runtime performance of different strategies and uses an automated search algorithm to discover highly optimized strategies, which generally outperform today's manually designed strategies. FlexFlow uses a novel hierarchical search algorithm to jointly optimize algebraic transformations and parallelization while maintaining scalability. It supports parallelizing DNN training through combinations of the Sample, Operator, Attribute, and Parameter dimensions. FlexFlow accelerates generative LLM inference with speculative inference and token tree verification.
Platform
Features
• accelerates generative llm inference with speculative inference and token tree verification
• includes a novel execution simulator to evaluate runtime performance
• explores parallelization opportunities across different samples, operators, attributes, and parameters
• automatically discovers fast parallelization strategies for distributed dnn training
• supports parallelizing dnn training through combinations of sample, operator, attribute, and parameter dimensions
• generalizes and goes beyond manually designed parallelization strategies
• jointly optimizes algebraic transformations and parallelization while maintaining scalability
• uses an automated search algorithm to discover highly optimized strategies
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