Felix: Optimizing Tensor Programs with Gradient Descent
Yifan Zhao, Hashim Sharif, Vikram Adve, Saša Misailovíc
Abstract
Obtaining high-performance implementations of tensor programs such as deep neural networks on a wide range of hardware remains a challenging task. Search-based tensor program optimizers can automatically find high-performance programs on a given hardware platform, but the search process in existing tools suffer from low efficiency, requiring hours or days of time to discover good programs due to the size of the search space.
Topics & Concepts
Computer scienceTask (project management)ImplementationTensor (intrinsic definition)Range (aeronautics)Gradient descentProcess (computing)Artificial neural networkComputer engineeringArtificial intelligenceParallel computingProgramming languageMathematicsEngineeringAerospace engineeringSystems engineeringPure mathematicsParallel Computing and Optimization TechniquesAdvanced Neural Network ApplicationsTensor decomposition and applications