GPTune is a performance autotuner designed particularly for HPC applications that are expensive to evaluate. GPTune uses Bayesian optimization based on Gaussian Process regression and supports advanced features such as multi-task learning, transfer learning, multi-fidelity/objective tuning, and parameter sensitivity analysis.

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History Database

GPTune provides a shared database (history database) that allows users to share performance data samples, so everyone can benefit from (expensive) runs of widely used high-performance computing codes. Sign up for free to access more data and use all the available features of the history database.

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Current statistics
  • Number of tuning problems (target applications): 23
  • Number of registered users: 45
  • Number of function evaluations: 14132

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