Performance Prediction Tools


Dimemas is a performance analysis tool for message-passing programs. The Dimemas simulator reconstructs the time behaviour of a parallel application on a machine modelled by the key factors influencing the performance. With a simple model, a network of SMP nodes (see below), Dimemas allows to simulate complete parametric studies in a very short time frame. Dimemas generates as part of its output a Paraver trace file, enabling the user to conveniently examine the simulator run.


Illustration: Dimemas Simulator Model

Partner: BSC


BOAST is a modular meta-programming framework. It implements a DSL that allows description and parametrization of computing kernels. Application developer can port their computing kernel to BOAST and implement several optimization techniques. The kernels with the chosen optimizations can then be generated in the target language of choice: C, Fortran, OpenCL, CUDA or C with vector instructions. This approach also allows application developers to study application specific parameters. The generated kernels can then be built and executed inside of BOAST to evaluate their performance. With this framework one can easily find the best performing version of a kernel on a given architecture. Performance results could also be used to interact with automatic performance analysis tools (ASK, Collective Mind, ...) in order to reduce the search space. Binary kernels that are generated can also be given to tools like MAQAO for static or dynamic analysis.

Illustration: BOAST Architecture

Partner: CNRS