Section: New Results

CPU+GPU adaptive computation

In this work, we aim to automatically use CPU and GPU to jointly execute a parallel code. To ensure load balance between different PUs, thus to preserve performance, it is necessary to consider the underlying hardware and the program parameters. Compiler optimizations, execution context, hardware availability and specification make it difficult to determine execution times statically. To overcome this hurdle we rely on a portable and automatic method for predicting execution times of statically generated codes on multicore CPUs and on CUDA GPUs. This approach relies on three stages: automatic code generation, offline profiling and online prediction.

This is the latest result of PhD student Jean-François Dollinger, advised by Vincent Loechner since 2011. Preliminary results, a "fastest-wins" algorithm between a multicore CPU and the best predicted GPU code version, was published in 2013 in ICPP [14] . We are currently writing a conference paper presenting the latest advances, and preparing a journal paper to be submitted in 2014, before Jean-François Dollinger's PhD defense by the end of the year.