GPU-based heterogeneous architectures have been given much attention recently. How to get optimal performance out of those architectures with affordable programming effort remains a complex challenge. The PEPPHER framework is one possible solution. Within the PEPPHER framework, the StarPU run-time system is used to decrease such programming efforts, and at the same time to ensure near optimal performance by efficient scheduling over such architectures. However, adapting a normal C/C++ application to the StarPU runtime system requires additional programming effort.
This thesis implements and tests a composition tool for automatic adaptation of normal C/C++ applications withPEPPHER components to StarPU. This composition tool requires XML annotation for applications and several trivial changes to applications, which take limited efforts. Our results obtained by three test cases (vector scale, sorting, andmatrix multiplication) show that automatic adaptation works well on different platforms that StarPU supports. It is also shown that besides StarPU’s dynamic composition, this tool facilitates static composition to improve performance portability of normal C/C++ applications.