A Static Task Partitioning Approach for Heterogeneous Systems Using OpenCL
http://??
The authors propose a purely static approach based on predictive modeling and program features. They extract static code features from OpenCL kernel source codes and runtime pass the run-time information such as kernel arguments or index space to the model. Using Support Vector Machines, they partition and mapping the workload of OpenCL kernel on heterogeneous CPU-GPU systems. However, the static features is less accurate than runtime features. Therefore, it degrades the quality of the SVM model.
Dominik Grewe