Maestro: Data Orchestation and Tuning for OpenCL Devices

Abstract

Abstract. As heterogeneous computing platforms become more prevalent, the programmer must account for complex memory hierarchies in addition to the diculties of parallel programming. OpenCL is an open standard for parallel computing that helps alleviate this diculty by providing a portable set of abstractions for device memory hierarchies. However, OpenCL requires that the programmer explicitly controls data transfer and device synchronization, two tedious and error-prone tasks. This paper introduces Maestro, an open source library for data orchestration on OpenCL devices. Maestro provides automatic data transfer, task decomposition across multiple devices, and autotuning of dynamic execution parameters for some types of problems.