An OpenCL Runtime Library for Embedded Multi-Core Accelerator

In recent years, improvements of energy efficiency and computational performance have become a major issue, because smartphones and tablets become popular. To implement high performance, multi-core accelerator consists of general purpose processors and accelerators are often used. But to use these multi-core accelerator efficiently, programmers have to consider synchronization and data transfer between accelerators, memory and I/O. Therefore frameworks such as OpenCL have been proposed for effective use of parallel computing resources of multi-core processors. OpenCL frameworks for GPGPU, Intel multi-core and many other kind of multi-core processors have been developed on Linux. However, in order to use those multi-core accelerators effectively, it is necessary to control accelerators with software environment aiming effective use of accelerators. Generally user mode application program calls OS to synchronize of accelerator's data transfer and termination of the its execution with overhead. In this paper, accelerators are controlled from collaborated OS and OpenCL library, instead of user mode application program. Our feature of these methods is that OS cooperates with library to reduce overhead of control accelerators. The proposed framework in this paper integrates the execution and data transfer control in an OpenCL library and an embedded OS. The OpenCL library creates task automaticity generated from the description of the user program. The OpenCL library gives scheduling information such as execution order about tasks to the scheduler of the embedded OS. The embedded OS's scheduler handles events of execution, termination and synchronization of data transfer via interrupts from accelerators. The scheduler determines to execute next task from the scheduling information passed by the OpenCL library. By the schemes to control accelerators are managed in OS, accelerators can be worked efficiently. The poster presentation shows the implemented OpenCL and OS framework for "Cube" processor embedded multi-core accelerator.