Augmenting Operating Systems with OpenCL Accelerators

Abstract

Heterogeneous computing leverages more than one kind of processors to boost the performance of user-space applications with the heterogeneous programming languages, e.g., OpenCL. While some works have been done to accelerate the computations required by Linux kernel software, they are either application-specific solutions or tightly coupled with the certain computing platforms and are not able to support the general-purpose in-kernel accelerations using different types of processors. In this article, the general-purpose software framework called Kernel acceleration with OpenCL (KOCL), is proposed to tackle the problem. KOCL exposes a set of the high-level programming interfaces for the Linux kernel module developers to offload compute-intensive tasks on different hardware accelerators without managing and coordinating the platform-specific computing and memory resources. The simplified programming efforts are achieved by the developed platform management and memory models, which provide a systematic means of managing the heterogeneous hardware resources. In addition, the one- and zero-copy data-buffering schemes are offered by KOCL, so that the offloaded tasks deliver high performance on the platforms with different memory architectures. We have developed the prototype system to accelerate the Network-Attached Storage server applications. Significant performance improvements are achieved with the three different types of accelerators, i.e., the multicore processor, the integrated GPU, and the discrete GPU, respectively. We believe that KOCL is useful for the design of embedded appliances to evaluate the performance of design alternatives.