Abstract
Graphical Processing Unit (GPU) programming languages are used extensively for general-purpose computations. However, GPU programming languages are at a level of abstraction suitable only for use by expert parallel programmers. This paper presents a new approach through which `C' or Java programmers can access these languages without having to focus on the technical or language-specific details. A prototype of the approach, named CUDACL, is introduced through which a programmer can specify one or more parallel blocks in a file and execute in a GPU. CUDACL also helps the programmer to make CUDA or OpenCL kernel calls inside an existing program. Two scenarios have been successfully implemented to assess the usability and potential of the tool. The tool was created based on a detailed analysis of the CUDA and OpenCL programs. Our evaluation of CUDACL compared to other similar approaches shows the efficiency and effectiveness of CUDACL.