Fusion: abstrações linguísticas sobre Java para programação paralela heterogênea sobre GPGPUs

Abstract

Acceleration units free, or GPU (Graphical Processing Units), have been consolidated in recent years for general purpose computing for accelerating critical sections of programs that exhibit high standards of performance and the execution time. GPUs are one of several types of general-purpose computational accelerators that have been built on various platforms for high performance computing, especially also for the MIC (Many Integrated Cores) and FPGA (Field Programmable Gateway Arrays). Despite the emphasis on the research of new parallel algorithms capable of exploiting the massive parallelism offered by GPGPU devices are still incipient initiatives on new programming abstractions that make the simplest description of these algorithms on GPGPUs, without detriment to the effciency. It is still necessary that the programmer has specific knowledge of the peculiarities of the architecture of these devices, as well as programming techniques that are not domain even experienced parallel programmers today. In recent years, NVIDIA, an industry that has dominated the evolution of architectural GPGPU devices, launched the Kepler architecture, including extensions to support Hyper-Q and Dynamic Parallelism (DP), which offer new opportunities for expression patterns of parallel programming on such devices. This paper aims at proposing new programming abstractions over a parallel object-oriented language based on Java, am expressing parallel computations heterogeneous type multicore / manycore, where the GPU device is shared by a set of parallel threads running in host processor, on a higher level of abstraction compared to existing alternatives, but still offering the programmer full control over the use of device capabilities. The design of this proposed language abstractions, hereinafter called Fusion, part of the expressiveness offered by Kepler architecture.