high performance computing on graphics processing units: hgpu.org

During this decade, high performance computation demand has been increasing more and more, for example in the field of humanities [1]. Scientists and investigators are in need of high speed and performance environments for their research, which need to perform millions of floating points operations per second [2]. One way to achieve this goal is to increase the power of the hardware. Multi-core CPUs and Supercomputers [3] are an example of the evolution of this path. However, even this type of hardware (Supercomputers) has their limits. Supercomputers, besides being very expensive and complicate to build, have a very high electricity consumption [22]. In the meanwhile, another kind of processors, the GPUs, have experimented a great improvement within this decade, and a single GPU IC chip is able to achieve 10 TFLOPS. This performance attracts HPC researchers to the potential computing power of GPUs, so in the last decade the field called GPGPU [17] (General-Purpose computation on Graphics Processing Units) has gained more importance. However programming on the GPU entails a great difficulty, due to its architecture, that is categorized into two types nowadays.