high performance computing on graphics processing units: hgpu.org

Quantum computing emerges as a field that captures a great theoretical interest. Its simulation represents a problem with high memory and computational requirements which makes advisable the use of parallel platforms. In this work we deal with the simulation of an ideal quantum computer on the Compute Unified Device Architecture (CUDA), as such a problem can benefit from the high computational capacities of Graphics Processing Units (GPU). After all, modern GPUs are becoming very powerful computational architectures which is causing a growing interest in their application for general purpose. CUDA provides an execution model oriented towards a more general exploitation of the GPU allowing to use it as a massively parallel SIMT (Single-Instruction Multiple-Thread) multiprocessor. A simulator that takes into account memory reference locality issues is proposed, showing that the challenge of achieving a high performance depends strongly on the explicit exploitation of memory hierarchy. Several strategies have been experimentally evaluated obtaining good performance results in comparison with conventional platforms.