GPUHELP: um ambiente de apoio à execução de programas paralelos em arquiteturas de GPU

• Ano de defesa: 2014
• Autor(a) principal: Borges, Douglas Pires
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Ciência da Computação; UFSM; Programa de Pós-Graduação em Informática
• Palavras-chave em Português: Programação paralela em GPU; Ambiente de apoio à execução de programas paralelos em GPU; Parallel programming on GPU; Environment supporting execution of parallel programs on GPU; OpenCL/CUDA; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/5422

Faced with complex problems that involve scientific applications, researchers are looking for new ways to optimize the processing of these, using new concepts and paradigms for parallel and distributed programming. An emerging alternative to this scenario is the use of GPUs (Graphics Processing Unit) due to its high computational power. However, along with the benefits from the use of such techniques has been diverse and complex issues related to teaching and learning from them. Thus, researchers began to devote efforts to obtain better results in teaching these areas. So, the environments to support teaching of parallel programming have emerged. Such environments provide a set of tools for the development and testing of applications, thereby improving the educational experience. However, the current researches focuses on environments supporting teaching parallel programming for CPU architectures, not exist environments to teaching support teaching oriented architectures GPU. The absence of such environments has a negative impact, proven in various scientific researches. In this context, this work presents an environment for supporting parallel programming in GPU, called GPUHelp. The GPUHelp provides to users a complete solution for developing and codes test for GPU architectures, the CUDA and OpenCL, even for those users that do not have graphics cards on their computers, which was not possible before, given the need to graphics card compatible with such architectures. Evaluations have shown that GPUHelp is a feasible solution with different applicability scenarios in education and training on parallel programming GPU.