GPU Cloud Architectures for Bioinformatic Applications

The world of computing is constantly evolving. The trends that are shaping today's applications are Cloud computing and GPU computing. These technologies allow bringing high performance computations to low power devices, when using a computing outsourcing architecture. Following the trend, bioinformatic applications are looking to take advantage of these paradigms, but there are challenges that have to be solved. Data that these applications work with is usually sensible and has to be protected. Also, GPU usage in Cloud architectures currently presents inefficiencies. This paper makes a review of the characteristics of Cloud computing outsourcing architectures, including the security aspects, and GPU usage for these applications. The proposed architecture includes GPU devices and tries to make efficient use of them. The experiments show that it has the opportunity to increase parallelism and reduce context switching costs when running different applications concurrently on the GPU.