Analysis on parallelism between CPU and GPGPU processing on cluster computing

Computer cluster is a collection of multiple computers connected together so that it can be viewed and perform as a single computer using an interconnected device. Graphical Processing Unit is a specialized hardware used to accelerate the creation of an image by manipulating and altering the memory to help CPU to produce an image. Previously, only CPU is used to perform the task execution in a cluster, however since the advancement of technology in cluster computing, GPU´s can now be used as alternative processor to perform execution of a task or job. Due to its relatively cheap in Flops/price ratio, GPGPU cluster system has gained a lot of popularity, however, the real world performance for both CPU cluster system and GPGPU cluster system has not been widely tested. In this paper, the performance between CPU cluster system and GPGPU cluster system simulating proteins using GROMACS 4.6.5 will be measured and analyzed, and how the parallelism between the two will be evaluate by comparing two set of tasks. The cluster´s protein folding performance is measured in ns/day, average CPU utilization, average memory usage, and average network bandwidth will be taken into account in this simulation.