2014 Topics in Parallel Computation
Abstract
This course covers theory of concurrency and parallelism. It also cover how to use it an high performance computing. The course is
providing students with the concept of processing that need high performance computing (hpc) , the hpc computing architecture. providing students with skills to analysis problem solving that needs the hpc technology. providing students with skills to solve problem in cluster computing environments. The Students will have some exercises and homework using Cluster and GPU.
Intellectual Merit
It help students to explore and have sufficient experience using state of the art resources. Their experiences are valuable in the future collaborative activities.Software and curriculum materials developed under this project will be distributed to the community as free, open source materials.
Broader Impact
it provides basic background in parallel computation. The students passed this courses will be able to joint some research projects
related to parallel computation using Cluster and GPU.
Use of FutureGrid
students will compile MPI and CUDA codes, and have them run on Cluster and GPU.
Scale Of Use
The class will use the system about 5-6 hours/day. In cluster, they will be using about 32-64 cores
Futuregrid is a resource provider for