Parallel computers using the multicore technology are becoming widespread. Today, even an ordinary PC has more than one processor core, in principle a mini parallel computer by itself.  In order to unleash the computing power on multicore-based architectures, an appropriate programming model is essential. Today's two most widely used programming models are MPI http://www.mpi-forum.org/ and OpenMPhttp://www.openmp.org/. For a PC having several processor cores, both the programming approaches can be used.

Theoretically, OpenMP should be a better approach because of both OpenMP's simplicity and a multicore PC's underlying shared memory (and cache). However, it is yet to be seen that OpenMP clearly beats MPI on the multicore. To get a better understanding of this behavior, we need to carry out a detailed study by looking closely at issues such as communication overhead, the benefits and also disadvantages of shared memory and cache. A number of standard simulators for numerical computations will be used as the testbed.

After finishing the thesis, the master student is expected to get rich knowledge of state-of-the-art computer hardware, and the capability of using the two most widespread parallel programming approaches.

The master project is worth 60 credits, and the supervisor is Prof. Xing Cai.