Experiment

Dr. Moncada's research interests are in the areas of parallel computing and distributed systems.

Parallel computing refers to the process of breaking down larger problems into smaller, independent, often similar parts that can be executed simultaneously by multiple processors communicating via shared memory, the results of which are combined upon completion as part of an overall algorithm. The primary goal of parallel computing is to increase available computation power for faster application processing and problem solving.

Memory in parallel systems can either be shared or distributed. In share computing, the work is divided between multiple threads or processes running on a single machine and these threads have access to common (shared) memory. In distributed computing, we have multiple autonomous computers which seem to the user as a single system. In distributed systems, there is no shared memory and computers communicate with each other through message passing. In distributed computing, a single task is divided among different computers. Parallel computing provides concurrency and saves time and money.

The recently concentrated on the use of the graphics processing unit (GPU) as a general-purpose processor. GPUs can potentially deliver substantially greater performance on a broad range of problems than their CPU counterparts, but effectively mapping problems to a parallel programming model with an immature programming environment is a significant and important research problem.

Henry R. Moncada