Learn how to compare parallel and distributed computing based on problem characteristics, resource constraints, and performance goals. Find out which approach is best for your situation.

Parallel and distributed computing are two methods of harnessing multiple processors or computers to perform complex tasks faster and more efficiently. In this article, you will learn about the ...

The Parallel & Distributed Computing Lab (PDCL) conducts research at the intersection of high performance computing and big data processing. Our group works in the broad area of Parallel & Distributed ...

In recognition of this seismic shift in the computing landscape, the ACM/IEEE CS Curriculum 2013 (CS 2013) contains a new knowledge area named Parallel and Distributed Computing (PDC), with 15 hours ...

Scope The Parallel and Distributed Software section is dedicated to publishing research focused on advancing the field of parallel and distributed computing. Led by Dr. Basilio Fraguela from the ...

Summary form only given. Parallel computing for high performance scientific applications gained widespread adoption and deployment about two decades ago. Computer systems based on shared memory and ...

This has helped spur analysis of "beyond NP" problems. How to distribute your computation As if that weren't enough, Valiant has contributed to distributed and parallel computing.

The recent increase in interest on big data and data intensive computing makes it important for CS undergraduate students to receive education in Parallel and Distributed Computing. The increase in ...

Dr. Hoefler’s research aims at understanding the performance of parallel computing systems ranging from parallel computer architecture through parallel programming to parallel algorithms. He is also ...