The main part of parallel computing
is to exploit or to create the concurrency in the program, share it to the other computers/processors using the parallel application programming interface (API), such as the MPI, so that other computers can act upon the data (Peterson, Arbenz 2004).
allows a computer code to use the resources of multiple computers simultaneously.
Toolbox enables engineers and scientists in MATLAB to access all available computing resources available to them, from multicores and GPUs on local desktops to clusters and grids, with minimal programming effort.
Today tens of thousands of developers, scientists and researchers are writing CUDA-based parallel computing
applications in areas such as seismic data analysis, financial modeling, medical imaging and weather forecasting, to name a few.
As hardware systems become more powerful, MATLAB users are increasingly presented with data-intensive problems that involve highly complex data sets," said Silvina Grad-Freilich, manager of parallel computing
and application deployment marketing at The MathWorks.
NVIDIA's CUDA is a general purpose parallel computing
architecture that takes advantage of the parallel compute engine in NVIDIA GPUs to solve many computational problems in a fraction of the time required on a general purpose CPU.
International Conference on Parallel Computing
in Electrical Engineering (2006: Bialystok, Poland)
AMAX's parallel computing
solutions utilize NVIDIA's latest Tesla10 series GPU architecture.
research areas include accelerating the mobile web browser and runtime environments; increasing mobile device performance while lowering power consumption in both active and idle modes; and achieving seamless ubiquitous wireless connectivity and cross-domain interoperability.
for bioinformatics and computational biology; models, enabling technologies, and case studies.
The MathWorks today announced that Argonne National Laboratory significantly reduced the simulation time of models built with the Powertrain System Analysis Toolkit (PSAT) by using Parallel Computing
Toolbox and MATLAB Distributed Computing Server from The MathWorks.
NVIDIA's Revolutionary CUDA Parallel Computing
Architecture to Support OpenCL