Data parallelism is an approach towards parallel processing that depends on being able to break up data between multiple compute units (which could be cores in a processor, processors in a computer, ...

In the task-parallel model represented by OpenMP, the user specifies the distribution of iterations among processors and then the data travels to the computations. In data-parallel programming, the ...

As hardware designers turn toward multicore processors to improve computing power, software programmers must find new programming strategies that harness the power of parallel computing. One technique ...

Programming languages are a dime a dozen; throw a rock in any direction and you’ll hit one. Question is … can you use any of them to program data-centric applications that are deployable across CPUs, ...

Multi-core processors theoretically can run many threads of code in parallel, but some categories of operation currently bog down attempts to raise overall performance by parallelizing computing. Is ...

When I wrote about password guessing using GPUs last week, I mentioned that password guessing is an embarrassingly parallel problem, right up there with 3-D rendering, face recognition, Monte Carlo ...

Huge volumes of data need near-supercomputer power to process and analyze it all. You can get there with the .NET Task Parallel Library. As Web and mobile applications face the challenge of quickly ...

This application note presents the process of converting a serial output into parallel output using common serial-to-parallel register integrated circuits. The document also discussed the CS556x/7x/8x ...

The MAX3950 is designed to convert 10-Gbps serial data to 16-bit-wide, 622-Mbps parallel data. Its ability to handle FEC data rates make the MAX3950 ideal for a variety of applications in SDH/SONET ...

Language Integrated Query, also known as LINQ, is a query execution pipeline that adds query capabilities to languages targeted at the managed environment of .Net. Parallel LINQ, or PLINQ, is a query ...