Concurrent programming is a way of designing and writing programs that can execute multiple tasks or processes at the same time, without waiting for one to finish before starting another.

Parallel programming is a powerful way to speed up your applications, harness the power of multiple processors, and solve complex problems. However, it also comes with its own challenges, such as ...

Programming languages are evolving to bring the software closer to hardware. As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example ...

CPU-GPU based cluster computing in today's modern world encompasses the domain of complex and high-intensity computation. To exploit the efficient resource utilization of a cluster, traditional ...

One of the best features of using FPGAs for a design is the inherent parallelism. Sure, you can write software to take advantage of multiple CPUs. But with an FPGA you can enjoy massive parallelism… ...

CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on its own GPUs (graphics processing units).CUDA enables developers to speed up compute ...

The new pseudo-code is implemented as a kernel. A kernel is a function that executes on several GPU cores at the same time. Kernels are launched by a host program controlled from the regular CPU that ...

In a lot of our programs, we run only one additional thing at a time and wait for it to complete; this is usually referred to with the more generic term "asynchronous programming." Parallel ...

A critical part of any parallel program is scalable memory allocation, which includes use of new as well as explicit calls to malloc, calloc, or realloc.Options include TBBmalloc (Intel Threading ...