We explain what is GPU Computing, advantages of GPU and how it is used? How is GPU (Graphics Processing Unit) different from CPU.

NCAR was able to speed up the Weather Research & Forecasting Model by 20% by parallelizing one component of the model with NVIDIA CUDA software and a many-core GPU Computing Processor called Tesla.

Parallel computing is the fundamental concept that, along with advanced semiconductors, has ushered in the generative-AI boom.

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

What is CUDA programming, exactly? According to Nvidia, CUDA is a parallel computing platform and programming model that enables developers to write code and build applications on Nvidia's GPUs.

Unlike CPUs, GPUs contain thousands of small cores that can process multiple tasks simultaneously, making them highly efficient for parallel computing.

Graphics Processing Units (GPUs) are now pivotal in high-performance computing, offering substantial computational throughput through inherently parallel architectures. Modern research in GPU ...

Nvidia has unveiled a new compiler source code to add new languages to its parallel programming and boost the adoption of GPUs.