The difference between a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit) primarily lies in their design and functionality. CPUs are designed to handle a wide range of computing ...

A Graphics Processing Unit or GPU in short is used as a co-processor along with the CPU for heavy tasks and computing. Generally, GPUs are used to accelerate or speed up memory-intensive tasks such as ...

One of the key trends for Nvidia right now is the growth of CUDA (Compute Unified Device Architecture), Nvidia's programming language for general-purpose GPU computing. In a keynote speech, Huang ...

In my previous article, I discussed the role of data management innovation in improving data center efficiency. I concluded with words of caution and optimism regarding the growing use of larger, ...

Nvidia Corporation's parallel computing platform, CUDA, is a key factor in the company's competitive advantage, with exponential growth showcased at COMPUTEX 2023, boasting over four million ...

In brief: Fujitsu is a Japanese multinational conglomerate that mostly sells personal and enterprise computing products, as well as x86 and mainframe servers. The company is active in the ...

GPU-based sorting algorithms have emerged as a crucial area of research due to their ability to harness the immense parallel processing power inherent in modern graphics processing units. By ...

Graphics processing units (GPUs) are traditionally designed to handle graphics computational tasks, such as image and video processing and rendering, 2D and 3D graphics, vectoring, and more.