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 ...

Students will be able to analyze the computing and memory architecture of a super computing node and use OpenMP directives to improve vectorization of their programs. This module focuses on the key ...

Flow Computing is a pioneer in licensing on-die ultra-high-performance parallel computing solutions to CPU vendors of all architectures. And today the company is emerging from stealth with a funding ...

Concurrent and parallel systems form the bedrock of modern computational infrastructures, enabling vast improvements in processing speed, efficiency and scalability. By orchestrating multiple ...

Increasingly complex applications such as artificial intelligence require ever more powerful and power-hungry computers to run. Optical computing is a proposed solution to increase speed and power ...

This course focuses on developing and optimizing applications software on massively parallel graphics processing units (GPUs). Such processing units routinely come with hundreds to thousands of cores ...

In January we gave NVIDIA’s CUDA (Compute Unified Device Architecture) software tools that allows C programmers to use multiple high-performance GPU cards to perform massively parallel computations ...

The enormous growth in artificial intelligence (AI) and Internet of Things (IoT) is fueling a growing demand for high-efficiency computing to perform real-time analysis on massive amounts of data. In ...