Nvidia earlier this month unveiled CUDA Tile, a programming model designed to make it easier to write and manage programs for GPUs across large datasets, part of what the chip giant claimed was its ...

Nvidia has updated its CUDA software platform, adding a programming model designed to simplify GPU management. Added in what the chip giant claims is its “biggest evolution” since its debut back in ...

The CUDA toolkit is now packaged with Rocky Linux, SUSE Linux, and Ubuntu. This will make life easier for AI developers on these Linux distros. It will also speed up AI development and deployments on ...

Git isn’t hard to learn. Moreover, with a Git GUI such as Atlassian’s Sourcetree, and a SaaS code repository such as Bitbucket, mastery of the industry’s most powerful version control tools is within ...

The big picture: Nvidia has long been developing an AI PC processor that combines Arm CPU cores with Blackwell GPU architecture. The chip has now appeared on the Geekbench database for at least the ...

A project is trying to cut the cost of making machine learning applications for Nvidia hardware, by developing on an Apple Silicon Mac and exporting it to CUDA. Machine learning is costly to enter, in ...

NVIDIA introduces cuda.cccl, bridging the gap for Python developers by providing essential building blocks for CUDA kernel fusion, enhancing performance across GPU architectures. NVIDIA has unveiled a ...

Why it matters: Nvidia introduced CUDA in 2006 as a proprietary API and software layer that eventually became the key to unlocking the immense parallel computing power of GPUs. CUDA plays a major role ...

Introduced a couple of weeks before the Ford Mustang, the Plymouth Barracuda was born as a pony and morphed into a fully-fledged muscle rig by the end of the decade. However, it didn't get the iconic ...

CUDA enables faster AI processing by allowing simultaneous calculations, giving Nvidia a market lead. Nvidia's CUDA platform is the foundation of many GPU-accelerated applications, attracting ...