Today Nvidia announced that growing ranks of Python users can now take full advantage of GPU acceleration for HPC and Big Data analytics applications by using the CUDA parallel programming model. As a ...

AI developers use popular frameworks like TensorFlow, PyTorch, and JAX to work on their projects. All these frameworks, in turn, rely on Nvidia's CUDA AI toolkit and libraries for high-performance AI ...

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 ...

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 ...

Nvidia has been more than a hardware company for a long time. As its GPUs are broadly used to run machine learning workloads, machine learning has become a key priority for Nvidia. In its GTC event ...

In this video from the Nvidia booth at SC13, Travis Oliphant from Continuum Analytics presents: Applications of Programming the GPU Directly from Python Using NumbaPro. NumbaPro is a powerful compiler ...

Nvidia is the undisputed leader in professional GPU applications, and that doesn’t come down solely to making the best graphics cards. A big piece of the puzzle is Nvidia’s CUDA platform, which is the ...

GPU startup Oxmiq has emerged from stealth with plans to launch licensable GPU software and hardware IP following a $20 million seed raise. Founded two years ago by Raja Koduri, a GPU architect who ...

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 ...