The Fenghua No. 3 is based on the open-source RISC-V architecture, with inputs from the OpenCore Institute's Nanhu V3 project. The new design is expected to ...
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 ...
The RTX Pro 4000 SFF and RTX Pro 2000 deliver Blackwell-based AI acceleration, advanced ray tracing, and improved energy efficiency. Nvidia announced two new professional GPUs, the RTX Pro 4000 Small ...
NVIDIA's CUDA Toolkit 13.0 introduces innovative features like tile-based programming and unified Arm platform support, enhancing developer productivity and GPU performance. The latest iteration of ...
TL;DR: AMD will launch the Radeon AI PRO R9700 workstation GPU on July 23, featuring 32GB GDDR6 memory and RDNA 4 architecture. Optimized for AI workloads, it offers up to 496% faster inference than ...
Apple’s MLX machine learning framework, originally designed for Apple Silicon, is getting a CUDA backend, which is a pretty big deal. Here’s why. The work is being led by developer @zcbenz on GitHub ...
In several cases, TensorFlow fails to detect or utilize available NVIDIA GPUs, even when the system is correctly configured with the appropriate hardware, drivers, CUDA, and cuDNN versions. This issue ...
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 ...
Delve into the potential of handwritten PTX code for enhancing GPU performance in CUDA applications, as outlined by NVIDIA experts. As the demand for accelerated computing continues to rise within ...
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