Tensor Cores are specially developed hardware units inside of an Nvidia graphics card that enable mixed-precision computing ...

The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the ...

If you want a CPU that has the floating point performance of a GPU, all you have to do is wait six or so years and the CPU ...

The AI enigma. The direction in which some AEC software developers are heading raises important questions about workstation ...

NVIDIA is the market leader in AI-focused GPUs, with the Tesla (now A100 and H100) and RTX series optimised for machine ...

Just when you thought the pace of change of AI models couldn’t get any faster, it accelerates yet again. In the popular news media, the introduction of DeepSeek in January 2025 created a moment that ...

As of September 2024, AMD had $4.5 billion in cash and cash equivalents against total debt of $1.7 billion. AMD took on debt to acquire Xilinx, but Xilinx generates healthy cash flow, and now that AMD ...

Ever since NVIDIA ventured into ray tracing with the ... This expanded transistor budget translates to a greater number of CUDA cores, RT Cores, Tensor Cores, and other specialised units, all ...

The GPU used in this paper is NVIDIA RTX3090. The development and testing are carried out in the Python3.9 environment, and the integrated development tool is Pycharm. We use PyTorch v1.12.0 as the ...

With the retirement of 32-bit CUDA application support on RTX 50 series GPUs, PhysX is now end-of-life starting with ...

The change makes some classic PC games run poorly even on modern hardware due to a lack of GPU-accelerated physics.