Researchers can leverage Compal GPU Annealer for large-scale quantum-inspired algorithm computations, and utilize CUDA-Q ...

The CUDA Toolkit includes libraries, debugging and optimization tools, a compiler, documentation, and a runtime library to deploy your applications. It has components that support deep learning ...

CUDA 12.x series (and before) will still allow application development for these GPUs. The deprecation targets offline compilation and library support. Essentially, future CUDA compilers (nvcc ...

Tenstorrent is part of a group of companies trying to build alternatives to Nvidia GPUs and the company’s CUDA library. It competes with Axelera, Etched, Groq and others. Koyeb was founded by ...

Programming GPUs directly in CUDA, according to Tillet and the team ... kernels that match the performance of cuBLAS," an Nvidia library that implements the open-source Basic Linear Algebra ...

After some industry discussions, Kumar observed that due to the CUDA library’s robust presence and the convenience of accessing pre-made models within it, a user would only consider switching to ...

Nvidia has released a new mathematical Python library specialized for Cuda-X. It offers direct, Python-like access to the mathematical core operations of Cuda-X without having to use additional C ...

The guide takes a closer look at the open-source library PyTorch which allows a Python developer to quickly get up-to-speed with the features of CUDA that make it so appealing to researchers and ...

cuTENSOR is a high-performance CUDA library for tensor primitives and its features include Extensive mixed-precision support for FP64 inputs with FP32 compute, FP32 inputs with FP16, BF16 ...