NVIDIA cuQuantum is an SDK of optimized libraries and tools that accelerate quantum computing emulations at both the circuit and device level by orders of…
NVIDIA cuQuantum is an SDK of optimized libraries and tools that accelerate quantum computing emulations at both the circuit and device level by orders of magnitude. With NVIDIA Tensor Core GPUs, developers can speed up quantum computer simulations based on quantum dynamics, state vectors, and tensor network methods by orders of magnitude. In many cases, this provides researchers with simulations…

As AI evolves to planning, research, and reasoning with agentic AI, workflows are becoming increasingly complex. To deploy agentic AI applications efficiently,…
This is the third post in the large language model latency-throughput benchmarking series, which aims to instruct developers on how to benchmark LLM inference…
RAPIDS, a suite of NVIDIA CUDA-X libraries for Python data science, released version 25.06, introducing exciting new features. These include a Polars GPU…
AI agents powered by large language models are transforming enterprise workflows, but high inference costs and latency can limit their scalability and user…
As accelerated computing continues to drive application performance in all areas of AI and scientific computing, there’s a renewed interest in GPU optimization…
As part of continued efforts to ensure NVIDIA Omniverse is a developer-first platform, NVIDIA will be deprecating the Omniverse Launcher on Oct. 1. Doing so…
FLUX.1 Kontext, the recently released model from Black Forest Labs, is a fascinating addition to the repertoire of community image generation models. The open…