Original article excerpt
Server-side extracted preview paragraphs from the original source.
NVIDIA CUDA-X libraries, microservices and reference code accelerate AI for science.
At the ISC conference running in Hamburg this week, NVIDIA is introducing new software that speeds AI for science, from chemistry and materials discovery to the search for dark matter.
The NVIDIA DAQIRI library and new NVIDIA ALCHEMI NIM microservices — as well as the NVIDIA cuPhoton reference code, coming soon — turn work that once took hours or days on CPUs into real-time, GPU-accelerated pipelines.
They’re a part of NVIDIA CUDA-X, a collection of tools and libraries that deliver dramatically higher performance across application domains, including AI and high-performance computing.
These performance gains are large and have real impact. Across disciplines, scientists are using AI and accelerated computing to generate data and insights with instruments and surveys faster than ever.
For example, running on NVIDIA GB200 NVL72 systems, cuPhoton speeds loading, reading, processing and analysis of FITS data — the standard astronomical file format — from observatories and telescopes. In early access, cuPhoton accelerated loading and reading of FITS images collected by the Rubin Observatory’s Legacy Survey of Space and Time (LSST) by 14,900x. It also enabled up to 8,400x faster signal processing and analysis using 32 NVIDIA Grace Blackwell superchips.
Ultimately, this means faster insights from the LSST camera — the largest digital camera ever built — which captures images of billions of far-away galaxies, as well as closer, faint objects that don’t reflect much light.