Nvidia · NVIDIA Blog
From Materials Simulation to Experimental Astronomy, New NVIDIA AI Software Unlocks Scientific Discoveries
Compiled by KHAO Editorial — aggregated from 1 source. See llms.txt for citation guidance.
★ Tier-1 Source
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.
Key facts
- In addition, Lila Sciences accelerates scientific discovery with the full NVIDIA stack, using NVIDIA Megatron-LM and NVIDIA Nemotron for training, including the Nemotron 3 Nano and Nemotron 3 Super
- 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
- Lila Sciences accelerated high-throughput materials screening by 50x using the ALCHEMI NIM microservice for BGR, identifying stable candidates that have higher chances of being synthesized
- NVIDIA DAQIRI, short for Data Acquisition for Integrated Real-time Instruments, is a high-performance networking library that streams data from fast detectors and sensors into NVIDIA software
Summary
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. 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. 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.