See the latest HPC developer news and resources from @NVIDIA. Be sure to check out our NVIDIA Technical Blog for more.
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Joined November 2009
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Teams across Europe are adapting NVIDIA Earth-2 open models to answer weather and climate questions that matter to their work.
@AXA is studying cyclone risk across more than 1,000 simulated seasons. @TotalEnergies is testing short-term solar forecasts at two solar farms.
At the @OfficialUoM, researchers adapted Earth-2 CorrDiff to model U.K. air quality, training it on Isambard-AI and running it locally on DGX Spark.
More from GTC Berlin in the blog: blogs.nvidia.com/blog/europe…
NVIDIA HPC Developer retweeted
NVIDIA and @fzj_jsc ran a record 104-qubit simulation of fault-tolerant quantum computing on JUPITER, Europe’s biggest supercomputer, so researchers can refine designs before building hardware, shortening the path to viable quantum computers.
Read the release ⬇️ nvidianews.nvidia.com/news/n…
NVIDIA HPC Developer retweeted
NVIDIA 💚 PyTorch since day 0.
Cheers to building AI together, from early research to one of the fastest-growing deep learning frameworks.
50+ million monthly downloads with CUDA support.
Join us at @PyTorch Conference North America 2026 this week!
Space42 is estimating urban building heights from a single satellite radar image, even through clouds and in the dark.
The team used NVIDIA Earth-2’s CorrDiff and PhysicsNeMo to generate height maps and flag areas where predictions are less reliable.
Here’s how @space42ai built it: nvda.ws/4zqXLKl
CUDA-X libraries support everything from molecular simulation and climate modeling to AI. Here’s how they help the same GPU infrastructure do it all.
What does “fungible” mean for AI infrastructure? The flexibility to run different workloads: every type of AI, every phase of AI and even workloads that aren’t AI at all.
One platform, built for maximum “productivity”, “durable” years after deployment, and “fungible” for every model and workload.
Read the blog to learn more: nvda.ws/4hphGmQ
Pretty cool to see GPU research from 2009 recognized 17 years later. Congrats to Michael Garland and Nathan Bell on the SC26 Test of Time Award! 👏
🏆 What makes research stand the test of time?
Nathan Bell and Michael Garland’s influential SC09 work on GPU sparse computing is the recipient of the #SC26 Test of Time Award.
Seventeen years later, the questions they tackled still matter.
sc26.supercomputing.org/2026…
@NVIDIAAI
Turn local weather data into real-time operational decisions
With AI data assimilation tools in NVIDIA Earth-2, you can pipe proprietary and local sensor data directly into high-res forecasting models like CorrDiff, StormCast, and HealDA. No full model retraining required.
Read the full Earth2Studio code walkthrough: nvda.ws/4cE3NOQ
Introducing CUDA Rust!
CUDA Rust lets you write GPU kernels natively in Rust, not just launch them from it.
Two paths: cuda-oxide for SIMT kernels compiled to PTX, and cutile-rs for Tile-based programming on stable Rust. Both can catch aliasing errors at compile time.
Technical blog: nvda.ws/4hm1bHS
CUDA Toolkit 13.4 is now available.
It adds Windows on Arm support, early developer support for NVIDIA Rubin, and MPS V3 controls for partitioning GPU compute and memory across workloads, plus new CUDA Python APIs and CCCL performance improvements.
Here's all the technical details: nvda.ws/4A8VzbC
NVIDIA HPC Developer retweeted
NVIDIA × Fair Math Challenges are LIVE on FHERMA!
We're excited to collaborate with @NVIDIAHPCDev to bring GPU acceleration layer support to the FHE ecosystem using NVIDIA's cuPQC.
To kickstart this initiative, we're launching two new developer challenges with GPU compute:
- Polynomial Multiplication: Build high-performance polynomial multiplication on cuPQC's bigint backend. (Great entry point for GPU/CUDA devs!)
- Key Switching in CKKS: Optimize one of FHE's biggest bottlenecks using GPU-native arithmetic.
Whether you're an FHE researcher or a CUDA/GPU dev, you can help build open-source infrastructure that projects worldwide will use.
Join the challenges: fherma.io
#FHE #Cryptography #CUDA #GPU #cuPQC #NVIDIA #OpenSource
Join us for a three-part webinar series on how AI is being used to study proteins, forecast climate risk and simulate new materials.
NVIDIA speakers will be joined by researchers from @emblebi, @OfficialUoM and @EPFL to share how teams are working with NVIDIA BioNeMo, Earth-2 and NVIDIA ALCHEMI.
Sept 23 | Sept 30 | Oct 6
Available in multiple time zones. Register below.
NVIDIA HPC Developer retweeted
SP1 is integrating the NVIDIA cuPQC cryptography library.
cuPQC powers core operations in SP1's GPU prover, making proving performant across @NVIDIA accelerated computing and expanding the range of GPUs that can prove efficiently on the Succinct Prover Network.
NVIDIA cuPQC v0.6 is here! Introducing cuPQC-BigInt and cuPQC-NTT, GPU-accelerated math libraries for building cryptographic systems.
Dive into big integer arithmetic (modular multiplication, inversion, exponentiation, and reduction) and number theoretic transforms for zero-knowledge proofs, fully homomorphic encryption, RSA, elliptic curve, and isogeny-based cryptography.
Read the blog: nvidia.github.io/cuPQC/relea…
Get started: developer.nvidia.com/cupqc
NVIDIA HPC Developer retweeted
10 million downloads for NVIDIA Warp 🎉
Warp started with a simple idea: you shouldn’t have to leave Python to get real GPU performance for physics and simulation.
Since then, developers have used it to accelerate work across physics simulation, computational engineering, geometry processing and robotics.
Thank you to everyone who downloaded it, broke it, filed an issue or sent a PR. On to the next 10M!
NVIDIA cuPhoton is now available on GitHub 🔭
Working with data from telescopes, X-ray sources and laser experiments often means spending months or years just getting the data ready to use.
cuPhoton moves that pipeline onto the GPU to speed up that process, from ingest and cleaning to analysis, bringing it down to hours or minutes.
Get started: github.com/nvidia/cuPhoton
RT @NVIDIARobotics: A milestone for the Holoscan community. 🎉
Over a million developers and researchers are using the Holoscan SDK to adva…
NVIDIA nvmath-python v1.0 is now GA.
Get the raw performance of CUDA-X math libraries (cuFFT, cuBLAS, cuSPARSE) directly inside your NumPy, CuPy, and PyTorch-based code.
🔹 Scale CPU ➡️ Single-GPU ➡️ Multi-node
🔹 Stateful APIs for reusable planning & autotuning
🔹 Fast JIT kernel fusion with numba-cuda
Details: developer.nvidia.com/blog/ru…
The CUDA MCP Server is available now.
This NVIDIA hosted MCP server gives your agent a search tool over indexed, current CUDA documentation and code examples, curated by NVIDIA engineers.
Ask a CUDA question, the agent searches the corpus and answers in-line, without leaving your agent of choice. Compatible with Claude Code, Codex, Cursor, Antigravity, or any MCP-compatible agent.
One line to connect 👇developer.nvidia.com/nsight-…
