Japan is once again building a landmark high-performance computing system — not simply by chasing speed, but by rethinking how technology can best serve the nation’s most urgent scientific needs. At the FugakuNEXT International Initiative Launch Ceremony held in Tokyo on Aug. 22, leaders from RIKEN, Japan’s top research institute, announced the start of an
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NVIDIA HPC SDK v25.7 delivers a significant leap forward for developers working on high-performance computing (HPC) applications with GPU acceleration. This…
NVIDIA HPC SDK v25.7 delivers a significant leap forward for developers working on high-performance computing (HPC) applications with GPU acceleration. This release marks nearly two years of ongoing development focused on unified memory programming, resulting in a complete toolset that automates data movement between CPU and GPU. By eliminating much of the manual data management traditionally…
From AI assistants doing deep research to autonomous vehicles making split-second navigation decisions, AI adoption is exploding across industries. Behind every one of those interactions is inference — the stage after training where an AI model processes inputs and produces outputs in real time. Today’s most advanced AI reasoning models — capable of multistep logic
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Gearing Up for the Gigawatt Data Center Age
Across the globe, AI factories are rising — massive new data centers built not to serve up web pages or email, but to train and deploy intelligence itself. Internet giants have invested billions in cloud-scale AI infrastructure for their customers. Companies are racing to build AI foundries that will spawn the next generation of products
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As datasets get bigger, ensuring data security and integrity becomes increasingly important. Cryptographic techniques, such as inclusion proofs, data-integrity…
As datasets get bigger, ensuring data security and integrity becomes increasingly important. Cryptographic techniques, such as inclusion proofs, data-integrity checks, consistency validation, and digital signatures, are essential for addressing these challenges and protecting critical workloads. That’s where cuPQC SDK v0.4 comes in. By offering powerful device functions capable of fusing…
The exponential growth in AI model complexity has driven parameter counts from millions to trillions, requiring unprecedented computational resources that…
The exponential growth in AI model complexity has driven parameter counts from millions to trillions, requiring unprecedented computational resources that require clusters of GPUs to accommodate. The adoption of mixture-of-experts (MoE) architectures and AI reasoning with test-time scaling increases compute demands even more. To efficiently deploy inference, AI systems have evolved toward large…
Get a glimpse into the future of gaming. The NVIDIA Blackwell RTX architecture is coming to GeForce NOW in September, marking the service’s biggest upgrade yet. Turn any device into a powerhouse gaming rig with GeForce RTX 5080-class performance, next-generation AI features and a major leap forward in stunning cinematic visuals — all without raising
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The initial release of NVIDIA NeMo-RL included training support through PyTorch DTensor (otherwise known as FSDP2). This backend enables native integration with…
The initial release of NVIDIA NeMo-RL included training support through PyTorch DTensor (otherwise known as FSDP2). This backend enables native integration with the HuggingFace ecosystem, quick experimentation, and scaling with PyTorch native parallelisms (FSDP2, tensor parallel, sequence parallel, and context parallel). However, when model sizes approach hundreds of billions of parameters…
Editor’s note: This blog is a part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Investments in industrial AI and physical AI are driving increased demand for digital twins across industries. These physically accurate, virtual replicas
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