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NVIDIAs CUDA-Q platform enables significant resource reduction in quantum clustering algorithms, making them more feasible for near-term quantum computing applications. (Read More)
In stark contrast to mainstream competitors, Procreate has said it would not use generative AI features in its products to protect artists.
NVIDIA's new cuda-checkpoint utility, combined with CRIU, allows transparent checkpointing and restoring of CUDA applications on Linux. (Read More)
NVIDIA CUDA Toolkit 12.4 introduces the nvFatbin library, streamlining the creation of fatbins at runtime and enhancing GPU code compatibility. (Read More)
NVIDIA introduces GPU-accelerated RDMA with DOCA GPUNetIO, boosting data transfer speeds. (Read More)
Quantum mechanics is enhancing drug discovery through the use of QUELO-G and CUDA graphs. (Read More)
Leading semiconductor companies are adopting NVIDIA's Blackwell and CUDA-X platforms to accelerate manufacturing processes, improve lithography, and enhance simulation capabilities. (Read More)
Explore how NVIDIA CUDA-X and Coiled streamline cloud-based data science, offering significant computational speedups and simplifying infrastructure management for data scientists. (Read More)
NVIDIA unveils cuEmbed, a CUDA library that significantly enhances embedding lookups on GPUs, promising improved performance for recommendation systems and other applications. (Read More)
NVIDIA's CUDA-Q platform enhances quantum computing research, offering improved performance and scalability for hybrid quantum supercomputers, according to NVIDIA Developer Blog. (Read More)
NVIDIA's CUDA libraries are revolutionizing cybersecurity by integrating AI, offering enhanced threat detection, real-time response, and scalability to tackle modern cyber threats. (Read More)
Explore PTX, the assembly language for NVIDIA CUDA GPUs, its role in enabling forward compatibility, and its significance in the GPU computing landscape. (Read More)
Learn how the new --fdevice-time-trace feature in CUDA 12.8 improves compile times for CUDA C++ developers, boosting productivity and efficiency. (Read More)
NVIDIA collaborates with AWS to integrate CUDA-Q with Amazon Braket, enhancing accessibility and efficiency in quantum computing through hybrid applications and streamlined QPU access. (Read More)
NVIDIA collaborates with Google Quantum AI to advance quantum computing design using NVIDIA's CUDA-Q platform, enabling large-scale simulations to tackle noise challenges in quantum hardware. (Read More)
NVIDIA introduces CUDA-QX, a set of libraries aimed at enhancing quantum supercomputing capabilities by integrating AI tools with quantum processing units (QPUs). (Read More)
Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiski. (Read More)
NVIDIA integrates CUDA-X with Polars, significantly boosting data processing speeds. The update promises up to 13x faster performance, enhancing efficiency for data scientists and engineers. (Read More)
Numbast introduces an automated pipeline to convert CUDA C++ APIs into Numba bindings, enhancing Python developers' access to CUDA's performance. (Read More)
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