Search results for “site:nvidia.com”
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551 results
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developer.nvidia.com
blog › spotlight-infleqtion-optimizes-portfolios-using-q-chop-and-nvidia-cuda-q-dynamics
Computing is an essential tool for the modern financial services industry. Profits are won and lost based on the speed and accuracy of algorithms guiding…
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developer.nvidia.com
blog › vulkan-1-3-broadens-cross-platform-functionality-with-developer-requested-features
The latest release of Vulkan 1.3 simplifies render passes and makes synchronization easier.
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developer.nvidia.com
blog › scale-realistic-robot-simulation-using-the-nvidia-nemo-agent-toolkit-for-physical-ai
Physical AI enables autonomous systems—think robots, self-driving cars, and smart spaces—to perceive, understand, and act intelligently in the real world.
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developer.nvidia.com
blog › constant-time-launch-for-straight-line-cuda-graphs-and-other-performance-enhancements
CUDA Graphs are a way to define and batch GPU operations as a graph rather than a sequence of stream launches. A CUDA Graph groups a set of CUDA kernels and…
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developer.nvidia.com
blog › accelerated-molecular-modeling-with-nvidia-cuequivariance-and-nvidia-nim-microservices
The emergence of models like AlphaFold2 has skyrocketed the demand for faster inference and training of molecular AI models. The need for speed comes with…
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developer.nvidia.com
blog › a-trio-of-new-nsight-tools-that-empowers-developers-to-fully-optimize-their-cpu-and-gpu-performance
Three big NVIDIA Nsight releases on the same day! NSight Systems is a brand new optimization tool; Nsight Visual Studio Edition 5.6 extends support to Volta…
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developer.nvidia.com
blog › accelerating-spark-3-0-and-xgboost-end-to-end-training-and-hyperparameter-tuning
At GTC Spring 2020, Adobe, Verizon Media, and Uber each discussed how they used Spark 3.0 with GPUs to accelerate and scale ML big data pre-processing, training…
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developer.nvidia.com
blog › nvidia-nsight-systems-2022-1-introduces-vulkan-1-3-and-linux-backtrace-sampling-and-profiling-improvements
The latest Nsight Systems 2022.1 release introduces several improvements aimed to enhance the profiling experience.
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developer.nvidia.com
blog › cooperative-groups
In efficient parallel algorithms, threads cooperate and share data to perform collective computations. To share data, the threads must synchronize.
d
developer.nvidia.com
blog › cuda-pro-tip-the-fast-way-to-query-device-properties
This post was updated in April 2025 to reflect performance on current hardware and software. CUDA applications often need to know the maximum available shared…
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