CUDA GPUs - Compute Capability - NVIDIA Developer
WEBExplore your GPU compute capability and learn more about CUDA-enabled desktops, notebooks, workstations, and supercomputers.
Nsight Compute - NVIDIA Developer
WEBNVIDIA Nsight™ Compute is an interactive profiler for CUDA® and NVIDIA OptiX™ that provides detailed performance metrics and API debugging via a user interface and command-line tool.
CUDA Toolkit - Free Tools and Training | NVIDIA Developer
WEBUsing built-in capabilities for distributing computations across multi-GPU configurations, you can develop applications that scale from single-GPU workstations to cloud installations with thousands of GPUs.
CUDA C++ Programming Guide - NVIDIA Documentation Hub
WEBIn November 2006, NVIDIA ® introduced CUDA ®, a general purpose parallel computing platform and programming model that leverages the parallel compute engine in NVIDIA GPUs to solve many complex computational problems in a more efficient way than on a …
High Performance Computing Products and Solutions - NVIDIA
WEBHigh performance computing (HPC) with the help of GPU is helping large-scale application programs run efficiently. NVIDIA provides a range of HPC solutions that is helping organizations to reduce cost.
What Is CUDA? - NVIDIA Blog
WEBSep 10, 2012 · CUDA is a parallel computing platform and programming model created by NVIDIA. With more than 20 million downloads to date, CUDA helps developers speed up their applications by harnessing the power of GPU accelerators.
CUDA Zone - Library of Resources - NVIDIA Developer
WEBCUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
NVIDIA Ampere Architecture In-Depth | NVIDIA Technical Blog
WEBMay 14, 2020 · The new streaming multiprocessor (SM) in the NVIDIA Ampere architecture-based A100 Tensor Core GPU significantly increases performance, builds upon features introduced in both the Volta and Turing SM architectures, and adds many new capabilities.
Advanced Strategies for High-Performance GPU Programming with NVIDIA …
WEBSep 11, 2024 · GPU architecture: Key differences between CPU and GPU approaches, with a focus on the NVIDIA Hopper H100 GPU and its implications for parallel processing. Parallelism: Distinction and effective use of data and task parallelism in CUDA programming. CUDA execution model: Understanding how CUDA manages threads and blocks to maximize performance.
CUDA Toolkit Documentation 12.6 Update 1
WEBThe NVIDIA® CUDA® Toolkit provides a development environment for creating high performance GPU-accelerated applications. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers.
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