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[NVIDIA CUDA/ ]cuda-gdb-11-1 11.1.105-1 [NVIDIA CUDA/ ]cuda-gdb-11-2 11.2.152-1 [NVIDIA CUDA/ ]cuda-gdb-11-3 11.3.109-1 [NVIDIA CUDA/ ]cuda-gdb-11-4 11.4.120-1 [NVIDIA CUDA/ ]cuda-gdb-11-5 11.5.114-1 [NVIDIA CUDA/ ]cuda-gdb-11-6 11.6.124-1 [NVIDIA CUDA/ ]cuda-gdb-11-7 11.7.91-1 [NVIDIA CUDA/ ]cuda-gdb-src-10-0 10.0.130-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-10-1 10.1.243-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-10-2 10.2.89-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-11-0 11.0.221-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-11-1 11.1.105-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-11-2 11.2.152-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-11-3 11.3.109-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-11-4 11.4.120-1 [NVIDIA CUDA/ ]└── Contains the source code for cuda-gdbcuda-gdb-src-11-5 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]cuda-memcheck-11-7 11.7.91-1 [NVIDIA CUDA/ ]cuda-minimal-build-10-0 10.0.130-1 [NVIDIA CUDA/ ]cuda-minimal-build-10-1 10.1.243-1 [NVIDIA CUDA/ ]cuda-minimal-build-10-2 10.2.89-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-0 11.0.3-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-1 11.1.1-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-2 11.2.2-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-3 11.3.1-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-4 11.4.4-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-5 11.5.2-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-6 11.6.2-1 [NVIDIA CUDA/ ]cuda-minimal-build-11-7 11.7.1-1 [NVIDIA CUDA/ ]cuda-misc-headers-10-0 10.0.130-1 [NVIDIA CUDA/ ]cuda-misc-headers-10-1 10.1.243-1 [NVIDIA CUDA/ ]cuda-misc-headers-10-2 10.2.89-1 [NVIDIA CUDA/ ]cuda-npp-10-0 10.0.130-1 [NVIDIA CUDA/ ]cuda-npp-10-1 10.1.243-1 [NVIDIA CUDA/ ]cuda-npp-10-2 10.2.89-1 [NVIDIA CUDA/ ]cuda-npp-dev-10-0 10.0.130-1 [NVIDIA CUDA/ ]cuda-npp-dev-10-1 10.1.243-1 [NVIDIA CUDA/ ]cuda-npp-dev-10-2 10.2.89-1 [NVIDIA CUDA/ ]cuda-nsight-10-0 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]cuda-nsight-compute-11-7 11.7.1-1 [NVIDIA CUDA/ ]cuda-nsight-systems-10-1 10.1.243-1 [NVIDIA CUDA/ ]cuda-nsight-systems-10-2 10.2.89-1 [NVIDIA CUDA/ ]cuda-nsight-systems-11-0 11.0.3-1 [NVIDIA CUDA/ ]cuda-nsight-systems-11-1 11.1.1-1 [NVIDIA CUDA/ ]cuda-nsight-systems-11-2 11.2.2-1 [NVIDIA CUDA/ ]cuda-nsight-systems-11-3 11.3.1-1 [NVIDIA CUDA/ ]cuda-nsight-systems-11-4 11.4.4-1 [NVIDIA CUDA/ ]cuda-nsight-systems-11-5 11.5.2-1 [NVIDIA CUDA/

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NVIDIA Nsight Compute is an interactive kernel profiler for CUDA applications. It provides detailed performance metrics and API debugging via a user interface and command-line tool. Browse NVIDIA Nsight Deep Learning Designer is a tool with an integrated development environment that helps developers efficiently design and develop deep neural networks for in-app inference. Browse NVIDIA Nsight Eclipse Edition is a unified CPU plus GPU integrated development environment (IDE) for developing CUDA® applications on Linux and Mac OS X for the x86, POWER and ARM platforms. Browse NVIDIA Nsight Graphics is a standalone developer tool that enables you to debug, profile, and export frames built with Direct3D, Vulkan, OpenGL, OpenVR, and the Oculus SDK. Browse NVIDIA Nsight Integration is a Visual Studio extension that enables you to access the power of Nsight Compute, Nsight Graphics, and Nsight Systems from within Visual Studio. Browse The NVIDIA Nsight Perf SDK is a toolbox for collecting and analyzing GPU performance data, directly from application code. Browse NVIDIA Nsight Systems is a system-wide performance analysis tool designed to visualize an application’s algorithms, help you identify the largest opportunities to optimize, and tune to scale efficiently across any quantity or size of CPUs and GPUs; from a large server to our smallest SoC. Browse NVIDIA Nsight Visual Studio Code Edition (VSCE) is an application development environment for heterogeneous platforms that brings CUDA development for GPUs into Microsoft Visual Studio Code. Browse NVIDIA Nsight Visual Studio Edition (VSE) is an application development environment for heterogeneous platforms that brings GPU computing into Microsoft Visual Studio. Browse NVIDIA® Nsight™ Aftermath is a library that integrates into a D3D12 or Vulkan game’s crash reporter to generate GPU “mini-dumps” when an exception or TDR occurs, exposing pipeline information to resolve an unexpected crash. Browse

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Product and may result in additional or different conditions and/or requirements beyond those contained in this document. NVIDIA accepts no liability related to any default, damage, costs, or problem which may be based on or attributable to: (i) the use of the NVIDIA product in any manner that is contrary to this document or (ii) customer product designs. No license, either expressed or implied, is granted under any NVIDIA patent right, copyright, or other NVIDIA intellectual property right under this document. Information published by NVIDIA regarding third-party products or services does not constitute a license from NVIDIA to use such products or services or a warranty or endorsement thereof. Use of such information may require a license from a third party under the patents or other intellectual property rights of the third party, or a license from NVIDIA under the patents or other intellectual property rights of NVIDIA. Reproduction of information in this document is permissible only if approved in advance by NVIDIA in writing, reproduced without alteration and in full compliance with all applicable export laws and regulations, and accompanied by all associated conditions, limitations, and notices. THIS DOCUMENT AND ALL NVIDIA DESIGN SPECIFICATIONS, REFERENCE BOARDS, FILES, DRAWINGS, DIAGNOSTICS, LISTS, AND OTHER DOCUMENTS (TOGETHER AND SEPARATELY, “MATERIALS”) ARE BEING PROVIDED “AS IS.” NVIDIA MAKES NO WARRANTIES, EXPRESSED, IMPLIED, STATUTORY, OR OTHERWISE WITH RESPECT TO THE MATERIALS, AND EXPRESSLY DISCLAIMS ALL IMPLIED WARRANTIES OF NONINFRINGEMENT, MERCHANTABILITY, AND FITNESS FOR A PARTICULAR PURPOSE. TO THE EXTENT NOT PROHIBITED BY LAW, IN NO EVENT WILL NVIDIA BE LIABLE FOR ANY DAMAGES, INCLUDING WITHOUT LIMITATION ANY DIRECT, INDIRECT, SPECIAL, INCIDENTAL, PUNITIVE, OR CONSEQUENTIAL DAMAGES, HOWEVER CAUSED AND REGARDLESS OF THE THEORY OF LIABILITY, ARISING OUT OF ANY USE OF THIS DOCUMENT, EVEN IF NVIDIA HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. Notwithstanding any damages that customer might incur for any reason whatsoever, NVIDIA’s aggregate and cumulative liability towards customer for the products described herein shall be limited in accordance with the Terms of Sale for the product. HDMI HDMI, the HDMI logo, and High-Definition Multimedia Interface are trademarks or registered trademarks of HDMI Licensing LLC. OpenCL OpenCL is a trademark of Apple Inc. used under license to the Khronos Group Inc. Trademarks NVIDIA, the NVIDIA logo, and cuBLAS, CUDA, DALI, DGX, DGX-1, DGX-2, DGX Station, DLProf, Jetson, Kepler, Maxwell, NCCL, Nsight Compute, Nsight Systems, NvCaffe, PerfWorks, Pascal, SDK Manager, Tegra, TensorRT,. parallel nsight下载 nvidia nsight下载 nvidia parallel nsight visual studio nvidia parallel nsight install nvidia parallel nsight monitor download eutron smartkey parallel driver Free nvidia parallel nsight install download software at UpdateStar - nvidia parallel nsight install at UpdateStar N. More NVIDIA Parallel Nsight for Visual Studio, Jul. NVIDIA Corporation -

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Access to resources, please visit the main Nsight™ Compute page.NVIDIA® Nsight™ Compute 2023.1 is available for download under the NVIDIA Registered Developer Program. Download 2023.1.2 Download 2023.1.1 Download 2023.1.0 Documentation PRODUCT INFO Supported Platforms Windows Linux Mac DRIVE OS Host Windows x86_64[1] Linux x86_64[1] Linux aarch64 sbsa[1] Linux aarch64 (L4T)[2] MacOS[1] - Target Windows x86_64[1] Linux x86_64[1] Linux PowerPC[1] Linux aarch64 sbsa[1] Linux aarch64 (L4T)[2] - DRIVE OS QNX aarch64[2][3] DRIVE OS Linux aarch64[2][3] Host platforms support the Nsight Compute UI for viewing reports, interactive profiling and remote connections. Applications are profiled on target platforms, which also support the Nsight Compute command line interface. Supported NVIDIA GPU architectures Ada: AD10x Ampere: A100 with Multi-Instance GPU, GA10x Hopper: H100 with Multi-Instance GPU Turing: TU1xx Volta: GV100[1], GV10B[2] [1] available in this download and the CUDA Desktop Toolkit [2] available in the Embedded or Drive toolkits only [3] Only the command line interface (CLI) is provided for these platforms. There is no Nsight Compute GUI application for these platforms Recommended Drivers NVIDIA Windows Driver - 531.14 or newer NVIDIA Linux Driver Linux - 530.30.02 or newer We recommend using drivers provided with the most recent CUDA Toolkit production release or a newer version. Older driver versions are also supported. References Overview (features) Getting Started (download, platforms, requirements) Documentation Downloads Revision History Videos News & Blogs Nsight Compute forum

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Is a software library that provides Computer Vision / Image Processing algorithms implemented on PVA1 (Programmable Vision Accelerator), GPU and CPU OpenCV is a leading open source library for computer vision, image processing and machine learning. VisionWorks2 is a software development package for Computer Vision (CV) and image processing. JetPack 4.6.1 includes VPI 1.2 Production quality support for Python bindings Multi-Stream support in Python bindings to allow creation of multiple streams to parallelize operations Support for calling Python scripts in a VPI Stream New algorithms Image Erode\Dilate algorithm on CPU and GPU backends Image Min\Max location algorithm on CPU and GPU backends JetPack 4.6.1 includes OpenCV 4.1.1 Jetpack 4.6.1 includes VisionWorks 1.6 1PVA is available only on Jetson AGX Xavier series and Jetson Xavier NX 2VisionWorks will no longer be included after JetPack 4.6.x. Developers should instead use the VPI library for computer vision and image processing. Refer to the announcement here. Developer Tools CUDA Toolkit provides a comprehensive development environment for C and C++ developers building high-performance GPU-accelerated applications with CUDA libraries. The toolkit includes Nsight Eclipse Edition, debugging and profiling tools including Nsight Compute, and a toolchain for cross-compiling applications. NVIDIA Nsight Systems is a low overhead system-wide profiling tool, providing the insights developers need to analyze and optimize software performance. NVIDIA Nsight Graphics is a standalone application for debugging and profiling graphics applications. JetPack 4.6.1 includes NVIDIA Nsight Systems 2021.5 JetPack 4.6.1 includes NVIDIA Nsight Graphics 2021.2 Refer to release notes for more details. Supported SDKs and Tools NVIDIA DeepStream SDK is a complete analytics toolkit for AI-based multi-sensor processing and video and audio understanding. DeepStream SDK 6.0 supports JetPack 4.6.1 NVIDIA Triton™ Inference Server simplifies deployment of AI models at scale. Triton Inference Server is open source and supports deployment of trained AI models from NVIDIA TensorRT, TensorFlow and ONNX Runtime on Jetson. On Jetson, Triton Inference Server is provided as a shared library for direct integration with C API. PowerEstimator is a webapp that simplifies creation of custom power mode profiles and estimates Jetson module power consumption. PowerEstimator v1.1 supports JetPack 4.6. Cloud Native Jetson brings Cloud-Native to the edge and enables technologies like containers and container orchestration. NVIDIA JetPack includes NVIDIA Container Runtime with Docker integration, enabling GPU accelerated containerized applications on Jetson platform. NVIDIA hosts several container images for Jetson on NVIDIA NGC. Some are suitable for software development with samples and documentation and others are suitable for production software deployment, containing only runtime components. Find more information and a list of all container images at the Cloud-Native on Jetson page. Security NVIDIA Jetson modules include various security features including Hardware Root of Trust, Secure Boot, Hardware Cryptographic Acceleration, Trusted Execution Environment, Disk and Memory Encryption, Physical Attack Protection and more. Learn about the security features by jumping to the security section of the Jetson Linux Developer guide. Functional Safety NVIDIA Jetson approach to Functional Safety is to give access to the hardware error diagnostics foundation that can be used in the context

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The NVIDIA container image for PyTorch, release 22.10, is available on NGC. Contents of the PyTorch container This container image contains the complete source of the version of PyTorch in /opt/pytorch. It is prebuilt and installed in the Conda default environment (/opt/conda/lib/python3.8/site-packages/torch/) in the container image. The container also includes the following: Ubuntu 20.04 including Python 3.8 NVIDIA CUDA® 11.8.0 NVIDIA cuBLAS 11.11.3.6 NVIDIA cuDNN 8.6.0.163 NVIDIA NCCL 2.15.5 (optimized for NVIDIA NVLink®) NVIDIA RAPIDS™ 22.08.01 (For x86, only these libraries are included: cudf, xgboost, rmm, cuml, and cugraph.) Apex rdma-core 36.0 NVIDIA HPC-X 2.12.2tp1 OpenMPI 4.1.5a1 GDRCopy 2.3 TensorBoard 2.10.0 Nsight Compute 2022.3.0.22 Nsight Systems 2022.4.2.1 NVIDIA TensorRT™ 8.5.0.12 Torch-TensorRT 1.1.0a0 NVIDIA DALI® 1.18.0 MAGMA 2.6.2 JupyterLab 2.3.2 including Jupyter-TensorBoard TransformerEngine 0.1.0 Driver Requirements Release 22.10 is based on CUDA 11.8.0, which requires NVIDIA Driver release 520 or later. However, if you are running on a data center GPU (for example, T4 or any other data center GPU), you can use NVIDIA driver release 450.51 (or later R450), 470.57 (or later R470), 510.47 (or later R510), or 515.65 (or later R515). The CUDA driver's compatibility package only supports particular drivers. Thus, users should upgrade from all R418, R440, and R460 drivers, which are not forward-compatible with CUDA 11.8. For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades. GPU Requirements Release 22.10 supports CUDA compute capability 6.0 and later. This corresponds to GPUs in the NVIDIA Pascal, NVIDIA Volta™, NVIDIA Turing™, NVIDIA Ampere architecture, and NVIDIA Hopper™ architecture families. For a list of GPUs to which this compute capability corresponds, see CUDA GPUs. For additional support details, see Deep Learning Frameworks Support Matrix. Key Features and Enhancements This PyTorch release includes the following key features and enhancements. PyTorch

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New Application Replay Activity -- > New Application Replay complements the Kernel Replay activity. -- > New Application Replay complements the Kernel Replay activity(See the Super Computing 2020 spotlight on these replay modes) -->NVIDIA® Nsight™ Compute 2023.1 Videos and Blogs 2023.1 Spotlight and GTC 2020 videos Unleashing the Power of NVIDIA Ampere Architecture with NVIDIA Nsight Developer Tools blog GTC 2020 Lab Video and Materials-->Updates in 2023.1.0:General Support for CUDA Toolkit 12.1 was added. Resolved Issues blah--> Updates in 2023.1.2General Support for CUDA Toolkit 12.1 Update 2 was added. Enhanced support for NVIDIA virtual GPUs (vGPUs) in the upcoming GRID release. Updates in 2023.1.1General Added support for the CUDA toolkit 12.1 Update 1. Added new configuration options to set the default view mode and precision for the Source page.Resolved Issues Added support for the DT_RUNPATH attribute when intercepting calls to dlopen. Fixed issue for applications or libraries relying on DT_RUNPATH not finding all dynamic libraries when launched by NVIDIA Nsight Compute. Improved interaction between custom additional metrics and the selected metric set. Adding custom metrics no longer forces switching to the custom metric set. Added ability to gracefully skip folders with insufficient access permissions while importing source code. Fixed the calculation of the peak values for the L1 and L2 cache bandwidths in the hierarchical roofline charts. Fixed issue that prevented modules loaded with function optixModuleCreateFromPTX showing up in the Optix: Modules table of the Resources tool window. Fixed handling of deprecated functions when querying function pointers from the OptiX. parallel nsight下载 nvidia nsight下载 nvidia parallel nsight visual studio nvidia parallel nsight install nvidia parallel nsight monitor download eutron smartkey parallel driver

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Interception library. Fixed that sometimes sections or rules couldn't be easily selected in the tool window. Fixed issue with Reset Application Data that prevented some setting from correctly resetting. Fixed potential crash of NVIDIA Nsight Compute when Reset Application Data was executed multiple times in a row. Fixed a crash when saving or loading baselines for non-kernel results. Fixed that memory written while executing a CUDA graph was not properly restored in single-pass graph profiling. Fixed potential memory leak while collecting SW counters for modules with unpatched kernel functions.Updates in 2023.1.0General Added support for the CUDA toolkit 12.1. Support for OptiX 7.7 Added a new app-range replay mode to profile ranges without API capture by relaunching the entire application multiple times. Added sharedBankConflicts sample CUDA application and document to show how NVIDIA Nsight Compute can be used to analyze and identify the shared memory bank conflicts which result in inefficient shared memory accesses. Refer to the README.TXT file, sample code and document under extras/samples/sharedBankConflicts. Jupyter notebook samples are available in the Nsight training github repository. The equivalent of the high-level Python report interface is now available in rule files.NVIDIA Nsight Compute Added support for profiling individual metrics in Interactive Profile activity. A new input field for metrics was added in the Metric Selection tool window. Files on remote systems can be opened directly from the menu. Metric- and section-related entries in the menu, Profile activity and Metric Selection tool window were renamed to make them more clear. CPU and GPU

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Firefox Source Docs Doing performance work with GPUs is harder than with CPUs because of theasynchronous and massively parallel architecture.ToolsPIX - Can dotiming of Direct3D calls. Works reasonably well with Firefox.NVIDIA PerfHUD - Last I checked required a special build to be used.NVIDIA Parallel Nsight - Haven’t tried.AMD GPU ShaderAnalyzer - Will compile a shader and show the machine codeand give static pipeline estimations. Not that useful for Firefoxbecause all of our shaders are pretty simple.AMD GPU PerfStudio - I had trouble getting this to work, and can’tremember whether I actually did or not.Intel Graphics Performance AnalyzersHaven’t tried.APITraceOpen source, works OK.PVRTraceDoesn’t seem to emit traces on android/Nexus S. Looks like it’sdesigned for X11-based linux-ARM devices, OMAP3 is mentioned a lot inthe docs …GuidesAccurately Profiling Direct3D API Calls (Direct3D9)Suggests avoiding normal profilers like xperf and instead measuring thetime to flush the command buffer.OS X - Best Practices for Working with TextureDataSort of old, but still useful.