This page contains news and instructional blogs for NVIDIA® Nsight™ Compute. These articles are a great resource for enhancing your understanding of all the features Nsight Compute has to offer.


Using NVIDIA Nsight Compute 2020.1 in Containers

Containers are now ubiquitous, and for good reason; the portability and productivity enhancements they provide have made them a standard component in HPC and many other computing fields. The NVIDIA Nsight family of developer tools for analyzing performance of CUDA applications are supported in container environments. This post contains information for using Nsight Compute in container environments. Nsight Compute is specifically designed to provide detailed performance analysis of CUDA kernels running on the GPU.


August 14, 2020 Nsight Compute Overview | Read on NVIDIA's DevBlogs

GTC 2020 Lab: Modern CUDA Programming Hazards and the Linux Nsight Toolbox to Fix Them

In this hands-on lab, you'll learn from NVIDIA developers and experts about efficiently debugging, profiling, and optimizing CUDA applications on Linux. Through a set of exercises, you'll use the latest features in NVIDIA's suite of tools, including Nsight Compute 2020.1, to detect and fix common issues of correctness and performance in their applications.


May 21, 2020 Lab Instructions (PDF) | Lab Materials on GitHub

Unleashing the Power of NVIDIA Ampere Architecture with NVIDIA Nsight Developer Tools

See how NVIDIA Nsight Compute 2020.1 fits into a top-down profiling strategy and how it can help you tune your applications for use with CUDA 11.0 and NVIDIA's Ampere GPU architecture.


May 14, 2020 Nsight Compute Overview | New in 2020.1 | Read on NVIDIA's DevBlogs

Using Nsight Compute to Inspect your Kernels

NVIDIA has added Nsight Compute to the repertoire of CUDA tools available for developers. This tool is important when using newer GPU architectures. For the example project in this blog, using Nsight Compute is necessary to get the results we are after for Turing architecture GPUs and beyond. One of the main purposes of Nsight Compute is to provide access to kernel-level analysis using GPU performance metrics. If you’ve used either the NVIDIA Visual Profiler, or nvprof (the command-line profiler), you may have inspected specific metrics for your CUDA kernels. This blog focuses on how to do that using Nsight Compute.


September 16, 2019 | Nsight Compute 2019.4 (CUDA 10.1 Update 2) | Read on NVIDIA's DevBlogs

Migrating to NVIDIA Nsight Tools from NVVP and Nvprof

See how NVIDIA Nsight Compute 2020.1 fits into a top-down profiling strategy and how it can help you tune your applications for use with CUDA 11.0 and NVIDIA's Ampere GPU architecture.


July 15, 2019 | Nsight Compute 2019.3 (CUDA 10.1 Update 1) | Read on NVIDIA's DevBlogs

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