How to Install and Uninstall nsight-systems Package on Ubuntu 21.10 (Impish Indri)
Last updated: November 25,2024
1. Install "nsight-systems" package
This tutorial shows how to install nsight-systems on Ubuntu 21.10 (Impish Indri)
$
sudo apt update
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$
sudo apt install
nsight-systems
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2. Uninstall "nsight-systems" package
Please follow the instructions below to uninstall nsight-systems on Ubuntu 21.10 (Impish Indri):
$
sudo apt remove
nsight-systems
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the nsight-systems package on Ubuntu 21.10 (Impish Indri)
Package: nsight-systems
Architecture: amd64
Version: 2021.1.3.14~11.3.1-4
Priority: optional
Section: multiverse/devel
Source: nvidia-cuda-toolkit (11.3.1-4)
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian NVIDIA Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 344533
Depends: libjs-jquery, libjs-sphinxdoc, libjs-underscore, nsight-systems-target (= 2021.1.3.14~11.3.1-4), libasound2 (>= 1.0.16), libc6 (>= 2.17), libdbus-1-3 (>= 1.9.14), libexpat1 (>= 2.0.1), libfontconfig1 (>= 2.12.6), libfreetype6 (>= 2.6), libgcc-s1 (>= 4.0), libgl1, libglib2.0-0 (>= 2.22.0), libgssapi-krb5-2 (>= 1.17), libnspr4 (>= 2:4.9-2~), libnss3 (>= 2:3.22), libssl1.1 (>= 1.1.1), libstdc++6 (>= 6), libx11-6, libx11-xcb1 (>= 2:1.7.2), libxcb-glx0, libxcb1 (>= 1.8), libxcomposite1 (>= 1:0.4.5), libxcursor1 (>> 1.1.2), libxdamage1 (>= 1:1.1), libxext6, libxfixes3, libxi6, libxkbcommon-x11-0 (>= 0.5.0), libxkbcommon0 (>= 0.5.0), libxrandr2, libxrender1, libxtst6, zlib1g (>= 1:1.2.3.4)
Filename: pool/multiverse/n/nvidia-cuda-toolkit/nsight-systems_2021.1.3.14~11.3.1-4_amd64.deb
Size: 104110626
MD5sum: 8f0abe8ba9cab2f34a3d6a868de69928
SHA1: 2bb163e0b87239bc7bca161b660ccc215183b2e0
SHA256: e9b5a59003977733b3c610c4a34fa39e64dbed61acb5f62aa6011be554485c89
SHA512: ac4cf8bff8e747147e60b3e3f0e948d0f3bb0b7de6ae60fa145535e05326eaf10ec4c18313b754e09dff330bcce567a3fe8a4acd3a8459c99bf8220dfec460ac
Homepage: https://developer.nvidia.com/nsight-systems
Description-en: NVIDIA Nsight Systems
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 large server to smallest SoCs.
Description-md5: 07ace54e5beaed541842de61e76de614
Architecture: amd64
Version: 2021.1.3.14~11.3.1-4
Priority: optional
Section: multiverse/devel
Source: nvidia-cuda-toolkit (11.3.1-4)
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian NVIDIA Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 344533
Depends: libjs-jquery, libjs-sphinxdoc, libjs-underscore, nsight-systems-target (= 2021.1.3.14~11.3.1-4), libasound2 (>= 1.0.16), libc6 (>= 2.17), libdbus-1-3 (>= 1.9.14), libexpat1 (>= 2.0.1), libfontconfig1 (>= 2.12.6), libfreetype6 (>= 2.6), libgcc-s1 (>= 4.0), libgl1, libglib2.0-0 (>= 2.22.0), libgssapi-krb5-2 (>= 1.17), libnspr4 (>= 2:4.9-2~), libnss3 (>= 2:3.22), libssl1.1 (>= 1.1.1), libstdc++6 (>= 6), libx11-6, libx11-xcb1 (>= 2:1.7.2), libxcb-glx0, libxcb1 (>= 1.8), libxcomposite1 (>= 1:0.4.5), libxcursor1 (>> 1.1.2), libxdamage1 (>= 1:1.1), libxext6, libxfixes3, libxi6, libxkbcommon-x11-0 (>= 0.5.0), libxkbcommon0 (>= 0.5.0), libxrandr2, libxrender1, libxtst6, zlib1g (>= 1:1.2.3.4)
Filename: pool/multiverse/n/nvidia-cuda-toolkit/nsight-systems_2021.1.3.14~11.3.1-4_amd64.deb
Size: 104110626
MD5sum: 8f0abe8ba9cab2f34a3d6a868de69928
SHA1: 2bb163e0b87239bc7bca161b660ccc215183b2e0
SHA256: e9b5a59003977733b3c610c4a34fa39e64dbed61acb5f62aa6011be554485c89
SHA512: ac4cf8bff8e747147e60b3e3f0e948d0f3bb0b7de6ae60fa145535e05326eaf10ec4c18313b754e09dff330bcce567a3fe8a4acd3a8459c99bf8220dfec460ac
Homepage: https://developer.nvidia.com/nsight-systems
Description-en: NVIDIA Nsight Systems
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 large server to smallest SoCs.
Description-md5: 07ace54e5beaed541842de61e76de614