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 our smallest SoC.

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Overview

NVIDIA Nsight Systems is a low overhead performance analysis tool designed to provide nsights developers need to optimize their software. Unbiased activity data is visualized within the tool to help users investigate bottlenecks, avoid inferring false-positives, and pursue optimizations with higher probability of performance gains. Users will be able to identify issues, such as GPU starvation, unnecessary GPU synchronization, insufficient CPU parallelizing, and even unexpectedly expensive algorithms across the CPUs and GPUs of their target platform. It is designed to scale across a wide range of NVIDIA platforms such as: large Tesla multi-GPU x86 servers, Quadro workstations, Optimus enabled laptops, DRIVE devices with Tegra+dGPU multi-OS, and Jetson. NVIDIA Nsight Systems can even provide valuable insight into the behaviors and load of deep learning frameworks such as PyTorch and TensorFlow; allowing users to tune their models and parameters to increase overall single or multi-GPU utilization.

Platforms

Learn about Nsight Systems on your platform:

Release Highlights

2021.1 - Announcement Post

• Support for top ray tracing titles on Vulkan
• UX and performance improvements

2020.5 - Announcement Post

• NVIDIA Ampere Architecture
• CUDA memory allocation trace
• NCCL trace
• UX improvements
• Improved selection highlights
• Support for hi-DPI displays

2020.4 - Announcement Post

• NVIDIA Ampere Architecture
• CUDA 11.1
• CUDA memory allocation trace
• Labeled and color coded UVM transfers
• Launch Nsight Compute to profile kernel selected from within Nsight Systems
• Vulkan mGPU and device groups
• Timeline improvements
• Unified OpenGL workloads
• Frame duration statistics
• System wall clock allowing to compare multiple reports
• CLI on Windows
• UX improvements

2020.3 - Announcement Post

• NVIDIA Ampere Architecture
• CUDA 11.0
• CUDA Graph correlation
• OptiX
• Vulkan KHR ray tracing extension
• OpenMP
• CLI improvements
• UX improvements

Downloads

Available for profiling directly on Linux workstations and servers, including the NVIDIA DGX line, or remotely from a variety of hosts: Windows, Linux, or MacOSX.

Not profiling Linux workstations or servers?
Learn about other target platforms.

Documentation

Support

To provide feedback, request additional features, or report support issues, please use the Developer Forums.

System Requirements

Supported target operating systems for data collection:

• Ubuntu 16.04, 18.04 and 20.04*
• CentOS 7+*
• Red Hat Enterprise Linux 7+*
* For older OS versions, please use Nsight Systems 2020.3

Supported target hardware

• GPU: Pascal or newer
• CPU: x86-64, Arm Server Base System Architecture and Power9 processors*
* Intel Haswell architecture or newer is required for LBR sampling backtraces

Supported target software

• 64 bit applications only
• CUDA 10.0+ for CUDA tracing
• Requires driver r418 or newer

Supported host operating systems for data visualization:

• Windows 10+
• macOS X 10.9+
• Ubuntu 16.04, 18.04 and 20.04

Release Highlights

2021.1 - Announcement Post

• Support for top ray tracing titles on DirectX and Vulkan
• Stats on Windows CLI
• UX and performance improvements

2020.5 - Announcement Post

• NVIDIA Ampere Architecture
• UX improvements
• Improved selection highlights
• Support for hi-DPI displays

2020.4 - Announcement Post

• NVIDIA Ampere Architecture
• CUDA 11.1
• CUDA memory allocation trace
• Labeled and color coded UVM transfers
• Launch Nsight Compute to profile kernel selected from within Nsight Systems
• Vulkan mGPU and device groups
• Timeline improvements
• Unified OpenGL workloads
• Frame duration statistics
• System wall clock allowing to compare multiple reports
• CLI on Windows
• UX improvements

2020.3 - Announcement Post

• NVIDIA Ampere Architecture
• CUDA 11.0
• CUDA Graph correlation
• OptiX
• Vulkan KHR ray tracing extension
• DirectX Raytracing(DXR) Tier 1.1
• UX improvements

Downloads

Available for profiling directly on Linux workstations and servers, including the NVIDIA DGX line, or remotely from a variety of hosts: Windows, Linux, or MacOSX.
Visual Studio Integration*requires Nsights Sytems to be installed

Not profiling Windows targets?
Learn about other target platforms.

Documentation

Support

To provide feedback, request additional features, or report support issues, please use the Developer Forums.

System Requirements

Supported operating systems

• Windows 10

Supported target hardware

• GPU: Pascal or newer
• CPU: x86-64 processors

Supported target software

• 64 bit applications only
• CUDA 10.0+ for CUDA tracing
• Requires driver r418 or newer

Release Highlights

2019.4

• Ftrace collection on Linux
• Event table - alternative view of timeline data
• Improved CUDA memory transfer color scheme
• Android 9 support
• Expanded export capabilities
  • New data sources: thread information, cuDNN, cuBLAS

2019.3

• QNX OS runtime backtraces for long blocking functions
• Exporters for SQLite & JSON
  • NVTX, CUDA, OS Runtime Trace(OSRT)

Downloads

Nsight Systems is bundled as part of the following product development suites:

Jetson via NVIDIA SDK Manager

Documentation

Support

To provide feedback, request additional features, or report support issues, please use the Developer Forums.

System Requirements

Supported Target Hardware

• ShieldTV
• Jetson AGX Xavier, Jetson TX2, Jetson TX1
• DRIVE AGX Pegasus, DRIVE AGX Xavier, DRIVE PX Parker AutoChauffeur, DRIVE PX Parker AutoCruise

Supported target operating systems for data collection:

• QNX
• Linux
• Android

Supported host operating systems for data visualization:

• Ubuntu 16.04, and 18.04

Features

Learn about feature support per target platform group

Feature	Linux Workstations and Servers	Windows Workstations and Gaming PCs	Jetson Autonomous Machines	DRIVE Autonomous Vehicles
View system-wide application behavior across CPUs and GPUs
CPU cores utilization, process, & thread activities	yes	yes	yes	yes
CPU thread periodic sampling backtraces	yes*	no	yes	yes
CPU thread blocked state backtraces	yes**	yes	yes	yes
CPU performance counter sampling	no	no	yes	yes
GPU workload trace	yes	yes	yes	yes
GPU context switch trace	no	no	yes	yes
SOC hypervisor trace	-	-	-	yes
SOC memory bandwidth sampling	-	-	yes	yes
SOC Accelerators trace	-	-	Xavier	Xavier
OS Event Trace	ftrace	ETW	ftrace	ftrace
Investigate CPU-GPU interactions and bubbles
User annotations API trace NVIDIA Tools Extension API (NVTX)	yes	yes	yes	yes
CUDA API	yes	yes	yes	yes
CUDA libraries trace (cuBLAS, cuDNN & TensorRT)	yes	no	yes	yes
OpenGL API trace	yes	yes	yes	yes
Vulkan API trace	yes	yes	no	no
Direct3D12, Direct3D11, DXR, & PIX APIs	-	yes	-	-
OptiX	7.1+	7.1+	-	-
Bidirectional correlation of API and GPU workload	yes	yes	yes	yes
Identify GPU idle and sparse usage	yes	yes	yes	yes
Multi-GPU Graphics trace	-	Direct3D12	-	-
Ready for big data
Fast GUI capable of visualizing in excess of 10 million events on laptops	yes	yes	yes	yes
Additional command line collection tool	yes	no	no	no
NV-Docker container support	yes	-	-	-
NVIDIA GPU Cloud support	yes	-	-	-
Minimum user privilege level	user	administrator	root	root

* On Intel Haswell and newer CPU architecture

** Only with OS runtime trace enabled. Some syscalls such as handcrafted assembly may be missed. Backtraces may only appear if time threasholds are exceeded.

What Users Are Saying

AWS

Deepset achieves a 3.9x speedup and 12.8x cost reduction for training NLP models by working with AWS and NVIDIA

Tracxpoint

We noticed that our new Quadro P6000 server was ‘starved’ during training and we needed experts for supporting us. NVIDIA Nsight Systems helped us to achieve over 90 percent GPU utilization. A deep learning model that previously took 600 minutes to train, now takes only 90.

Felix Goldberg, Chief AI Scientist, Tracepoint

NVIDIA

I used Nsight Systems to analyze our internal system and built a plan for optimizing both CPU and GPU usage, with significant performance and resource gains ultimately achieved to both. Overall, there is no alternative tool like Nsight which helps me to extract only, and exactly what I need to understand resource usage.

Sang Hun Lee, System Software Engineer, NVIDIA

NIH Center for Macromolecular Modeling and Bioinformatics at University of Illinois at Urbana-Champaign

Watch John Stone, present how he achieved over a 3x performance increase in VMD; a popular tool for analyzing large biomolecular systems.

Related Media

Direct3D11 Feature Spotlight

The 2019.6 release aims to provide a more detailed data collection, exploration, and collection control for all markets ranging from high performance computing to visual effects. 2019.6 introduces new data sources, improved visual data navigation, expanded CLI capabilities, extended export coverage and statistics.

Command Line Sessions Feature Spotlight

NVIDIA Nsight Systems 2020.1 release adds CLI support for Power9 architecture. The ability to run multiple recording sessions simultaneously in CLI. UX improvements and stats export options in the GUI and CLI.

OpenMP Feature spotlight

In the 2020.3 release, Nsight Systems adds ability to analyze applications parallelized using OpenMP.

Statistics Driven Profiling

In the 2019.3 release, Nsight Systems adds the ability to analyze reports using statistics to identify opportunities for improving your GPU-accelerated application.

2019.4 Release Spotlight

The 2019.4 release aims to provide a more detailed data collection, exploration, and collection control for all markets ranging from high performance computing to visual effects. 2019.4 introduces new data sources, improved visual data navigation, expanded CLI capabilities, extended export coverage and statistics.

Vulkan Trace

In the 2019.3 release, Nsight Systems adds the ability to trace vulkan on Windows and Linux targets; allowing you to inspect the CPU/GPU relationship and solve complicated frame stuttering issues in your Vulkan application.

Optimizing HPC simulation and visualization code

Watch John Stone, of the NIH Center for Macromolecular Modeling and Bioinformatics at University of Illinois at Urbana-Champaign, discuss how he achieved over a 3x performance increase of VMD, a popular tool for analyzing large biomolecular systems.

NVIDIA Jetson Partner Stories: Stereolabs

In the drone industry, the weight and size of the main board is critical. With the ZED stereo camera by Stereolabs, developers can capture the world in 3D and map 3D models of indoor and outdoor scenes up to 20 meters. The small form factor of the Jetson TX1 enables Stereolabs to bring advanced computer vision capabilities to smaller and smaller systems. See what is possible when these two technologies come together in drones to power the latest virtual reality applications.

NVIDIA System Profiler - Introduction

An introduction to the latest NVIDIA System Profiler. Includes an UI workthrough and setup details for NVIDIA System Profiler on the NVIDIA Jetson Embedded Platform. Download and learn more here.

Analyzing NCCL Usage with NVIDIA Nsight Systems

NVIDIA Nsight Systems now includes support for tracing NCCL (NVIDIA Collective Communications Library) usage in your CUDA application. Download and learn more here.

Nsight Systems Feature Spotlight: OpenMP

NVIDIA® Nsight™ Systems is an indispensable system-wide performance analysis tool, designed to help developers tune and scale software across CPUs and GPUs. Download and learn more here.

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Nsight™ Systems provides system-wide visualization of application performance on HPC servers and enables you to optimize away bottlenecks and scale parallel applications across multicore CPUs and GPUs. Nsight Compute allows you to deep dive into GPU kernels in an interactive profiler for GPU-accelerated applications via a graphical or command-line user interface, and allows you to pinpoint performance bottlenecks using the NVTX API to directly instrument regions of your source code.

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Developer blog: Building and Deploying HPC Applications using NVIDIA HPC SDK from the NVIDIA NGC Catalog.

What Users are Saying

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– Nicholas Wright, NERSC Chief Architect

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