NVIDIA® Nsight™ Systems is a system-wide performance analysis tool designed to visualize an application’s algorithms, help you select the largest opportunities to optimize, and tune to scale efficiently across any quantity of CPUs and GPUs in your computer; from laptops to DGX servers.
NVIDIA Nsight Systems is a low overhead performance analysis tool designed to provide insights 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 workstations and servers. NVIDIA Nsight Systems can even provide valuable insight into the behaviors and load of deep learning frameworks such as Caffe2 and TensorFlow; allowing users to tune their models and parameters to increase overall single or GPU utilization.
Watch John Stone, from the NIH Center for Macromolecular Modeling and Bioinformatics at University of Illinois at Urbana-Champaign, present how he achieved over a 3x performance increase in VMD; a popular tool for analyzing large biomolecular systems.
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.
To provide feedback, request additional features, or report support issues, please use the Developer Forums.
Supported target operating systems for data collection:
* In distribution versions below 7.4, some features will be disabled unless the OS kernel has been upgraded to greater than or equal to kernel version 4.3
Supported target hardware
Supported target software
Supported host operating systems for data visualization:
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.
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.