In this video, Seth Schneider, Nsight Program Manager at NVIDIA, details the three most important things developers need to know about Nsight Systems.
Overview
The article discusses three essential aspects of Nsight Systems, a profiling tool developed by NVIDIA. It highlights its low overhead nature, its ability to eliminate guesswork in optimization, and its capability to trace CPU, GPU, and OS kernel events.
What You'll Learn
1
How to use Nsight Systems to inspect application algorithm timings
2
Why Nsight Systems is essential for identifying GPU starvation issues
3
When to transition from Nsight Systems to Nsight Compute or Nsight Graphics
Key Questions Answered
What is Nsight Systems and how does it help developers?
Nsight Systems is a profiling tool that helps developers inspect application algorithm timings and GPU interactions. It identifies optimization opportunities by analyzing workloads across CPU and GPU, making it easier to pinpoint performance bottlenecks.
How does Nsight Systems eliminate guesswork in optimization?
Nsight Systems allows users to identify various performance issues such as GPU starvation and unnecessary synchronization. By providing detailed insights into CPU and GPU performance, it helps developers make informed decisions about optimizations.
What types of events can be traced using Nsight Systems?
Nsight Systems can trace CPU, GPU, and OS kernel events, rendering millions of events from processes, threads, and APIs. This allows users to visualize relationships between these events and gain a comprehensive understanding of application performance.
Technologies & Tools
Backend
Cuda
Used for GPU programming and performance analysis in Nsight Systems.
Backend
Directx 12
Supported graphics API for profiling in Nsight Systems.
Key Actionable Insights
1Utilize Nsight Systems to identify the largest opportunities for optimization in your application.By inspecting algorithm timings and GPU interactions, you can pinpoint where performance improvements can be made, leading to more efficient applications.
2Incorporate NVTX annotations in your application for better visualization of trace data.This will help you understand the relationships between different events and improve your ability to analyze performance bottlenecks.
3Export timeline data to a SQLite database for advanced data mining.This allows for deeper analysis of performance metrics and can help in identifying long-term trends and issues that may not be immediately apparent.
Common Pitfalls
1
Failing to analyze GPU workloads can lead to missed optimization opportunities.
Developers may assume their applications are optimized without using profiling tools, which can result in suboptimal performance.