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Introduction to Intel® Graphics Performance Analyzers
Game Optimization Methodology
Install and Launch Intel® GPA
Enable System-wide Time-based GPU Metrics and Enable Query-based Metrics for OpenGL* in Graphics Frame Analyzer for Ubuntu*
Launch Application for Analysis
Configure Analysis Settings
Quick Start with Profiling Unreal Engine* Games
Analyze Desktop Graphics Applications
Instrumentation and Tracing Technology API Support
Intel® GPA Reference
Notices and Disclaimers
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Introduction to Intel® Graphics Performance Analyzers
Intel® Graphics Performance Analyzers (Intel® GPA) is an application suite that contains tools for analysis and optimization of graphics-intensive applications, including but not limited to Microsoft DirectX*, Vulkan*, and OpenGL* games. With Intel GPA, you can test your applications on various platforms to detect bottlenecks and find the best optimization for each platform. You can also enable/disable certain features (such as detailed terrain features or additional interactive game elements) until you achieve the optimal game-playing experience.
Intel GPA tools display the application performance data, including GPU and CPU metrics, system events and their dependencies, which can help you optimize the application, save time and effort, and get your product to market faster. Intel GPA provides the following tools:
Graphics Monitor
Use the Graphics Monitor tool to access and arrange the set of metrics for graphics performance analysis of Microsoft DirectX, Vulkan, and OpenGL applications.
In Graphics Monitor you can choose desktop or Universal Windows applications for analysis, and open captured frames, streams and traces with the respective tools.
System Analyzer
Use System Analyzer as the first step on your way to application analysis to determine whether your code is CPU- or GPU-bound. If it is GPU-bound, keep on analyzing with Intel GPA tools.
Graphics Frame Analyzer
Use Frame Analyzer to explore the captured frame and understand the performance impact of specific API calls at different stages of the rendering pipeline. Experiment with API calls and various rendering pipeline settings to identify, locate, and resolve rendering issues in your Microsoft DirectX, Vulkan, and OpenGL applications.
Decrease frame rendering time, see into draw call issues and understand how they impact the FPS at different stages of the rendering pipeline.
Graphics Trace Analyzer
Use Graphics Trace Analyzer to identify problems with distributing the GPU and CPU resources and application data between functions.
Visualize the execution profile of the system events in your code over time across various flows, analyze application-level and system-level performance data, such as thread activity, context switches, API calls, identify synchronization and load balancing issues in your application.
Visualize the dynamics of resource sharing for application engines with multiple discrete tasks, such as collision detection and terrain generation, and more. Trace Analyzer can also help you identify whether your application is CPU- of GPU-bound. For details, refer to the Identify Issues in Graphics Application Execution with Trace Analyzer topic.
NOTE:
If your application is CPU-bound, consider using Intel® VTune™ Profiler, which is a tool to profile serial and multithreaded compute and media client and server applications that are executed on a variety of hardware platforms (CPU, GPU, FPGA). VTune Profiler supports local and remote target analysis on the Windows* and Linux* platforms.
Intel® Graphics Performance Analyzers Framework
Intel® Graphics Performance Analyzers Framework (Intel GPA Framework) is a cross-platform, cross-API suite of tools and interfaces that enables you to capture, playback, and analyze 3D graphics rich applications.
Use Framework in different ways: as a back-end, directly with console tools, and through linkage with libraries. Integrate Intel GPA Framework into CI automated frameworks to flag performance regressions and frame budget reports, automate various performance optimization experiments into scripts to quickly identify common bottlenecks. Capture multi-frame streams to spot performance issues that are hard to detect with single a frame capture, such as overall frame time variance, intermittent glitches, and so on.