--- title: Analyzing Apple GPU performance using a visual timeline framework: xcode role: article role_heading: Article path: xcode/analyzing-apple-gpu-performance-using-a-visual-timeline --- # Analyzing Apple GPU performance using a visual timeline Locate performance issues using the Performance timeline. ## Overview Overview important: The Performance timeline feature is only applicable to Apple GPUs. For other GPU architectures, see Analyzing non-Apple GPU performance using counter statistics. Apple GPUs run vertex, fragment, and compute tasks in parallel whenever possible. To explore the parallel nature of Apple GPUs, the Performance timeline helps you visualize the various passes and stages running simultaneously. For information on using the Performance timeline to optimize your Metal workload and profiling your workload in different GPU execution modes, see Optimizing GPU performance. View your shaders in the timeline The top section has the Vertex, Fragment, and Compute GPU tracks, which display the beginning time and duration of individual passes running with overlap. Below the GPU tracks are the aggregated shader tracks that combine the individual shaders. You can view the timeline of individual shaders in a waterfall-like fashion by expanding the aggregated shader tracks. The bottom section has a separate Counters timeline, which includes GPU counters such as Occupancy, Limiter, and Bandwidth. The counters can help you diagnose performance bottlenecks. You can focus on counter subsets by switching between different counter tabs. Display additional information Clicking any track in the Performance timeline selects it and displays additional information about the track in the sidebar. Similarly, clicking any element in the Performance timeline selects it and displays additional information about the element in the sidebar. Limit your scope with filters Adjust the track-filtering criteria with the filter field at the bottom of the GPU timeline or Counters timeline. You can type filter terms into the field, and the GPU timeline or Counters timeline shows tracks with names that match those terms. For example, you can simplify the Counters timeline to only show limiter counters by adding “limiter” to the filter field. For any filter term, you can click it and choose to include or exclude tracks that match that term. Search for specific elements Choose Find > Find to display the search bar above the Performance timeline. You can type search terms into the search bar’s text field to find matching command encoders and shaders. For any search term, you can click it and choose to include or exclude elements that match the term. The two arrow buttons to the right of the text field let you move to the previous or the next matching element in the timeline. Focus on the time for an element Focusing on the time for an element collapses the nonrelevant time ranges in the Performance timeline: To focus on an encoder, Control-click the element in the timeline and select Focus on Encoder. To focus on a shader, Control-click the element in the timeline and select Focus on Shader. To exit the focus mode, click the Expand Timeline button at the bottom of the Performance timeline. Minimize performance bottlenecks Look for abnormally long passes. Check whether the GPU time for various tasks matches your expectation or exceeds the budget time. Try overlapping GPU tasks. Apple GPUs run vertex, fragment, and compute tasks in parallel whenever possible. For example, independent render passes and compute passes can run in parallel. If you observe nonoverlapping work, check whether your GPU work is overserialized. Also, use concurrent compute passes wherever possible so dispatches that touch different resources can execute concurrently. Avoid too many small passes. There’s setup time between passes, so having small passes adds latency. Use the counters as insights for improving passes in the critical path. The counter tracks available below the GPU tracks show a few key performance metrics. Aim for higher occupancy with efficient GPU work. Use limiters as clues to offload some work to underutilized subsystems on the GPU. In addition, you can Control-click any pass in the Performance timeline and choose Reveal in Counters to view more detailed counters data for a pass. For more information on counters, see Finding your Metal app’s GPU occupancy and Reducing shader bottlenecks. Prioritize optimizing passes in the critical path. When inspecting a pass, you can focus on the running shaders in the aggregated shader track below the GPU track. In addition, you can Control-click any shader in the Performance timeline and choose Open Shader. In the Shader editor, you can find per-line shader profiling statistics for identifying hot spots. ## See Also ### Metal workload analysis - [Analyzing your Metal workload](xcode/analyzing-your-metal-workload.md) - [Analyzing resource dependencies](xcode/analyzing-resource-dependencies.md) - [Analyzing memory usage](xcode/analyzing-memory-usage.md) - [Analyzing Apple GPU performance using counter statistics](xcode/analyzing-apple-gpu-performance-using-counter-statistics.md) - [Analyzing Apple GPU performance with performance heat maps](xcode/analyzing-apple-gpu-performance-using-performance-heatmaps-a17-m3.md) - [Analyzing Apple GPU performance using the shader cost graph](xcode/analyzing-apple-gpu-performance-using-shader-cost-graph-a17-m3.md) - [Analyzing non-Apple GPU performance using counter statistics](xcode/analyzing-non-apple-gpu-performance-using-counter-statistics.md)