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Differential flame graphs compare two profiling runs and highlight where performance has changed. This makes it easier to detect regressions introduced by code changes and to verify that optimizations have the intended effect. The visualization renders the current profile with frame widths representing current time consumption. Color is then applied to show the difference relative to the baseline profile: red gradients indicate regressions, while blue gradients indicate improvements. Some call paths may disappear entirely between profiles. These are referred to as elided stacks and occur when optimizations remove code paths or when certain branches stop executing. When elided stacks are present, an "Elided" toggle is displayed, allowing the user to switch between the main differential view and a view showing only the removed paths. Co-authored-by: Pablo Galindo Salgado <Pablogsal@gmail.com> |
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| sampling | ||
| tracing | ||
| __init__.py | ||