google/perfetto
Apr 2026 – May 2026
2 Months active
Languages Used
C++Python
Technical Skills
C++ developmentPerformance analysisPython scriptingUI developmentData processingGPU profiling
Ross Ning
PROFILE
Ross Ning
Over a two-month period, contributed to the google/perfetto repository by enhancing GPU tracing and timeline analysis for Adreno devices. Developed custom C++ and Python parsers to process KGSL ftrace events, enabling accurate visualization of GPU command batch activity within the Perfetto UI. Introduced dual-push timestamp handling and per-cmdbatch synchronization logic in the trace processor, resolving timeline drift and improving event ordering for GPU workloads. Updated documentation and test plans to support repeatable validation, and implemented regression tests to ensure timeline integrity. This work improved the reliability of GPU profiling and performance analysis for developers using Perfetto on mobile platforms.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
732
Activity Months2
Your Network
261 peopleShared Repositories
261
Work History
May 2026
2 Commits • 1 Features
May 1, 2026Monthly summary for 2026-05 (google/perfetto): Delivered GPU Timeline Integrity Improvements in Trace Processor, significantly enhancing timeline accuracy for GPU events and overall usability for performance debugging. Implemented a dual-push approach for timestamps (raw and forged) to ensure correct event ordering in ftrace_event, and added specialized parsing for kgsl adreno_cmdbatch_sync and adreno_cmdbatch_retired events to generate precise GPU timeline slices. This work builds on prior timeline reliability improvements and enables robust GPU analysis across Adreno workloads. Key achievements include the integration of two critical commits that drive these improvements: 55f31a51d6067f42bdb127e3d244d4c3a89246e0 (tp: use raw ftrace timestamp in ftrace_event table via dual-push; introduce custom tokenizers to forge a separate sorter timestamp) and d119b70f5b0b2dc307f7a06142674c9c1ac33631 (trace_processor: Parse adreno_cmdbatch_retired/sync events; produce GPU timeline slices; fix drift using per-cmdbatch sync points). The changes collectively fix GPU timeline drift and ensure correct slice ordering. Major bugs fixed: resolved drift in the GPU timeline for Adreno cmdbatch events by adopting per-cmdbatch sync points and custom event parsing, replacing reliance on a single global timestamp. Validated with regression tests showing stable Adreno timeline slices and zero drift in targeted scenarios. Overall impact and business value: Provides accurate GPU timelines, enabling faster diagnosis of performance regressions and GPU stalls, more reliable performance analytics, and reduced MTTR for GPU-related issues. This strengthens Perfetto as a production-grade tracing/diagnostics platform for GPU workloads. Technologies/skills demonstrated: Ftrace event handling, trace processor parsing, Adreno/kgsl GPU events, per-cmdbatch synchronization logic, custom tokenizers, advanced timeline sorting and testing workflows (Python tooling and regression tests).
2 Commits • 1 Features
May 1, 2026Monthly summary for 2026-05 (google/perfetto): Delivered GPU Timeline Integrity Improvements in Trace Processor, significantly enhancing timeline accuracy for GPU events and overall usability for performance debugging. Implemented a dual-push approach for timestamps (raw and forged) to ensure correct event ordering in ftrace_event, and added specialized parsing for kgsl adreno_cmdbatch_sync and adreno_cmdbatch_retired events to generate precise GPU timeline slices. This work builds on prior timeline reliability improvements and enables robust GPU analysis across Adreno workloads. Key achievements include the integration of two critical commits that drive these improvements: 55f31a51d6067f42bdb127e3d244d4c3a89246e0 (tp: use raw ftrace timestamp in ftrace_event table via dual-push; introduce custom tokenizers to forge a separate sorter timestamp) and d119b70f5b0b2dc307f7a06142674c9c1ac33631 (trace_processor: Parse adreno_cmdbatch_retired/sync events; produce GPU timeline slices; fix drift using per-cmdbatch sync points). The changes collectively fix GPU timeline drift and ensure correct slice ordering. Major bugs fixed: resolved drift in the GPU timeline for Adreno cmdbatch events by adopting per-cmdbatch sync points and custom event parsing, replacing reliance on a single global timestamp. Validated with regression tests showing stable Adreno timeline slices and zero drift in targeted scenarios. Overall impact and business value: Provides accurate GPU timelines, enabling faster diagnosis of performance regressions and GPU stalls, more reliable performance analytics, and reduced MTTR for GPU-related issues. This strengthens Perfetto as a production-grade tracing/diagnostics platform for GPU workloads. Technologies/skills demonstrated: Ftrace event handling, trace processor parsing, Adreno/kgsl GPU events, per-cmdbatch synchronization logic, custom tokenizers, advanced timeline sorting and testing workflows (Python tooling and regression tests).
May 2026
April 2026
1 Commits • 1 Features
Apr 1, 2026In April 2026, focused on expanding Perfetto's GPU tracing capabilities by delivering UI-level GPU slices and ensuring reliable visualization for Adreno KGSL events. This work enhances developers’ ability to debug GPU workloads and optimize GPU-accelerated pipelines across mobile devices.
April 2026
1 Commits • 1 Features
Apr 1, 2026In April 2026, focused on expanding Perfetto's GPU tracing capabilities by delivering UI-level GPU slices and ensuring reliable visualization for Adreno KGSL events. This work enhances developers’ ability to debug GPU workloads and optimize GPU-accelerated pipelines across mobile devices.
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage33.4%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++ developmentData processingGPU profilingPerformance analysisPython scriptingUI development
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