google-ai-edge/LiteRT
Mar 2025 – Jan 2026
2 Months active
Languages Used
C++Shell
Technical Skills
BenchmarkingBuild SystemsC++DebuggingGPU ComputingMemory Management
piyu
PROFILE
Piyu
Piyu contributed to the google-ai-edge/LiteRT repository by developing features that enhanced both benchmarking and profiling capabilities for model execution on GPUs. Over two months, Piyu built a configurable Benchmark Model Class, allowing pre-execution model compilation and flexible benchmarking workflows using C++ and TensorFlow Lite. Addressing GPU model execution failures, Piyu resolved tensor layout inconsistencies and fixed memory leaks, improving runtime stability. In a subsequent phase, Piyu integrated a ProfileSummarizer into LiteRtProfiler, enabling detailed operator-level performance analysis and new API methods for profiling data. The work demonstrated depth in debugging, performance profiling, and GPU-aware C++ development for robust model deployment.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
1,105
Activity Months2
Your Network
4513 peopleSame Organization
@google.com4362
Benedict OdaiMember
Craig IngramMember
KayyuriMember
Scott SuarezMember
Agent2Agent (A2A) BotMember
Andreas AbelMember
Aadi KapurMember
Aadish GoelMember
Aahil MehtaMember
Work History
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 performance-focused contributions for google-ai-edge/LiteRT. Delivered profiling enhancements focused on observability and performance analysis. Integrated LiteRtProfiler ProfileSummarizer to provide detailed operator-level summaries and performance metrics, with new API methods to generate profile summaries and update statistics from profiling events. This enables data-driven optimization and faster identification of bottlenecks during model execution. Commit: b28179d6cb900eeb71101a3e1d4827c3062ae143; RevId: 852383063.
1 Commits • 1 Features
Jan 1, 2026January 2026 performance-focused contributions for google-ai-edge/LiteRT. Delivered profiling enhancements focused on observability and performance analysis. Integrated LiteRtProfiler ProfileSummarizer to provide detailed operator-level summaries and performance metrics, with new API methods to generate profile summaries and update statistics from profiling events. This enables data-driven optimization and faster identification of bottlenecks during model execution. Commit: b28179d6cb900eeb71101a3e1d4827c3062ae143; RevId: 852383063.
January 2026
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for google-ai-edge/LiteRT focusing on stability improvements and benchmarking capabilities. Highlights include bug fixes for GPU model execution stability and the addition of a new LiteRT Benchmark Model Class enabling configurable pre-execution builds.
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for google-ai-edge/LiteRT focusing on stability improvements and benchmarking capabilities. Highlights include bug fixes for GPU model execution stability and the addition of a new LiteRT Benchmark Model Class enabling configurable pre-execution builds.
Activity
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture80.0%
Performance73.4%
AI Usage33.4%
Skills & Technologies
Programming Languages
C++Shell
Technical Skills
BenchmarkingBuild SystemsC++C++ developmentDebuggingGPU ComputingMemory ManagementModel ExecutionTensorFlow Liteperformance profilingsoftware testing
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