tenstorrent/tt-mlir
Jun 2026 – Jun 2026
1 Month active
Languages Used
BashC++Python
Technical Skills
C++ DevelopmentC++ developmentMLIRPython scriptingTensor OperationsTesting
Arsen Iman
PROFILE
Arsen Iman
Worked on the tenstorrent/tt-mlir repository to deliver enhanced profiling and instrumentation features focused on deepening observability and performance analysis for D2M operations. Developed a perf-analyzer tool and expanded operation-level instrumentation, enabling more granular bottleneck detection and improved data visualization. Integrated hardware performance counters and updated kernel duration semantics to provide accurate profiling data, while introducing helper Python scripts to streamline profiling workflows. Additionally, implemented argmax decomposition into D2M operations and added a column-major option for arange, both with comprehensive C++ and Python-based tests to ensure correctness and flexibility in tensor operations. No bugs were reported or fixed.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
2,338
Activity Months1
Your Network
479 peopleWork History
June 2026
3 Commits • 2 Features
Jun 1, 2026June 2026: Delivered profiling and instrumentation enhancements for tenstorrent/tt-mlir, focusing on comprehensive observability and D2M performance analysis. Implemented a perf-analyzer and expanded instrumentation across operations, enabling more reliable bottleneck detection and data presentation. Added hardware-counter based profiling for D2M and introduced helper tooling to streamline profiling workflows. Also delivered Argmax decomposition into D2M operations and a column-major option for arange, with accompanying tests to ensure correctness and coverage.
3 Commits • 2 Features
Jun 1, 2026June 2026: Delivered profiling and instrumentation enhancements for tenstorrent/tt-mlir, focusing on comprehensive observability and D2M performance analysis. Implemented a perf-analyzer and expanded instrumentation across operations, enabling more reliable bottleneck detection and data presentation. Added hardware-counter based profiling for D2M and introduced helper tooling to streamline profiling workflows. Also delivered Argmax decomposition into D2M operations and a column-major option for arange, with accompanying tests to ensure correctness and coverage.
June 2026
Activity
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture86.6%
Performance80.0%
AI Usage46.6%
Skills & Technologies
Programming Languages
BashC++Python
Technical Skills
C++ DevelopmentC++ developmentMLIRPython scriptingTensor OperationsTestingdata visualizationhardware performance countersperformance analysisperformance profilingprofiling
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