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Jovan Serbedzija

PROFILE

Jovan Serbedzija

Jovan Serbedzija contributed to the tenstorrent/tt-metal and tt-forge-fe repositories by developing features and resolving issues focused on tensor operations and performance optimization. He enhanced test coverage for Conv2dWeights unpadding, introducing validation tests and debugging outputs to improve diagnosability of tensor shape issues. Jovan implemented flexible input handling by enabling optional TensorSpec to Tensor conversion for the PrepareConvBias API, increasing robustness in C++ code. In tt-forge-fe, he added configuration-driven Conv2dWithMultiply optimizations for ResNet benchmarks using MLIR. He also stabilized tt-metal builds by fixing a MemoryConfig compilation error, demonstrating depth in error resolution and header file management.

Overall Statistics

Feature vs Bugs

75%Features

Repository Contributions

5Total
Bugs
1
Commits
5
Features
3
Lines of code
91
Activity Months3

Work History

September 2025

1 Commits

Sep 1, 2025

September 2025: Focused on stabilizing the tt-metal build by addressing a MemoryConfig compilation issue in the NLP decode path, delivering a targeted include directive fix that eliminates a blocking error and improves integration resilience.

July 2025

3 Commits • 2 Features

Jul 1, 2025

2025-07 Monthly Summary across tt-metal and tt-forge-fe focused on robustness and performance improvements through new input handling capabilities and configuration-driven optimizations. In tt-metal, added conversion from optional TensorSpec to optional Tensor to support the PrepareConvBias constraint API, enabling handling of absent TensorSpecs and increasing flexibility and robustness of tensor input handling. Commits: 012325b78f7b8f960f0b869b67ce892bb7aa10df; 36b72a2ab65cf54bf11e09a43460d1bf5f4bbf83.

June 2025

1 Commits • 1 Features

Jun 1, 2025

June 2025: focus on strengthening test coverage for Conv2dWeights unpadding in tt-metal. Implemented a new validation test for PrepareConv2dWeights unpadding, with debugging output to diagnose tensor shape issues. This work reduces risk of regressions in unpadding logic and accelerates diagnosis of shape issues in future changes.

Activity

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Quality Metrics

Correctness92.0%
Maintainability92.0%
Architecture92.0%
Performance92.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++Python

Technical Skills

API developmentBenchmarkingC++ developmentCompiler OptimizationMLIRPerformance TuningTensor manipulationTensor operationserror resolutionheader file managementtensor operationsunit testing

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

tenstorrent/tt-metal

Jun 2025 Sep 2025
3 Months active

Languages Used

C++

Technical Skills

C++ developmenttensor operationsunit testingAPI developmentTensor manipulationTensor operations

tenstorrent/tt-forge-fe

Jul 2025 Jul 2025
1 Month active

Languages Used

C++Python

Technical Skills

BenchmarkingCompiler OptimizationMLIRPerformance Tuning

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