tenstorrent/tt-mlir
Oct 2025 – Oct 2025
1 Month active
Languages Used
C++Python
Technical Skills
Code GenerationCompiler DevelopmentLow-Level OptimizationMLIRPass ImplementationTesting
David Milinkovic
PROFILE
David Milinkovic
During October 2025, Dusan Milinkovic enhanced the tenstorrent/tt-mlir repository by developing features to improve CPU translation readiness for TTIR. He implemented an affine lowering pass within the TTIRToCPUPipeline, enabling translation from TTIR to CPU-friendly dialects and facilitating the generation of production-grade CPU binaries. Using C++ and MLIR, Dusan introduced NonContiguousMemrefCopyToLinalg to lower memref.copy operations for ttir.conv2d, ensuring correct CPU-hoisting by copying tensor.extract_slice results into output buffers. He also updated and un-quarantined tests, adding missing device parameters to improve test coverage. The work demonstrated depth in compiler development and low-level optimization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
128
Activity Months1
Your Network
390 people
Work History
October 2025
2 Commits • 2 Features
Oct 1, 2025Month 2025-10 focused on delivering CPU-ready TTIR features and stabilizing CPU-hoist paths for tt-mlir, enabling translation to CPU binaries and more robust performance. Key outcomes include introducing an affine lowering pass in TTIRToCPUPipeline to translate TTIR to CPU-friendly dialects and updating tests to include the missing device parameter; implementing NonContiguousMemrefCopyToLinalg to lower memref.copy for ttir.conv2d and ensuring tensor.extract_slice results are copied into the output buffer to support CPU-hoistability; overall improvements in CPU translation readiness and test coverage.
2 Commits • 2 Features
Oct 1, 2025Month 2025-10 focused on delivering CPU-ready TTIR features and stabilizing CPU-hoist paths for tt-mlir, enabling translation to CPU binaries and more robust performance. Key outcomes include introducing an affine lowering pass in TTIRToCPUPipeline to translate TTIR to CPU-friendly dialects and updating tests to include the missing device parameter; implementing NonContiguousMemrefCopyToLinalg to lower memref.copy for ttir.conv2d and ensuring tensor.extract_slice results are copied into the output buffer to support CPU-hoistability; overall improvements in CPU translation readiness and test coverage.
October 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Code GenerationCompiler DevelopmentLow-Level OptimizationMLIRPass ImplementationTesting
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