tenstorrent/tt-mlir
Oct 2025 – Apr 2026
2 Months active
Languages Used
C++MLIRPython
Technical Skills
Compiler DevelopmentDialect ExtensionLow-Level ProgrammingTensor Operationscompiler designhardware acceleration
Alex Richins
PROFILE
Alex Richins
During their tenure, Alex Richins enhanced the tenstorrent/tt-mlir repository by developing cross-dialect Bitwise NOT support for i32 and implementing hardware-accelerated unary math operations in the TTKernel dialect. Their work involved designing new operations, type handling, and lowering paths in C++ and MLIR, ensuring seamless integration with existing intermediate representations and code generation flows. Alex introduced comprehensive end-to-end and EmitC conversion tests, improving correctness and maintainability. By enabling lowering of unary math ops to the LLK compute API, they addressed performance and portability requirements. The depth of their contributions reflects strong skills in compiler development and low-level programming.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
573
Activity Months2
Your Network
438 peopleWork History
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for tenstorrent/tt-mlir focused on hardware-backed math operations via TTKernel dialect enhancements. Delivered 16 unary tile operations (exp2, expm1, log1p, square, softsign, signbit, selu, frac, trunc and respective init+tile pairs) to support lowering unary math ops to the LLK compute API in tt-metal. Implemented pattern where each op has an init+tile pair, with specific handling for ops requiring extra parameters (e.g., Selu with scale/alpha). Updated TTKernelToEmitC.cpp to register all new ops and added lit test cases in ttkernel.mlir to verify EmitC conversion. All changes are covered by a dedicated tests suite and aligned with a PR referencing #7914. This work enables hardware-accelerated unary math operations and paves the path for improved performance and portability across backends.
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for tenstorrent/tt-mlir focused on hardware-backed math operations via TTKernel dialect enhancements. Delivered 16 unary tile operations (exp2, expm1, log1p, square, softsign, signbit, selu, frac, trunc and respective init+tile pairs) to support lowering unary math ops to the LLK compute API in tt-metal. Implemented pattern where each op has an init+tile pair, with specific handling for ops requiring extra parameters (e.g., Selu with scale/alpha). Updated TTKernelToEmitC.cpp to register all new ops and added lit test cases in ttkernel.mlir to verify EmitC conversion. All changes are covered by a dedicated tests suite and aligned with a PR referencing #7914. This work enables hardware-accelerated unary math operations and paves the path for improved performance and portability across backends.
April 2026
October 2025
1 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on tt-mlir feature work: delivered cross-dialect Bitwise NOT support for i32, including new ops, type handling, lowering, and tests. This work enhances correctness and consistency across dialects, enabling broader optimization and codegen paths. The effort also improves test coverage and maintainability in the tt-mlir repo.
October 2025
1 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on tt-mlir feature work: delivered cross-dialect Bitwise NOT support for i32, including new ops, type handling, lowering, and tests. This work enhances correctness and consistency across dialects, enabling broader optimization and codegen paths. The effort also improves test coverage and maintainability in the tt-mlir repo.
Activity
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Quality Metrics
Correctness95.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++MLIRPython
Technical Skills
Compiler DevelopmentDialect ExtensionLow-Level ProgrammingTensor Operationscompiler designhardware accelerationlow-level programming
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