Xilinx/onnx-mlir
Apr 2025 – May 2025
2 Months active
Languages Used
C++MLIRPython
Technical Skills
Code GenerationCompiler DevelopmentCompiler OptimizationMLIRMLIR Dialect DevelopmentONNX
Arkar-Hema
PROFILE
Arkar-hema
Worked on the Xilinx/onnx-mlir repository to enhance ONNX dialect optimization and correctness using C++, MLIR, and Python. Developed a canonicalization fix ensuring MaxPool precedes Relu when Relu’s input is not directly from a Conv output, improving model transformation accuracy and processing efficiency. Introduced an optimization pass to merge nested Concat operations along the same axis, reducing redundant computations and simplifying the intermediate representation. Additionally, implemented a convolution fusion pass that combines parallel Conv operations sharing the same input, streamlining the computation graph and enabling future performance improvements. The work focused on maintainability and runtime efficiency in ONNX model compilation.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
510
Activity Months2
Your Network
102 peopleWork History
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05 Overview: In May 2025, delivered a new ONNX Convolution Fusion Optimization in the ONNX dialect, introducing a pass to merge parallel Convolution operations that share the same input into a single Conv operation. This reduces redundant computations, simplifies the computation graph, and lays groundwork for further performance optimizations in the ONNX-MLIR integration with Xilinx toolchains. The change is tracked in commit 32ba7210e491cbb83e657375e222b244206e50a1 with message 'Combine Parallel Convolution optimization pass in ONNX Dialect (#3116)'.
1 Commits • 1 Features
May 1, 2025Month: 2025-05 Overview: In May 2025, delivered a new ONNX Convolution Fusion Optimization in the ONNX dialect, introducing a pass to merge parallel Convolution operations that share the same input into a single Conv operation. This reduces redundant computations, simplifies the computation graph, and lays groundwork for further performance optimizations in the ONNX-MLIR integration with Xilinx toolchains. The change is tracked in commit 32ba7210e491cbb83e657375e222b244206e50a1 with message 'Combine Parallel Convolution optimization pass in ONNX Dialect (#3116)'.
May 2025
April 2025
2 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for Xilinx/onnx-mlir focusing on business value and technical achievements. Delivered two high-impact changes in the ONNX dialect with clear operational benefits: (1) Bug fix in canonicalization to ensure MaxPool precedes Relu when Relu input is not directly from a Conv output, improving correctness and processing efficiency; (2) New optimization pass to merge nested Concat operations along the same axis into a single Concat, reducing redundant computations and IR complexity. These changes streamline model transformations, reduce runtime overhead for compiled ONNX models, and improve maintainability of the ONNX dialect optimization pipeline.
April 2025
2 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for Xilinx/onnx-mlir focusing on business value and technical achievements. Delivered two high-impact changes in the ONNX dialect with clear operational benefits: (1) Bug fix in canonicalization to ensure MaxPool precedes Relu when Relu input is not directly from a Conv output, improving correctness and processing efficiency; (2) New optimization pass to merge nested Concat operations along the same axis into a single Concat, reducing redundant computations and IR complexity. These changes streamline model transformations, reduce runtime overhead for compiled ONNX models, and improve maintainability of the ONNX dialect optimization pipeline.
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture83.4%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++MLIRPython
Technical Skills
C++Code GenerationCompiler DevelopmentCompiler OptimizationMLIRMLIR Dialect DevelopmentONNXONNX RuntimeOptimizationOptimization Passes
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