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PROFILE

Qti-mattsinc

Matt Sincavage contributed to the CodeLinaro/onnxruntime and ROCm/onnxruntime repositories, focusing on backend and GPU enhancements for deep learning model execution. He developed FP16 Expand support and multi-device GPU backend handling, implementing device selection logic and extending the QNN Execution Provider to prefer GPU when available. Using C++ and Python, Matt added features such as Pad operation support for pre-opset 11 models, Softmax layout transformation for GPU backends, and an alternate LayerNorm fusion pattern. He also addressed cross-backend zero padding consistency, improving model portability and runtime stability. His work demonstrated depth in backend development and testing.

Overall Statistics

Feature vs Bugs

83%Features

Repository Contributions

7Total
Bugs
1
Commits
7
Features
5
Lines of code
932
Activity Months3

Work History

January 2026

4 Commits • 4 Features

Jan 1, 2026

January 2026: Delivered key QNN EP enhancements to CodeLinaro/onnxruntime that improve device selection, broaden model compatibility, and boost GPU backend support. Implemented default device behavior, added Pad op support for pre-opset11, enabled Softmax layout transformation for GPUs, and introduced an alternate LayerNorm fusion pattern in preprocess. These changes improve stability, performance, and deployment scenarios across diverse hardware, delivering tangible business value for end-to-end DL model execution.

December 2025

1 Commits

Dec 1, 2025

2025-12 monthly summary for ROCm/onnxruntime focusing on key bug fix delivering cross-backend padding consistency and validation improvements. The month centered on stabilizing zero padding behavior across backends and reducing model-runtime surprises, enabling smoother deployments.

September 2025

2 Commits • 1 Features

Sep 1, 2025

Month: 2025-09 | Repository: CodeLinaro/onnxruntime. Focused feature delivery in QNN: FP16 Expand support and GPU backend, with multi-device handling and GPU preference. Implemented translation of FP16 Expand op and extended QNN Execution Provider factory to include GPU support, accompanied by cross-device tests for CPU and GPU backends. No major bugs reported during this period.

Activity

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Quality Metrics

Correctness91.4%
Maintainability80.0%
Architecture88.6%
Performance80.0%
AI Usage22.8%

Skills & Technologies

Programming Languages

C++Python

Technical Skills

API DevelopmentBackend DevelopmentC++C++ developmentData ProcessingDeep LearningEmbedded SystemsGPU programmingMachine LearningPythonTestingalgorithm designbackend developmenttesting

Repositories Contributed To

2 repos

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

CodeLinaro/onnxruntime

Sep 2025 Jan 2026
2 Months active

Languages Used

C++Python

Technical Skills

API DevelopmentBackend DevelopmentC++C++ developmentDeep LearningGPU programming

ROCm/onnxruntime

Dec 2025 Dec 2025
1 Month active

Languages Used

C++

Technical Skills

C++algorithm designbackend development

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