nod-ai/SHARK-Platform
Aug 2025 – Aug 2025
1 Month active
Languages Used
Python
Technical Skills
Machine Learning OperationsPerformance BenchmarkingPython ScriptingSystem Programming
bmullick-amd
PROFILE
Bmullick-amd
During August 2025, B. Mullick developed an SDXL Inference Benchmarking Tool for the nod-ai/SHARK-Platform repository. The tool automated the setup, execution, and measurement of Stable Diffusion XL inference across various configurations and devices, supporting customizable prompts, resolutions, and batch sizes. Built in Python and leveraging skills in machine learning operations and system programming, the solution established a standardized, reproducible workflow for benchmarking model performance. By enabling export-ready reporting and detailed timing metrics, Mullick’s work provided a foundation for data-driven optimization and cross-device comparison, addressing the need for consistent performance evaluation in machine learning inference environments on the SHARK-Platform.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
592
Activity Months1
Your Network
1323 people
Work History
August 2025
1 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for nod-ai/SHARK-Platform. Delivered an SDXL Inference Benchmarking Tool that enables scripted setup, execution, and measurement of Stable Diffusion XL inference across configurations and devices, with configurable prompts, resolutions, and parameters to evaluate efficiency. This tool establishes a standardized, repeatable benchmarking workflow to support optimization and cost/performance decisions.
1 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for nod-ai/SHARK-Platform. Delivered an SDXL Inference Benchmarking Tool that enables scripted setup, execution, and measurement of Stable Diffusion XL inference across configurations and devices, with configurable prompts, resolutions, and parameters to evaluate efficiency. This tool establishes a standardized, repeatable benchmarking workflow to support optimization and cost/performance decisions.
August 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Machine Learning OperationsPerformance BenchmarkingPython ScriptingSystem Programming
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