microsoft/olive-recipes
Oct 2025 – Oct 2025
1 Month active
Languages Used
BashMarkdownYAML
Technical Skills
Configuration ManagementDevOpsGPU ComputingModel OptimizationQuantization
vjatoth-qti
PROFILE
Vjatoth-qti
Vjatoth Toth developed QNN-GPU execution support for the microsoft/olive-recipes repository, enabling GPU-accelerated model inference through the QNN Execution Provider. By updating both documentation and model configuration files in Markdown and YAML, Vjatoth ensured that QNN-GPU optimization and compilation settings were clearly reflected across multiple models. The work enforced compatibility with a specific Olive commit, supporting reproducible and stable deployments. Leveraging skills in configuration management, DevOps, and GPU computing, Vjatoth’s contributions improved the scalability and performance of Olive-based workflows, laying the groundwork for future GPU-enabled throughput enhancements while maintaining traceability and reliability in the deployment process.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
813
Activity Months1
Your Network
105 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025Implemented QNN-GPU execution support in Olive recipes (via QNN-EP) to enable GPU-accelerated model execution, updated docs and model configs for multiple models to reflect QNN-GPU optimization and compilation settings, and enforced compatibility with a referenced Olive commit for reliable deployments. This work, linked to commit 5a0958d9af7317f3155227cb9dde20b9b62d9d96, enhances performance, scalability, and reproducibility of Olive-based workflows.
1 Commits • 1 Features
Oct 1, 2025Implemented QNN-GPU execution support in Olive recipes (via QNN-EP) to enable GPU-accelerated model execution, updated docs and model configs for multiple models to reflect QNN-GPU optimization and compilation settings, and enforced compatibility with a referenced Olive commit for reliable deployments. This work, linked to commit 5a0958d9af7317f3155227cb9dde20b9b62d9d96, enhances performance, scalability, and reproducibility of Olive-based workflows.
October 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashMarkdownYAML
Technical Skills
Configuration ManagementDevOpsGPU ComputingModel OptimizationQuantization
Repositories Contributed To
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