openvinotoolkit/openvino
Jul 2025 – Nov 2025
2 Months active
Languages Used
C++C
Technical Skills
Broadcasting LogicDeep Learning FrameworksGPU ProgrammingOperator ImplementationOpenCLPerformance Optimization
Prithviraj-R
PROFILE
Prithviraj-r
Prithviraj R. contributed to the openvinotoolkit/openvino repository by enhancing GPU operator reliability and flexibility over a three-month period. He addressed edge-case failures in GPU Leaky ReLU (PReLU) by aligning broadcasting logic with NumPy rules using C++ and OpenCL, improving model compatibility and inference stability. Prithviraj also expanded Rotary Position Embedding (RoPE) support by enabling by-channel de-quantization and re-quantization in the KV_CACHE_ROTATE OCL kernel, increasing transformer workload flexibility. Additionally, he stabilized MVN fusion by refining self-multiply square handling and updating pattern matching logic, leveraging algorithm optimization and unit testing to ensure robust operator performance.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
3Total
Bugs
2
Commits
3
Features
1
Lines of code
230
Activity Months3
Your Network
2249 peopleSame Organization
@intel.com1996
Work History
March 2026
1 Commits
Mar 1, 2026In March 2026, the MVN fusion path was stabilized by fixing square handling implemented via self-multiply, enabling the optimized MVN operator path and reducing edge-case failures in MVNFusion. This work included adding test coverage to validate the self-multiply square scenario and updating the MVNFusionWithoutConstants matching logic.
1 Commits
Mar 1, 2026In March 2026, the MVN fusion path was stabilized by fixing square handling implemented via self-multiply, enabling the optimized MVN operator path and reducing edge-case failures in MVNFusion. This work included adding test coverage to validate the self-multiply square scenario and updating the MVNFusionWithoutConstants matching logic.
March 2026
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary. Focused on expanding RoPE support in the OpenVINO GPU back-end by enabling by-channel de-quantization and re-quantization within the KV_CACHE_ROTATE OCL kernel. This work improves RoPE handling for by-channel quantized key caches, increasing flexibility and potential performance for transformer workloads.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary. Focused on expanding RoPE support in the OpenVINO GPU back-end by enabling by-channel de-quantization and re-quantization within the KV_CACHE_ROTATE OCL kernel. This work improves RoPE handling for by-channel quantized key caches, increasing flexibility and potential performance for transformer workloads.
July 2025
1 Commits
Jul 1, 2025July 2025 monthly summary: Delivered a critical GPU-side fix for Leaky ReLU (PReLU) broadcasting, ensuring correct behavior when a 1D slope input is used and aligning with NumPy broadcasting rules. This improves accuracy, stability, and compatibility of OpenVINO's GPU plugins for models using PReLU. The fix reduces edge-case failures and broadens deployment scenarios across GPU backends.
1 Commits
Jul 1, 2025July 2025 monthly summary: Delivered a critical GPU-side fix for Leaky ReLU (PReLU) broadcasting, ensuring correct behavior when a 1D slope input is used and aligning with NumPy broadcasting rules. This improves accuracy, stability, and compatibility of OpenVINO's GPU plugins for models using PReLU. The fix reduces edge-case failures and broadens deployment scenarios across GPU backends.
July 2025
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Quality Metrics
Correctness93.4%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage26.6%
Skills & Technologies
Programming Languages
CC++
Technical Skills
Broadcasting LogicC++ programmingDeep Learning FrameworksGPU ProgrammingOpenCLOperator ImplementationPerformance Optimizationalgorithm optimizationunit testing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
aobolensk/openvino
Mar 2026 – Mar 2026
1 Month active
Languages Used
C++
Technical Skills
C++ programmingalgorithm optimizationunit testing