openvinotoolkit/openvino
Dec 2024 – Aug 2025
3 Months active
Languages Used
C++Python
Technical Skills
Build Systems (CMake)Code GenerationCompute Model (CM)GPU ProgrammingKernel DevelopmentOpenCL
Jakub Kasprzak
PROFILE
Jakub Kasprzak
Jakub Kasprzak contributed to the openvinotoolkit/openvino repository by enabling Compute Model (CM) kernel support for Intel GPUs, reusing and extending existing OpenCL kernel management logic while ensuring clear separation of CM and OCL sources in code generation. He improved graph optimization by eliminating redundant reorder-permute patterns, updated CM LSTM output formats for better batch handling, and enhanced build reliability across platforms, including Windows. Jakub also addressed stability issues by gating the DynamicQuantizeFullyConnected optimization based on OneDNN availability. His work demonstrated depth in C++, GPU programming, and performance optimization, resulting in more robust, maintainable, and efficient GPU inference workflows.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
5Total
Bugs
2
Commits
5
Features
2
Lines of code
629
Activity Months3
Your Network
2005 people
Work History
August 2025
1 Commits
Aug 1, 2025Month 2025-08: Stability-focused fix in OpenVINO by gating the DynamicQuantizeFullyConnected optimization when OneDNN is unavailable, preventing OpenCL/dynamic quantization failures with zero-dimension shapes and improving reliability for GPU workloads.
1 Commits
Aug 1, 2025Month 2025-08: Stability-focused fix in OpenVINO by gating the DynamicQuantizeFullyConnected optimization when OneDNN is unavailable, preventing OpenCL/dynamic quantization failures with zero-dimension shapes and improving reliability for GPU workloads.
August 2025
March 2025
3 Commits • 1 Features
Mar 1, 2025March 2025: Delivered performance and reliability improvements for the openvino repository, focusing on graph-level optimization and cross-platform build stability. Key changes include a targeted graph optimization to eliminate redundant reorder-permute patterns and a CM LSTM output format update, enabling batch=1 processing and smoother handoff to subsequent LSTM layers. Also completed JIT/build hygiene and Windows compatibility improvements to reduce noise and ensure smoother CI/builds across platforms. Overall impact: faster inference for edge/model workloads, easier integration and maintenance, and more predictable builds on Windows.
March 2025
3 Commits • 1 Features
Mar 1, 2025March 2025: Delivered performance and reliability improvements for the openvino repository, focusing on graph-level optimization and cross-platform build stability. Key changes include a targeted graph optimization to eliminate redundant reorder-permute patterns and a CM LSTM output format update, enabling batch=1 processing and smoother handoff to subsequent LSTM layers. Also completed JIT/build hygiene and Windows compatibility improvements to reduce noise and ensure smoother CI/builds across platforms. Overall impact: faster inference for edge/model workloads, easier integration and maintenance, and more predictable builds on Windows.
December 2024
1 Commits • 1 Features
Dec 1, 2024For 2024-12, delivered Compute Model (CM) kernel support for Intel GPUs in openvino. Reuses existing OpenCL (OCL) kernel selection, caching, and compilation logic, while clearly differentiating CM sources from OCL in the primitive database and code generation. Included an example CM print kernel for the fully_connected primitive and accompanying unit tests. No outstanding critical bugs observed this month; CI and local tests pass.
1 Commits • 1 Features
Dec 1, 2024For 2024-12, delivered Compute Model (CM) kernel support for Intel GPUs in openvino. Reuses existing OpenCL (OCL) kernel selection, caching, and compilation logic, while clearly differentiating CM sources from OCL in the primitive database and code generation. Included an example CM print kernel for the fully_connected primitive and accompanying unit tests. No outstanding critical bugs observed this month; CI and local tests pass.
December 2024
Activity
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Quality Metrics
Correctness92.0%
Maintainability88.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Build Systems (CMake)C++Code GenerationCompiler OptimizationCompute Model (CM)Deep LearningDriver DevelopmentGPU ComputingGPU ProgrammingGraph OptimizationKernel DevelopmentOpenCLPerformance OptimizationPlugin Development
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