ROCm/rocm-libraries
Sep 2025 – Sep 2025
1 Month active
Languages Used
C++HIPOpenCL
Technical Skills
Code PortingGPU ComputingHIPKernel DevelopmentOpenCLPerformance Optimization
Dmitrii Polomin
PROFILE
Dmitrii Polomin
During September 2025, this developer ported the Op4dTensorLite kernel from OpenCL to HIP within the ROCm/rocm-libraries repository, enabling HIP-based execution and expanding hardware compatibility. The work involved adapting vector types and block sizes to address miopenHalf support challenges in HIP, as well as updating kernel implementations and helper functions to align with HIP architecture. By focusing on code porting, GPU computing, and performance optimization using C++, HIP, and OpenCL, the developer preserved both functionality and performance. This contribution reduced platform fragmentation and facilitated broader adoption of HIP-enabled hardware, enhancing the overall flexibility and reach of the ROCm ecosystem.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
197
Activity Months1
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142 peopleSame Organization
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Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for ROCm/rocm-libraries: Delivered the HIP backend port for Op4dTensorLite kernel (OpenCL to HIP), enabling HIP-based execution for this path and expanding hardware support. The change preserves functionality and performance while addressing miopenHalf support challenges in HIP by adapting vector types and block sizes and by updating kernel implementations and helper functions to align with HIP architecture. This work reduces platform fragmentation and accelerates customer adoption of HIP-enabled hardware.
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for ROCm/rocm-libraries: Delivered the HIP backend port for Op4dTensorLite kernel (OpenCL to HIP), enabling HIP-based execution for this path and expanding hardware support. The change preserves functionality and performance while addressing miopenHalf support challenges in HIP by adapting vector types and block sizes and by updating kernel implementations and helper functions to align with HIP architecture. This work reduces platform fragmentation and accelerates customer adoption of HIP-enabled hardware.
September 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++HIPOpenCL
Technical Skills
Code PortingGPU ComputingHIPKernel DevelopmentOpenCLPerformance Optimization
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