getsolus/packages
Sep 2025 – Dec 2025
2 Months active
Languages Used
CC++CMakePythonYAML
Technical Skills
Package ManagementSystem ProgrammingBuild system configurationC++ developmentDeep learningGLIBC
Jacek Jagosz
PROFILE
Jacek Jagosz
Jacek Jagosz contributed to the getsolus/packages repository by enabling ROCm support for PyTorch and its ecosystem, addressing core build and compatibility challenges. He upgraded iio-sensor-proxy to stabilize sensor data processing, resolving a buffer regression and improving device reliability. For PyTorch, Jacek implemented LLVM and glibc compatibility fixes, introduced device-specific assertion handling, and managed ABI updates to ensure seamless ROCm integration for torchvision and torchaudio. His work involved C++ and Python development, build system configuration, and package management. These contributions broadened hardware compatibility, improved system stability, and reduced barriers for deploying deep learning workloads on ROCm-enabled GPUs.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
5Total
Bugs
1
Commits
5
Features
2
Lines of code
4,885
Activity Months2
Your Network
47 peopleShared Repositories
47
Work History
December 2025
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for getsolus/packages focused on expanding ROCm support for PyTorch and its ecosystem, delivering core build readiness and ecosystem compatibility fixes that unlock ROCm-based AI workflows. Key features delivered: - ROCm-enabled PyTorch core build with LLVM/glibc compatibility fixes: enabled building PyTorch core under ROCm by addressing LLVM/glibc compatibility issues, adding device-specific assertion variants and necessary headers to resolve compilation errors, improving stability and ROCm maturity. Commits: ffdb2d772180f65a0d6cfc1bed3596519f14357d; cf9ffa928f14d8ad8628b8383c3a71a89b04baf5. - ROCm-enabled PyTorch ecosystem packages: torchvision and torchaudio: added ROCm support through ABI/library updates and maintained symbols, ensuring ROCm compatibility for the ecosystem. Commits: 2c25ecf2b54426fe413f944f6e6f79e9cfc96a19; 33d18edd4210ef170a56d7c5ddeff8cbf9ad10f4. Major bugs fixed: - rocm-llvm: Fixed build with newest LLVM, glibc and glibcxx assert fail, enabling PyTorch build under ROCm (summary: Resolve build blockers for ROCm PyTorch; relates to issue #6742). Commit: ffdb2d772180f65a0d6cfc1bed3596519f14357d. - pytorch build enablement under ROCm: Ensured the PyTorch build can target ROCm, addressing compatibility gaps and enabling stable builds. Commit: cf9ffa928f14d8ad8628b8383c3a71a89b04baf5. Overall impact and accomplishments: - Broadened hardware compatibility and readiness for ROCm deployments by delivering core ROCm support and ecosystem packaging improvements, enabling customers to run PyTorch workloads on ROCm-enabled GPUs with improved stability and performance visibility. Strengthened maintenance surface for ROCm in the getsolus/packages suite and reduced time-to-market for ROCm migrations. Technologies/skills demonstrated: - C/C++ build system work, ROCm, PyTorch internals, LLVM/glibc ABI compatibility, header management, device-specific assertion handling, multi-repo coordination, and package lifecycle management (rebuilds and ABI upkeep).
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for getsolus/packages focused on expanding ROCm support for PyTorch and its ecosystem, delivering core build readiness and ecosystem compatibility fixes that unlock ROCm-based AI workflows. Key features delivered: - ROCm-enabled PyTorch core build with LLVM/glibc compatibility fixes: enabled building PyTorch core under ROCm by addressing LLVM/glibc compatibility issues, adding device-specific assertion variants and necessary headers to resolve compilation errors, improving stability and ROCm maturity. Commits: ffdb2d772180f65a0d6cfc1bed3596519f14357d; cf9ffa928f14d8ad8628b8383c3a71a89b04baf5. - ROCm-enabled PyTorch ecosystem packages: torchvision and torchaudio: added ROCm support through ABI/library updates and maintained symbols, ensuring ROCm compatibility for the ecosystem. Commits: 2c25ecf2b54426fe413f944f6e6f79e9cfc96a19; 33d18edd4210ef170a56d7c5ddeff8cbf9ad10f4. Major bugs fixed: - rocm-llvm: Fixed build with newest LLVM, glibc and glibcxx assert fail, enabling PyTorch build under ROCm (summary: Resolve build blockers for ROCm PyTorch; relates to issue #6742). Commit: ffdb2d772180f65a0d6cfc1bed3596519f14357d. - pytorch build enablement under ROCm: Ensured the PyTorch build can target ROCm, addressing compatibility gaps and enabling stable builds. Commit: cf9ffa928f14d8ad8628b8383c3a71a89b04baf5. Overall impact and accomplishments: - Broadened hardware compatibility and readiness for ROCm deployments by delivering core ROCm support and ecosystem packaging improvements, enabling customers to run PyTorch workloads on ROCm-enabled GPUs with improved stability and performance visibility. Strengthened maintenance surface for ROCm in the getsolus/packages suite and reduced time-to-market for ROCm migrations. Technologies/skills demonstrated: - C/C++ build system work, ROCm, PyTorch internals, LLVM/glibc ABI compatibility, header management, device-specific assertion handling, multi-repo coordination, and package lifecycle management (rebuilds and ABI upkeep).
December 2025
September 2025
1 Commits
Sep 1, 2025In September 2025, focused on stabilizing sensor data processing in getsolus/packages. A targeted bug fix addressed a regression in buffer sensor handling by upgrading iio-sensor-proxy from 3.7 to 3.8, resulting in improved stability and reliability of sensor data processing across supported devices. The change minimizes data anomalies and contributes to a smoother user experience for sensor-driven features.
September 2025
1 Commits
Sep 1, 2025In September 2025, focused on stabilizing sensor data processing in getsolus/packages. A targeted bug fix addressed a regression in buffer sensor handling by upgrading iio-sensor-proxy from 3.7 to 3.8, resulting in improved stability and reliability of sensor data processing across supported devices. The change minimizes data anomalies and contributes to a smoother user experience for sensor-driven features.
Activity
Loading activity data...
Quality Metrics
Correctness88.0%
Maintainability80.0%
Architecture84.0%
Performance76.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CC++CMakePythonYAML
Technical Skills
Build system configurationC++ developmentDeep learningGLIBCGPU programmingLLVMLibrary developmentLibrary packagingPackage ManagementPackage managementPython developmentSystem Programmingbuild system configuration
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline