ROCm/pytorch
Jun 2025 – Oct 2025
4 Months active
Languages Used
C++YAMLPython
Technical Skills
C++PyTorchbackend developmentdevice compatibilitydevice managementdevice support integration
Andy (An) Wang
PROFILE
Andy (an) Wang
An Wang developed and integrated MTIA backend features across the graphcore/pytorch-fork and ROCm/pytorch repositories, focusing on in-tree migration of core tensor operations and device interface enhancements. Using C++, Python, and PyTorch, An unified operator registrations, implemented kernel fusion guardrails, and expanded Inductor backend support for MTIA devices. The work included restoring device compatibility, optimizing performance, and adding comprehensive unit and integration tests to ensure stability. By addressing build issues and introducing configurable resource limits for kernel fusion, An improved maintainability and reliability of MTIA-backed workloads, enabling broader device support and laying the groundwork for future performance optimizations.
Overall Statistics
Feature vs Bugs
82%Features
Repository Contributions
38Total
Bugs
2
Commits
38
Features
9
Lines of code
907
Activity Months5
Your Network
2889 people
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025October 2025: Delivered guardrails for MTIA Triton fusion in ROCm/pytorch, enabling configurable resource limits to improve stability and predictability of kernel fusion. Implemented two config options (combo_kernel_max_num_args and max_fusion_unique_io_buffers) with accompanying tests for IO buffer limits. Changes primarily affect the Inductor fusion path and include targeted tests to validate guardrails under edge conditions.
2 Commits • 1 Features
Oct 1, 2025October 2025: Delivered guardrails for MTIA Triton fusion in ROCm/pytorch, enabling configurable resource limits to improve stability and predictability of kernel fusion. Implemented two config options (combo_kernel_max_num_args and max_fusion_unique_io_buffers) with accompanying tests for IO buffer limits. Changes primarily affect the Inductor fusion path and include targeted tests to validate guardrails under edge conditions.
October 2025
August 2025
3 Commits • 2 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on MTIA-focused ROCm/pytorch work, including new MTIA tensor backend features, device interface restoration, and stability fixes that collectively improve MTIA support and PyTorch performance on ROCm.
August 2025
3 Commits • 2 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on MTIA-focused ROCm/pytorch work, including new MTIA tensor backend features, device interface restoration, and stability fixes that collectively improve MTIA support and PyTorch performance on ROCm.
July 2025
9 Commits • 3 Features
Jul 1, 2025July 2025 performance summary focused on MTIA-driven backend modernization for ROCm/pytorch and Inductor integration across MTIA-enabled devices, with benchmarks updated to reflect the new backend coverage. The work lays a foundation for higher throughput on MTIA devices and broader PyTorch compatibility via Inductor.
9 Commits • 3 Features
Jul 1, 2025July 2025 performance summary focused on MTIA-driven backend modernization for ROCm/pytorch and Inductor integration across MTIA-enabled devices, with benchmarks updated to reflect the new backend coverage. The work lays a foundation for higher throughput on MTIA devices and broader PyTorch compatibility via Inductor.
July 2025
June 2025
20 Commits • 2 Features
Jun 1, 2025June 2025 performance summary: Led MTIA backend integration across two major PyTorch forks (graphcore/pytorch-fork and ROCm/pytorch), delivering broad MTIA-backed tensor operations, CPU fallback, and cross-backend support. Increased reliability via in-tree migrations and tests; resolved a compile-time issue, improving build stability. Business value: expanded device compatibility, improved performance, and reduced maintenance overhead.
June 2025
20 Commits • 2 Features
Jun 1, 2025June 2025 performance summary: Led MTIA backend integration across two major PyTorch forks (graphcore/pytorch-fork and ROCm/pytorch), delivering broad MTIA-backed tensor operations, CPU fallback, and cross-backend support. Increased reliability via in-tree migrations and tests; resolved a compile-time issue, improving build stability. Business value: expanded device compatibility, improved performance, and reduced maintenance overhead.
May 2025
4 Commits • 1 Features
May 1, 2025May 2025: Delivered MTIA backend migration into PyTorch core for graphcore/pytorch-fork, consolidating MTIA operators (including view, _unsafe_view, clamp ops, and as_strided) in-tree with explicit registrations. Added unit tests for as_strided and updated registrations to ensure correct wiring and performance. No separate bug fixes were required this month; migration reduces OSS divergence, improves maintainability, and enables more reliable kernel code generation and performance optimizations for MTIA workloads. Business impact includes tighter integration, easier maintenance, and a foundation for faster future MTIA feature delivery.
4 Commits • 1 Features
May 1, 2025May 2025: Delivered MTIA backend migration into PyTorch core for graphcore/pytorch-fork, consolidating MTIA operators (including view, _unsafe_view, clamp ops, and as_strided) in-tree with explicit registrations. Added unit tests for as_strided and updated registrations to ensure correct wiring and performance. No separate bug fixes were required this month; migration reduces OSS divergence, improves maintainability, and enables more reliable kernel code generation and performance optimizations for MTIA workloads. Business impact includes tighter integration, easier maintenance, and a foundation for faster future MTIA feature delivery.
May 2025
Activity
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Quality Metrics
Correctness94.4%
Maintainability93.6%
Architecture94.2%
Performance92.6%
AI Usage22.6%
Skills & Technologies
Programming Languages
C++PythonYAML
Technical Skills
Backend DevelopmentC++C++ developmentCUDACode ConfigurationCode OptimizationInductorKernel FusionMachine Learning FrameworksPerformance OptimizationPerformance TuningPyTorchPythonPython programmingTesting
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
graphcore/pytorch-fork
May 2025 – Jun 2025
2 Months active
Languages Used
C++PythonYAML
Technical Skills
C++PyTorchbackend developmentmachine learningunit testingC++ development
pytorch/benchmark
Jul 2025 – Jul 2025
1 Month active
Languages Used
Python
Technical Skills
Backend DevelopmentMachine Learning FrameworksPerformance Optimization