pytorch/FBGEMM
Jun 2025 – Jul 2025
2 Months active
Languages Used
C++CUDA
Technical Skills
C++CUDAGPU ProgrammingPerformance Optimization
Haoqiang Guo
PROFILE
Haoqiang Guo
During June and July 2025, Haoqiang Guo developed and optimized AMD GPU kernels for the pytorch/FBGEMM repository, focusing on reordering batched ad indices to improve throughput for data-intensive workloads. He implemented a vectorized kernel, reorder_batched_ad_indices_kernel_vec, supporting Long and float data types with a broadcast_indices option, and introduced AMD-specific thread block sizing and conditional logic for multiple data types. Using C++, CUDA, and GPU programming techniques, Haoqiang’s work enhanced compute utilization and cross-architecture performance parity, particularly for large product length and ad count scenarios, demonstrating depth in performance optimization and hardware-aware kernel design without reported bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
150
Activity Months2
Your Network
2401 people
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 Monthly Summary (pytorch/FBGEMM) This month focused on AMD-optimized kernel enhancements to improve performance for reordering batched ad indices, targeting workloads with large product lengths and high ad counts. The work emphasizes compute utilization on AMD GPUs through vectorized kernel pathways and data-type aware configurations, laying groundwork for broader hardware-specific performance gains in FB-GEMM.
1 Commits • 1 Features
Jul 1, 2025July 2025 Monthly Summary (pytorch/FBGEMM) This month focused on AMD-optimized kernel enhancements to improve performance for reordering batched ad indices, targeting workloads with large product lengths and high ad counts. The work emphasizes compute utilization on AMD GPUs through vectorized kernel pathways and data-type aware configurations, laying groundwork for broader hardware-specific performance gains in FB-GEMM.
July 2025
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Focused AMD optimization within FBGEMM. Delivered a vectorized AMD-specific kernel reorder_batched_ad_indices_kernel_vec for reordering batched ad indices, with support for Long and float data types and a broadcast_indices option. This work is recorded under commit 8ba51842cb2a3c143cd93a0ee8ea54a69893c159 in pytorch/FBGEMM. No major bugs reported for this period; the feature enhances throughput for data-heavy workloads on AMD hardware and strengthens cross-arch performance parity.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Focused AMD optimization within FBGEMM. Delivered a vectorized AMD-specific kernel reorder_batched_ad_indices_kernel_vec for reordering batched ad indices, with support for Long and float data types and a broadcast_indices option. This work is recorded under commit 8ba51842cb2a3c143cd93a0ee8ea54a69893c159 in pytorch/FBGEMM. No major bugs reported for this period; the feature enhances throughput for data-heavy workloads on AMD hardware and strengthens cross-arch performance parity.
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CUDA
Technical Skills
C++CUDAGPU ProgrammingPerformance Optimization
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