google/XNNPACK
Jun 2025 – Jun 2025
1 Month active
Languages Used
CCMakeStarlark
Technical Skills
ARM AssemblyEmbedded SystemsMachine Learning AccelerationPerformance Optimization
Gian Marco Iodice
PROFILE
Gian Marco Iodice
Gianmarco Iodice developed SME2-optimized ARM64 GEMM microkernels for the qp8_f32_qc8w path in the google/XNNPACK repository, targeting performance-critical machine learning workloads. He implemented SME2 support by expanding the GEMM configuration and integrating new microkernels using ARM Assembly and C, with build management via CMake. His work included extending unit tests and benchmarks to validate the new SME2-optimized path on supported hardware, ensuring improved throughput and reduced inference latency for matrix multiplication. The depth of engineering addressed both integration and validation, resulting in a robust enhancement for ML acceleration on SME2-capable embedded systems within the XNNPACK framework.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
178
Activity Months1
Your Network
518 people
Work History
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for google/XNNPACK focusing on SME2-optimized ARM64 GEMM microkernels for qp8_f32_qc8w. Implemented SME2 support in the qp8_f32_qc8w GEMM path, expanded gemm-config, and extended the unit tests and benchmarks to cover the new SME2-optimized microkernels. The work validated on SME2-capable devices and is ready for deployment in performance-critical ML workloads.
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for google/XNNPACK focusing on SME2-optimized ARM64 GEMM microkernels for qp8_f32_qc8w. Implemented SME2 support in the qp8_f32_qc8w GEMM path, expanded gemm-config, and extended the unit tests and benchmarks to cover the new SME2-optimized microkernels. The work validated on SME2-capable devices and is ready for deployment in performance-critical ML workloads.
June 2025
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CCMakeStarlark
Technical Skills
ARM AssemblyEmbedded SystemsMachine Learning AccelerationPerformance Optimization
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