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
Worked on the google/XNNPACK repository to deliver SME2-optimized ARM64 GEMM microkernels for the qp8_f32_qc8w operation, targeting performance improvements in matrix multiplication for machine learning workloads. The approach involved implementing SME2 support in the GEMM path, expanding gemm-config, and extending both unit tests and benchmarks to validate the new microkernels on SME2-capable devices. Using ARM Assembly and C, the work focused on embedded systems and machine learning acceleration, resulting in enhanced throughput and reduced inference latency. The integration was committed and is ready for deployment in performance-critical environments, reflecting a deep focus on performance optimization and hardware efficiency.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
178
Activity Months1
Your Network
594 peopleSame Organization
@arm.com538
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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