oneapi-src/oneDNN
Mar 2025 – Mar 2025
1 Month active
Languages Used
CC++
Technical Skills
ARM ArchitectureCPU OptimizationEmbedded SystemsMachine Learning LibrariesPerformance Engineering
manjam01
PROFILE
Manjam01
Developed ACL Layer Normalization support for AArch64 within the oneapi-src/oneDNN repository, focusing on enhancing inference performance and hardware compatibility. The work involved updating the ACL minimum version to 25.02 to enable stateless LayerNorm, refactoring the implementation to leverage the experimental CpuMeanStdDevNormalization operator, and introducing comprehensive tensor dimension and data type validation. Performance heuristics were added, and the code was adapted to support channel-last formats and broader configuration validation. Utilizing C and C++ with expertise in ARM architecture and performance engineering, this contribution improved maintainability, correctness, and the overall flexibility of machine learning workloads on embedded systems.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
406
Activity Months1
Your Network
617 peopleSame Organization
@arm.com538
Work History
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025: Delivered ACL Layer Normalization support on AArch64 in oneDNN by enabling stateless LayerNorm through an ACL 25.02 minimum version update. Refactored to utilize the experimental CpuMeanStdDevNormalization operator, added tensor dimension and data type validation, introduced performance heuristics, and adapted the codepaths for channel-last formats and broader configuration validation. This work broadens hardware support, improves inference performance, and enhances correctness and maintainability.
1 Commits • 1 Features
Mar 1, 2025March 2025: Delivered ACL Layer Normalization support on AArch64 in oneDNN by enabling stateless LayerNorm through an ACL 25.02 minimum version update. Refactored to utilize the experimental CpuMeanStdDevNormalization operator, added tensor dimension and data type validation, introduced performance heuristics, and adapted the codepaths for channel-last formats and broader configuration validation. This work broadens hardware support, improves inference performance, and enhances correctness and maintainability.
March 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CC++
Technical Skills
ARM ArchitectureCPU OptimizationEmbedded SystemsMachine Learning LibrariesPerformance Engineering
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