libsdl-org/highway
Nov 2024 – Nov 2024
1 Month active
Languages Used
AssemblyC++JavaScriptMarkdown
Technical Skills
ARM SVEC++C++ DevelopmentC++ Template MetaprogrammingC++ developmentC++ metaprogramming
Mohammad Azim Khan
PROFILE
Mohammad Azim Khan
Developed a comprehensive suite of Unified Vector Math Enhancements for the libsdl-org/highway repository, focusing on expanding the library’s capabilities for high-performance numeric workloads. Leveraging C++ and ARM SVE, the work introduced new vector arithmetic primitives, complex number support, and floating-point promotion and demotion with rounding modes, all designed to improve expressiveness and accuracy in SIMD programming. The implementation included masked arithmetic, granular multiplication, and advanced bit manipulation, with extensive unit testing and documentation to ensure reliability. This feature set established a robust foundation for broader hardware support and streamlined the development of math-intensive applications requiring low-level optimization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
1
Lines of code
4,477
Activity Months1
Your Network
48 peopleSame Organization
@cambridgeconsultants.com1
Work History
November 2024
13 Commits • 1 Features
Nov 1, 2024November 2024 focused on delivering a cohesive Unified Vector Math Enhancements feature set for the highway library (libsdl-org/highway), establishing a strong foundation for high-performance numeric workloads. The work encompassed API breadth, correctness, and documentation to support broader hardware coverage and faster time-to-market for math-intensive features.
13 Commits • 1 Features
Nov 1, 2024November 2024 focused on delivering a cohesive Unified Vector Math Enhancements feature set for the highway library (libsdl-org/highway), establishing a strong foundation for high-performance numeric workloads. The work encompassed API breadth, correctness, and documentation to support broader hardware coverage and faster time-to-market for math-intensive features.
November 2024
Activity
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Quality Metrics
Correctness100.0%
Maintainability98.4%
Architecture98.4%
Performance97.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
AssemblyC++JavaScriptMarkdown
Technical Skills
ARM SVEC++C++ DevelopmentC++ Template MetaprogrammingC++ developmentC++ metaprogrammingC++ template metaprogrammingDocumentationLow-level OptimizationLow-level optimizationLow-level programmingNumerical computationPerformance OptimizationPerformance optimizationSIMD
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