oneapi-src/oneDNN
Apr 2026 – Apr 2026
1 Month active
Languages Used
C++
Technical Skills
JIT compilationRISC-V architectureconvolutional neural networkshigh-performance computing
Alexandre de Limas Santana
PROFILE
Alexandre De Limas Santana
Alexandre Delima Santana developed a vector-length-agnostic JIT 1x1 convolution kernel for the oneapi-src/oneDNN repository, targeting RISC-V’s RVV architecture. His work focused on enabling portable, high-performance convolutional neural network operations across varying vector lengths, addressing the challenge of hardware diversity. Using C++ and leveraging expertise in JIT compilation and high-performance computing, Alexandre introduced new format tags and updated memory descriptor handling to ensure correct data layout and efficient memory access. These architectural improvements enhanced both scalability and maintainability of the kernel and memory model, providing a robust foundation for future development and broader RVV support within oneDNN.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
213
Activity Months1
Your Network
90 peopleSame Organization
@bsc.es13
Work History
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for oneDNN: Delivered a vector-length-agnostic JIT 1x1 convolution kernel for RVV, enabling portable performance across RVV vector lengths and laying groundwork for scalable maintainable code. Implemented new format tags and updated memory descriptor handling to fully support the kernel, resulting in improved efficiency on diverse hardware profiles. The work enhances throughput for typical CNN scenarios and contributes to broader RVV portability and maintainability of the kernel and memory model.
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for oneDNN: Delivered a vector-length-agnostic JIT 1x1 convolution kernel for RVV, enabling portable performance across RVV vector lengths and laying groundwork for scalable maintainable code. Implemented new format tags and updated memory descriptor handling to fully support the kernel, resulting in improved efficiency on diverse hardware profiles. The work enhances throughput for typical CNN scenarios and contributes to broader RVV portability and maintainability of the kernel and memory model.
April 2026
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
C++
Technical Skills
JIT compilationRISC-V architectureconvolutional neural networkshigh-performance computing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline