![[2512.07841] Impact of Data-Oriented and Object-Oriented Design on Performance and Cache Utilization with Artificial Intelligence Algorithms in Multi-Threaded CPUs](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2512.07841] Impact of Data-Oriented and Object-Oriented Design on Performance and Cache Utilization with Artificial Intelligence Algorithms in Multi-Threaded CPUs
Summary
This article analyzes the performance and cache utilization of Data-Oriented Design (DOD) versus Object-Oriented Design (OOD) in multi-threaded CPUs, particularly in AI algorithms like A* search.
Why It Matters
Understanding the performance implications of different software design paradigms is crucial for optimizing AI applications, especially as hardware capabilities evolve. This research highlights DOD's advantages in cache efficiency and execution speed, which are vital for developing high-performance AI systems.
Key Takeaways
- DOD outperforms OOD in multi-threaded environments for AI algorithms.
- Performance gains in DOD are evident through reduced cache misses and faster execution times.
- Single-threaded implementations showed better performance than multi-threaded due to overhead in thread management.
- DOD is recommended for maximizing hardware efficiency in complex AI tasks.
- The study emphasizes the importance of hardware-aware software design.
Computer Science > Artificial Intelligence arXiv:2512.07841 (cs) [Submitted on 22 Nov 2025 (v1), last revised 13 Feb 2026 (this version, v2)] Title:Impact of Data-Oriented and Object-Oriented Design on Performance and Cache Utilization with Artificial Intelligence Algorithms in Multi-Threaded CPUs Authors:Gabriel M. Arantes, Giancarlo Lucca, Eduardo N. Borges, Richard F. Pinto, Bruno L. Dalmazo, Rafael A. Berri View a PDF of the paper titled Impact of Data-Oriented and Object-Oriented Design on Performance and Cache Utilization with Artificial Intelligence Algorithms in Multi-Threaded CPUs, by Gabriel M. Arantes and 4 other authors View PDF HTML (experimental) Abstract:The growing performance gap between multi-core CPUs and main memory necessitates hardware-aware software design paradigms. This study provides a comprehensive performance analysis of Data Oriented Design (DOD) versus the traditional Object-Oriented Design (OOD), focusing on cache utilization and efficiency in multi-threaded environments. We developed and compared four distinct versions of the A* search algorithm: single-threaded OOD (ST-OOD), single-threaded DOD (ST-DOD), multi-threaded OOD (MT-OOD), and multi-threaded DOD (MT-DOD). The evaluation was based on metrics including execution time, memory usage, and CPU cache misses. In multi-threaded tests, the DOD implementation demonstrated considerable performance gains, with faster execution times and a lower number of raw system calls and cache misses. Whil...
