The intelligent memory allocator selector

• Published in: Computer languages, systems & structures systems & structures, 2015-12, Vol.44, p.342-354
• Main Authors: Ülgen, Onur, Avci, Mutlu
• Format: Article
• Language: English
• Subjects: Balancing; Collectors; Computer programs; Fragmentation; Garbage collection; Mathematical models; Memory allocator; Memory fragmentation; Operating systems; Selectors; Software; Virtual machine
• ISSN: 1477-8424; 1873-6866
• DOI: 10.1016/j.cl.2015.09.003

Memory fragmentation is a serious obstacle preventing efficient memory usage. Garbage collectors may solve the problem; however, they cause serious performance impact, memory and energy consumption. Therefore, various memory allocators have been developed. Software developers must test memory allocators, and find an efficient one for their programs. Instead of this cumbersome method, we propose a novel approach for dynamically deciding the best memory allocator for every application. The proposed solution tests each process with various memory allocators. After the testing, it selects an efficient memory allocator according to condition of operating system (OS). If OS runs out of memory, then it selects the most memory efficient allocator for new processes. If most of the CPU power was occupied, then it selects the fastest allocator. Otherwise, the balanced allocator is selected. According to test results, the proposed solution offers up to 58% less fragmented memory, and 90% faster memory operations. In average of 107 processes, it offers 7.16±2.53% less fragmented memory, and 1.79±7.32% faster memory operations. The test results also prove the proposed approach is unbeatable by any memory allocator. In conclusion, the proposed method is a dynamic and efficient solution to the memory fragmentation problem. •Our solution is an intelligent memory allocator selector for operating systems.•The solution selects an efficient and fastest memory allocator for each process.•The approach reduces memory fragmentation, and increases system performance.•Our solution is a dynamic and efficient solution to memory fragmentation problem.