Hardware approach emerges as one of the candidate in improving the performance of dynamic memory management. This paper presents measurements of a self-maintained memory module subjected to several different workloads. This memory module supporting explicit dynamic memory management takes advantage of the high speed of a pure hardware implementation. Object allocation and deletion are strictly bounded in time. The whole heap space is divided into two semi-spaces, and a concurrent bidirectional memory compaction algorithm is exploited, so that memory compaction can be done while mutator process is running on the processor concurrently. Reported measurements demonstrate that hardware-assisted memory management is a viable alternative to traditional explicit memory management techniques. Experimental results show that more than 60% of memory traffic is saved by the proposed memory compaction scheme compared to software-only approach. Both processor delay and program execution time are greatly reduced.
Citation:
Weixing Ji, Feng Shi, Baojun Qiao, Qi Zuo, Caixia Liu, "Performance Evaluation of a Self-Maintained Memory Module," rtss, pp.254-266, 28th IEEE International Real-Time Systems Symposium (RTSS 2007), 2007