Memory disaggregation architecture presents unique challenges in ensuring data consistency due to the limited computational power available at memory servers. One line of pessimistic solutions utilizes lock tables to deal with this challenge. Since the lock release signal cannot be immediately synchronized to the compute server, such solutions can only achieve suboptimal memory utilization. To address the aforementioned limitation, another line of solutions operates optimistically, polling the memory server until the operation completes successfully. However, these solutions trigger a massive number of unnecessary retries, resulting in performance collapse in high contention scenarios.high memory utilization while avoiding the need for retries. Our key idea is that compute servers proactively predict the appropriate retry interval and schedule accordingly. By analyzing the properties of requests on memory disaggregation, we find that the retry interval mainly consists of network fluctuations and host congestion delay. ECC design builds upon insights gained from this analysis. We have integrated ECC into Clover—a state-of-the-art memory disaggregation system and evaluated it through simulations and testbed experiments. Our testbed results show that ECC improves throughput by 50.8% over Clover.

Summary This paper focuses on the topology structure of interconnection networks. To overcome drawbacks in the existing hypercube structure, we present an exchanged folded hypercube (EFH) structure, which is an improvement of the exchanged hypercube. Compared with the existing hypercube structures, EFH shows better performance in terms of many metrics such as smaller diameter, lower cost factor, and constant node degree. In this paper, we first introduce the structure of an EFH; then, we propose a routing algorithm and a load‐balancing algorithm for EFHs. Finally, we analyze the fault tolerance characteristics of EFHs including fault diameter and the cost effectiveness factor. Copyright © 2015 John Wiley & Sons, Ltd.