Spirit: Fair Allocation of Interdependent Resources in Remote Memory Systems

We address the problem of fair resource allocation in multiuser remote memory systems. Allocating local memory (used as cache) and network bandwidth to remote memory in such systems is challenging due to the complex interdependence between the two resources and application performance. A larger cache may reduce the need for fetching data over the network, while a larger bandwidth may permit more concurrent network requests, avoiding the need for large caches. As a result, applications can achieve the same data access throughput for a wide range of cache and bandwidth allocations. Such interdependence is unique to each application and hard to capture offline. We propose Spirit, a multi-user framework for fair resource allocation in remote memory systems. Spirit employs a novel Symbiosis algorithm rooted in microeconomic theory that takes application-specific dependency between cache and network bandwidth into account and 'trades' cache and bandwidth resources across users at runtime. We show, both theoretically and empirically, that Symbiosis allocations across users achieve strong fairness properties. Additionally, compared to traditional resource allocation schemes, Spirit improves performance by up to 21.6% across tens of real-world applications with diverse resource needs.