Spirit: Fair Allocation of Interdependent Resources in Remote Memory Systems
SeungSeob Lee, Jachym Putta, Ziming Mao, Anurag Khandelwal
Abstract
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.
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Cited by top-tier papers3
- Break On Through to the Other Side: Pooling Memory Elastically with RamRyderYanbo Zhou, Erci Xu, Dongjoo Seo, Adam Manzanares et al.OSDI 2026
- Efficient and Scalable Synchronization via Generalized Cache CoherenceYanpeng Yu, Seung-seob Lee, Lin Zhong, Anurag KhandelwalOSDI 2026
- Cache-Centric Multi-Resource Allocation for Storage ServicesChenhao Ye, Shawn Zhong, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-DusseauFAST 2026
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