Near-Memory Processing Offload to Remote (Persistent) Memory

Roei Kisous, Amit Golander, Yigal Korman, Tim Gubner, Rune Humborstad, Manyi Lu
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Abstract

Traditional Von Neumann computing architectures are struggling to keep up with the rapidly growing demand for scale, performance, power-efficiency and memory capacity. One promising approach to this challenge is Remote Memory, in which the memory is over RDMA fabric [1]. We enhance the remote memory architecture with Near Memory Processing (NMP), a capability that offloads particular compute tasks from the client to the server side as illustrated in Figure 1. Similar motivation drove IBM to offload object processing to their remote KV storage [2]. NMP offload adds latency and server resource costs, therefore, it should only be used when the offload value is substantial, specifically, to save: network bandwidth (e.g. Filter/Aggregate), round trip time (e.g. tree Lookup) and/or distributed locks (e.g. Append to a shared journal).
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近内存处理卸载到远程(持久)内存
传统的冯·诺伊曼计算架构正在努力跟上对规模、性能、能效和内存容量快速增长的需求。解决这一挑战的一个有希望的方法是远程内存,其中内存通过RDMA结构[1]。我们使用近内存处理(NMP)增强了远程内存体系结构,NMP是一种将特定的计算任务从客户机卸载到服务器端的功能,如图1所示。类似的动机促使IBM将对象处理工作卸载到远程KV存储器中[2]。NMP卸载增加了延迟和服务器资源成本,因此,它应该只在卸载值较大时使用,特别是为了节省:网络带宽(例如Filter/Aggregate)、往返时间(例如树查找)和/或分布式锁(例如追加到共享日志)。
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