论文标题
具有启用RDMA的内存分解的分布式共享记忆数据库的情况
The Case for Distributed Shared-Memory Databases with RDMA-Enabled Memory Disaggregation
论文作者
论文摘要
内存分解（MD）允许通过将计算（CPU）与内存分开，可以扩展和弹性数据中心设计。使用MD，计算和内存不再耦合到同一服务器框中。相反，它们通过超快速网络（例如RDMA）相互连接。 MD可以带来许多优势，例如，更高的内存利用率，更好的独立规模（计算和内存）以及较低的所有权成本。本文使MD可以在数据库系统上推动下一步的创新浪潮。我们观察到，医学博士在数据库社区中复兴了“分享”的巨大辩论。我们设想，以前没有受到更多关注的分布共享内存数据库（DSM -DB，简称为DSM -DB），将来有希望使用MD。我们提出了一系列挑战和机遇的清单，可以激发系统设计的下一步，为DSM-DB提供了理由。
Memory disaggregation (MD) allows for scalable and elastic data center design by separating compute (CPU) from memory. With MD, compute and memory are no longer coupled into the same server box. Instead, they are connected to each other via ultra-fast networking such as RDMA. MD can bring many advantages, e.g., higher memory utilization, better independent scaling (of compute and memory), and lower cost of ownership. This paper makes the case that MD can fuel the next wave of innovation on database systems. We observe that MD revives the great debate of "shared what" in the database community. We envision that distributed shared-memory databases (DSM-DB, for short) - that have not received much attention before - can be promising in the future with MD. We present a list of challenges and opportunities that can inspire next steps in system design making the case for DSM-DB.
