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Relevant bibliographies by topics / Remote Direct Memory Access (RDMA)

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Journal articles

Academic literature on the topic 'Remote Direct Memory Access (RDMA)'

Author: Grafiati

Published: 10 December 2022

Last updated: 27 January 2024

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Journal articles on the topic "Remote Direct Memory Access (RDMA)"

1

Chen, Wei, Songping Yu, and Zhiying Wang. "Fast In-Memory Key–Value Cache System with RDMA." Journal of Circuits, Systems and Computers 28, no. 05 (2019): 1950074. http://dx.doi.org/10.1142/s0218126619500749.

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The quick advances of Cloud and the advent of Fog computing impose more and more critical demand for computing and data transfer of low latency onto the underlying distributed computing infrastructure. Remote direct memory access (RDMA) technology has been widely applied for its low latency of remote data access. However, RDMA gives rise to a host of challenges in accelerating in-memory key–value stores, such as direct remote memory writes, making the remote system more vulnerable. This study presents an in-memory key–value system based on RDMA, named Craftscached, which enables: (1) buffering

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2

Ziegler, Tobias, Viktor Leis, and Carsten Binnig. "RDMA Communciation Patterns." Datenbank-Spektrum 20, no. 3 (2020): 199–210. http://dx.doi.org/10.1007/s13222-020-00355-7.

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Abstract Remote Direct Memory Access (RDMA) is a networking protocol that provides high bandwidth and low latency accesses to a remote node’s main memory. Although there has been much work around RDMA, such as building libraries on top of RDMA or even applications leveraging RDMA, it remains a hard problem to identify the most suitable RDMA primitives and their combination for a given problem. While there have been some initial studies included in papers that aim to investigate selected performance characteristics of particular design choices, there has not been a systematic study to evaluate

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3

Ziegler, Tobias, Jacob Nelson-Slivon, Viktor Leis, and Carsten Binnig. "Design Guidelines for Correct, Efficient, and Scalable Synchronization using One-Sided RDMA." Proceedings of the ACM on Management of Data 1, no. 2 (2023): 1–26. http://dx.doi.org/10.1145/3589276.

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Remote data structures built with one-sided Remote Direct Memory Access (RDMA) are at the heart of many disaggregated database management systems today. Concurrent access to these data structures by thousands of remote workers necessitates a highly efficient synchronization scheme. Remarkably, our investigation reveals that existing synchronization schemes display substantial variations in performance and scalability. Even worse, some schemes do not correctly synchronize, resulting in rare and hard-to-detect data corruption. Motivated by these observations, we conduct the first comprehensive a

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4

Gerstenberger, Robert, Maciej Besta, and Torsten Hoefler. "Enabling Highly-Scalable Remote Memory Access Programming with MPI-3 One Sided." Scientific Programming 22, no. 2 (2014): 75–91. http://dx.doi.org/10.1155/2014/571902.

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Modern interconnects offer remote direct memory access (RDMA) features. Yet, most applications rely on explicit message passing for communications albeit their unwanted overheads. The MPI-3.0 standard defines a programming interface for exploiting RDMA networks directly, however, it's scalability and practicability has to be demonstrated in practice. In this work, we develop scalable bufferless protocols that implement the MPI-3.0 specification. Our protocols support scaling to millions of cores with negligible memory consumption while providing highest performance and minimal overheads. To ar

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5

Zhu, Bohong, Youmin Chen, Qing Wang, Youyou Lu, and Jiwu Shu. "Octopus + : An RDMA-Enabled Distributed Persistent Memory File System." ACM Transactions on Storage 17, no. 3 (2021): 1–25. http://dx.doi.org/10.1145/3448418.

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Non-volatile memory and remote direct memory access (RDMA) provide extremely high performance in storage and network hardware. However, existing distributed file systems strictly isolate file system and network layers, and the heavy layered software designs leave high-speed hardware under-exploited. In this article, we propose an RDMA-enabled distributed persistent memory file system, Octopus + , to redesign file system internal mechanisms by closely coupling non-volatile memory and RDMA features. For data operations, Octopus + directly accesses a shared persistent memory pool to reduce memory

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6

Koo, Bonmoo, Jaesang Hwang, Jonghyeok Park, and Wook-Hee Kim. "Converting Concurrent Range Index Structure to Range Index Structure for Disaggregated Memory." Applied Sciences 13, no. 20 (2023): 11130. http://dx.doi.org/10.3390/app132011130.

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In this work, we propose the Spread approach, which tailors a concurrent range index structure to a range index structure for disaggregated memory connected via RDMA (Remote Direct Memory Access). The Spread approach leverages the concept of tolerating transient inconsistencies in a concurrent range index structure to reduce the amount of expensive RDMA operations. Based on the Spread approach, we converted Blink-tree, a concurrent range index structure, to a range index structure for disaggregated memory called RF-tree. In our experimental study, RF-tree shows comparable performance to Sherma

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7

Hemmatpour, Masoud, Bartolomeo Montrucchio, and Maurizio Rebaudengo. "Communicating Efficiently on Cluster-Based Remote Direct Memory Access (RDMA) over InfiniBand Protocol." Applied Sciences 8, no. 11 (2018): 2034. http://dx.doi.org/10.3390/app8112034.

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Distributed systems are commonly built under the assumption that the network is the primary bottleneck, however this assumption no longer holds by emerging high-performance RDMA enabled protocols in datacenters. Designing distributed applications over such protocols requires a fundamental rethinking in communication components in comparison with traditional protocols (i.e., TCP/IP). In this paper, communication paradigms in existing systems and new possible paradigms have been investigated. Advantages and drawbacks of each paradigm have been comprehensively analyzed and experimentally evaluate

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8

Wang, Zhonghua, Yixing Guo, Kai Lu, et al. "Rcmp: Reconstructing RDMA-Based Memory Disaggregation via CXL." ACM Transactions on Architecture and Code Optimization 21, no. 1 (2024): 1–26. http://dx.doi.org/10.1145/3634916.

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Memory disaggregation is a promising architecture for modern datacenters that separates compute and memory resources into independent pools connected by ultra-fast networks, which can improve memory utilization, reduce cost, and enable elastic scaling of compute and memory resources. However, existing memory disaggregation solutions based on remote direct memory access (RDMA) suffer from high latency and additional overheads including page faults and code refactoring. Emerging cache-coherent interconnects such as CXL offer opportunities to reconstruct high-performance memory disaggregation. Ho

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9

Chen, Hongzhi, Changji Li, Chenguang Zheng, et al. "G-tran." Proceedings of the VLDB Endowment 15, no. 11 (2022): 2545–58. http://dx.doi.org/10.14778/3551793.3551813.

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Graph transaction processing poses unique challenges such as random data access due to the irregularity of graph structures, low throughput and high abort rate due to the relatively large read/write sets in graph transactions. To address these challenges, we present G-Tran, a remote direct memory access (RDMA)-enabled distributed in-memory graph database with serializable and snapshot isolation support. First, we propose a graph-native data store to achieve good data locality and fast data access for transactional updates and queries. Second, G-Tran adopts a fully decentralized architecture th

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10

Wei, Xingda, Rong Chen, Haibo Chen, and Binyu Zang. "XStore : Fast RDMA-Based Ordered Key-Value Store Using Remote Learned Cache." ACM Transactions on Storage 17, no. 3 (2021): 1–32. http://dx.doi.org/10.1145/3468520.

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RDMA ( Remote Direct Memory Access ) has gained considerable interests in network-attached in-memory key-value stores. However, traversing the remote tree-based index in ordered key-value stores with RDMA becomes a critical obstacle, causing an order-of-magnitude slowdown and limited scalability due to multiple round trips. Using index cache with conventional wisdom—caching partial data and traversing them locally—usually leads to limited effect because of unavoidable capacity misses, massive random accesses, and costly cache invalidations. We argue that the machine learning (ML) model is a pe

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