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Related papers: Using RDMA for Lock Management

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Memory resources in data centers generally suffer from low utilization and lack of dynamics. Memory disaggregation solves these problems by decoupling CPU and memory, which currently includes approaches based on RDMA or interconnection…

Hardware Architecture · Computer Science 2023-02-23 Chenjiu Wang , Ke He , Ruiqi Fan , Xiaonan Wang , Yang Kong , Wei Wang , Qinfen Hao

Memory disaggregation architecture physically separates CPU and memory into independent components, which are connected via high-speed RDMA networks, greatly improving resource utilization of databases. However, such an architecture poses…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-21 Qing Wang , Youyou Lu , Jiwu Shu

Dynamic memory management requires special attention in programming. It should be fast and secure at the same time. This paper proposes a new randomized dynamic memory management algorithm designed to meet these requirements. Randomization…

Data Structures and Algorithms · Computer Science 2021-08-25 Irina Aleksandrovna Astrakhantseva , Roman Gennadevich Astrakhantsev , Arseny Viktorovich Mitin

Nowadays, avoiding system calls during cluster communication (e.g., in Data Centers and High Performance Computing) in modern high-speed interconnection networks has become a necessity, due to the high overhead of multiple data copies…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-27 Antonis Psistakis

As an enhanced version of massive machine-type communication in 5G, massive communication has emerged as one of the six usage scenarios anticipated for 6G, owing to its potential in industrial internet-of-things and smart metering. Driven…

Information Theory · Computer Science 2025-04-17 Yutao Chen , Wei Chen

We present "Reciprocating Locks", a novel mutual exclusion locking algorithm, targeting cache-coherent shared memory (CC), that enjoys a number of desirable properties. The doorway arrival phase and the release operation both run in…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-14 Dave Dice , Alex Kogan

Deep learning emerges as an important new resource-intensive workload and has been successfully applied in computer vision, speech, natural language processing, and so on. Distributed deep learning is becoming a necessity to cope with…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-23 Jilong Xue , Youshan Miao , Cheng Chen , Ming Wu , Lintao Zhang , Lidong Zhou

In the literature, asymptotic studies of multi-hop wireless network capacity often consider only centralized and deterministic TDMA (time-division multi-access) coordination schemes. There have been fewer studies of the asymptotic capacity…

Networking and Internet Architecture · Computer Science 2017-09-25 Chi-Kin Chau , Minghua Chen , Soung Chang Liew

Due to amount of data involved in emerging deep learning and big data applications, operations related to data movement have quickly become the bottleneck. Data-centric computing (DCC), as enabled by processing-in-memory (PIM) and…

Hardware Architecture · Computer Science 2020-09-22 Kamil Khan , Sudeep Pasricha , Ryan Gary Kim

Electronic control systems used for quantum computing have become increasingly complex as multiple qubit technologies employ larger numbers of qubits with higher fidelity targets. Whereas the control systems for different technologies share…

Rate-Splitting Multiple Access (RSMA) for multi-user downlink operates by splitting the message for each user equipment (UE) into a private message and a set of common messages, which are simultaneously transmitted by means of superposition…

Signal Processing · Electrical Eng. & Systems 2022-03-09 Daesung Yu , Seok-Hwan Park , Osvaldo Simeone , Shlomo Shamai

Rate Splitting Multiple Access (RSMA) has recently emerged as a promising technique to enhance the transmission rate for multiple access networks. Unlike conventional multiple access schemes, RSMA requires splitting and transmitting…

Information Theory · Computer Science 2022-04-01 Nguyen Quang Hieu , Dinh Thai Hoang , Dusit Niyato , Diep N. Nguyen , Dong In Kim , Abbas Jamalipour

Popular deep learning frameworks require users to fine-tune their memory usage so that the training data of a deep neural network (DNN) fits within the GPU physical memory. Prior work tries to address this restriction by virtualizing the…

Machine Learning · Computer Science 2017-05-05 Minsoo Rhu , Mike O'Connor , Niladrish Chatterjee , Jeff Pool , Stephen W. Keckler

The conventional approach of moving data to the CPU for computation has become a significant performance bottleneck for emerging scale-out data-intensive applications due to their limited data reuse. At the same time, the advancement in 3D…

Loop scheduling techniques aim to achieve load-balanced executions of scientific applications. Dynamic loop self-scheduling (DLS) libraries for distributed-memory systems are typically MPI-based and employ a centralized chunk calculation…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-19 Ahmed Eleliemy , Florina M. Ciorba

The thesis is dedicated to studying methods to improve the efficiency of random access schemes and to facilitate their deployment in machine-type communications (MTC). First, a joint user activity identification and channel estimation…

Information Theory · Computer Science 2019-06-11 Zhuo Sun

Multi-socket multi-core servers are used for solving some of the important problems in computing. Remote DRAM accesses can impact performance of certain applications running on such servers. This paper presents a new near linear operating…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-07 Suryanarayana Murthy Durbhakula

Load management is being recognized as an important option for active user participation in the energy market. Traditional load management methods usually require a centralized powerful control center and a two-way communication network…

Signal Processing · Electrical Eng. & Systems 2018-05-09 Wei Zhang , Yinliang Xu , Sisi Li , MengChu Zhou , Wenxin Liu , Ying Xu

At DBKDA 2019, we demonstrated that StrongDBMS with simple but rigorous optimistic algorithms, provides better performance in situations of high concurrency than major commercial database management systems (DBMS). The demonstration was…

Databases · Computer Science 2021-10-08 Malcolm Crowe , Fritz Laux

Memory-management support for lock-free data structures is well known to be a tough problem. Recent work has successfully reduced the overhead of such schemes. However, applying memory-management support to a data structure remains complex…

Programming Languages · Computer Science 2018-08-21 Nachshon Cohen