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Emerging non-volatile memory (NVM) technologies promise memory speed byte-addressable persistent storage with a load/store interface. However, programming applications to directly manipulate NVM data is complex and error-prone. Applications…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-01 Pradeep Fernando , Irina Calciu , Jayneel Gandhi , Aasheesh Kolli , Ada Gavrilovska

Data privacy and silos are nontrivial and greatly challenging in many real-world applications. Federated learning is a decentralized approach to training models across multiple local clients without the exchange of raw data from client…

Machine Learning · Computer Science 2024-03-01 Xin Yang , Hao Yu , Xin Gao , Hao Wang , Junbo Zhang , Tianrui Li

Non-volatile memory is expected to co-exist or replace DRAM in upcoming architectures. Durable concurrent data structures for non-volatile memories are essential building blocks for constructing adequate software for use with these…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-10 Yoav Zuriel , Michal Friedman , Gali Sheffi , Nachshon Cohen , Erez Petrank

This paper considers the modeling and the analysis of the performance of lock-free concurrent data structures. Lock-free designs employ an optimistic conflict control mechanism, allowing several processes to access the shared data object at…

Data Structures and Algorithms · Computer Science 2015-08-17 Aras Atalar , Paul Renaud-Goud , Philippas Tsigas

When compared to blocking concurrency, non-blocking concurrency can provide higher performance in parallel shared-memory contexts, especially in high contention scenarios. This paper proposes FLeeC, an application-level cache system based…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-17 André J. Costa , Nuno M. Preguiça , João M. Lourenço

Federated Continual Learning (FCL) has emerged as a promising paradigm that combines Federated Learning (FL) and Continual Learning (CL). To achieve good model accuracy, FCL needs to tackle catastrophic forgetting due to concept drift over…

Machine Learning · Computer Science 2023-11-14 Xiaopeng Jiang , Cristian Borcea

Federated continual learning (FCL) allows distributed autonomous fleets to adapt collaboratively to evolving terrain types across extended mission lifecycles. However, current approaches face several key challenges: 1) they use uniform…

Machine Learning · Computer Science 2026-04-23 Beining Wu , Jun Huang

Parallel batched data structures are designed to process synchronized batches of operations in a parallel computing model. In this paper, we propose parallel combining, a technique that implements a concurrent data structure from a parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-14 Vitaly Aksenov , Petr Kuznetsov , Anatoly Shalyto

DIMM-compatible persistent memory unites memory and storage. Prior works utilize persistent memory either by combining the filesystem with direct access on memory mapped files or by managing it as a collection of objects while abolishing…

Operating Systems · Computer Science 2022-04-08 Derrick Greenspan , Naveed Ul Mustafa , Zoran Kolega , Mark Heinrich , Yan Solihin

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

The disaggregated memory (DM) architecture offers high resource elasticity at the cost of data access performance. While caching frequently accessed data in compute nodes (CNs) reduces access overhead, it requires costly centralized…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-26 Hanze Zhang , Kaiming Wang , Rong Chen , Xingda Wei , Haibo Chen

In collaborative filtering (CF), interaction function (IFC) plays the important role of capturing interactions among items and users. The most popular IFC is the inner product, which has been successfully used in low-rank matrix…

Machine Learning · Computer Science 2020-04-07 Quanming Yao , Xiangning Chen , James Kwok , Yong Li , Cho-Jui Hsieh

The queue is conceptually one of the simplest data structures-a basic FIFO container. However, ensuring correctness in the presence of concurrency makes existing lock-free implementations significantly more complex than their original form.…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-13 Yusuf Motiwala

Fault tolerance is one of the major design goals for HPC. The emergence of non-volatile memories (NVM) provides a solution to build fault tolerant HPC. Data in NVM-based main memory are not lost when the system crashes because of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-17 Shuo Yang , Kai Wu , Yifan Qiao , Dong Li , Jidong Zhai

We study abstraction for crash-resilient concurrent objects using non-volatile memory (NVM). We develop a library correctness criterion that is sound for ensuring contextual refinement in this setting, thus allowing clients to reason about…

Programming Languages · Computer Science 2022-01-31 Artem Khyzha , Ori Lahav

Although a wide variety of handcrafted concurrent data structures have been proposed, there is considerable interest in universal approaches (henceforth called Universal Constructions or UCs) for building concurrent data structures. These…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-05 Ilya Kokorin , Alexander Fedorov , Trevor Brown , Vitaly Aksenov

Eventually linearizable objects are novel shared memory programming constructs introduced as an analogy to eventual consistency in message-passing systems. However, their behaviors in shared memory systems are so mysterious that very little…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-29 Tong Che

Work-stealing is a widely used technique for balancing irregular parallel workloads, and most modern runtime systems adopt lock-free work-stealing deques to reduce contention and improve scalability. However, existing algorithms are…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-09 Raja Sai Nandhan Yadav Kataru , Danial Davarnia , Ali Jannesari

Federated clustering (FC) is an extension of centralized clustering in federated settings. The key here is how to construct a global similarity measure without sharing private data, since the local similarity may be insufficient to group…

Machine Learning · Computer Science 2023-10-24 Jie Yan , Jing Liu , Ji Qi , Zhong-Yuan Zhang

We present a federated, asynchronous, memory-limited algorithm for online task scheduling across large-scale networks of hundreds of workers. This is achieved through recent advancements in federated edge computing that unlocks the ability…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-29 Andreas Grammenos , Evangelia Kalyvianaki , Peter Pietzuch