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Related papers: Modular Fault-Tolerant DBMS

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Remote Memory Access (RMA) is an emerging mechanism for programming high-performance computers and datacenters. However, little work exists on resilience schemes for RMA-based applications and systems. In this paper we analyze fault…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-20 Maciej Besta , Torsten Hoefler

In-memory columnar databases have become mainstream over the last decade and have vastly improved the fast processing of large volumes of data through multi-core parallelism and in-memory compression thereby eliminating the usual…

Databases · Computer Science 2016-09-27 Jayanth Jayanth

Databases, collections of related data, are as old as the written word. A database can be anything from a homemaker's metal recipe file to a sophisticated data warehouse. Yet today, when we think of a database we invariably think of…

Databases · Computer Science 2007-05-23 Nancy Hartline Bercich

Machine learning (ML) techniques for optimizing data management problems have been extensively studied and widely deployed in recent five years. However traditional ML methods have limitations on generalizability (adapting to different…

Databases · Computer Science 2024-02-06 Xuanhe Zhou , Xinyang Zhao , Guoliang Li

In modern computing, RDBMS are great to store different types of data. To a developer, one of the major objectives is to provide a very low cost and easy to use solution to an existing problem. While commercial databases are more easy to…

Databases · Computer Science 2015-03-19 Kisor Ray , Sourav Bag , Saumen Sarkar

Fine-tuning large language models (LLMs) with limited data poses a practical challenge in low-resource languages, specialized domains, and constrained deployment settings. While pre-trained LLMs provide strong foundations, effective…

Computation and Language · Computer Science 2025-10-29 Marton Szep , Daniel Rueckert , Rüdiger von Eisenhart-Rothe , Florian Hinterwimmer

Large Language Models (LLMs) have become a mainstay for many everyday applications. However, as data evolve their knowledge quickly becomes outdated. Continual learning aims to update LLMs with new information without erasing previously…

Machine Learning · Computer Science 2026-01-05 Thomas Katraouras , Dimitrios Rafailidis

In large distributed systems, failures are a daily event occurring frequently, especially with growing numbers of computation tasks and locations on which they are deployed. The advantage of representing an application with a workflow is…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-09 Alberto Mulone , Doriana Medić , Marco Aldinucci

Byzantine Fault Tolerance (BFT) is one of the most challenging problems in Distributed Machine Learning (DML), defined as the resilience of a fault-tolerant system in the presence of malicious components. Byzantine failures are still…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-06 Djamila Bouhata , Hamouma Moumen , Jocelyn Ahmed Mazari , Ahcène Bounceur

The metadata service (MDS) sits on the critical path for distributed file system (DFS) operations, and therefore it is key to the overall performance of a large-scale DFS. Common "serverful" MDS architectures, such as a single server or…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-22 Benjamin Carver , Runzhou Han , Jingyaun Zhang , Mai Zheng , Yue Cheng

In this paper, we argue that current work has failed to provide a comprehensive and maintainable in-memory representation for persistent memory. PM data should be easily mappable into a process address space, shareable across processes,…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-10-04 Suyash Mahar , Mingyao Shen , TJ Smith , Joseph Izraelevitz , Steven Swanson

Data management applications store their data using structured files in which data are usually sorted to serve indexing and queries. However, in-place insertions and removals of data are not naturally supported in a file's address space. To…

Operating Systems · Computer Science 2021-08-06 Chen Chen , Wenshao Zhong , Xingbo Wu

Multi-robot systems enhance efficiency and productivity across various applications, from manufacturing to surveillance. While single-robot motion planning has improved by using databases of prior solutions, extending this approach to…

Robotics · Computer Science 2024-11-14 Irving Solis , James Motes , Mike Qin , Marco Morales , Nancy M. Amato

Byte-addressable persistent memories (PM) has finally made their way into production. An important and pressing problem that follows is how to deploy them in existing datacenters. One viable approach is to attach PM as self-contained…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-08 Shin-Yeh Tsai , Yiying Zhang

High capacity and scalable memory systems play a vital role in enabling our desktops, smartphones, and pervasive technologies like Internet of Things (IoT). Unfortunately, memory systems are becoming increasingly prone to faults. This is…

Hardware Architecture · Computer Science 2019-09-04 Prashant J. Nair

Efficiency has been a pivotal aspect of the software industry since its inception, as a system that serves the end-user fast, and the service provider cost-efficiently benefits all parties. A database management system (DBMS) is an integral…

Performance · Computer Science 2023-11-28 Toni Taipalus

Miniaturized satellites are currently not considered suitable for critical, high-priority, and complex multi-phased missions, due to their low reliability. As hardware-side fault tolerance (FT) solutions designed for larger spacecraft can…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-26 Christian M. Fuchs , Nadia M. Murillo , Aske Plaat , Erik van der Kouwe , Todor Stefanov

With the increasing complexity of computing systems, complete hardware reliability can no longer be guaranteed. We need, however, to ensure overall system reliability. One of the most important features of artificial neural networks is…

Neural and Evolutionary Computing · Computer Science 2015-10-07 Anton Kulakov , Mark Zwolinski , Jeff Reeve

Persistent memory (PMEM) devices present an opportunity to retain the flexibility of main memory data structures and algorithms, but augment them with reliability and persistence. The challenge in doing this is to combine replication (for…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-17 Pradeep Fernando , Daniel Zahka , Ada Gavrilovska , Amitabha Roy , Subramanya R. Dulloor

Most distributed storage systems provide limited abilities for querying data by attributes other than their primary keys. Supporting efficient search on secondary attributes is challenging as applications pose varying requirements to query…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-03-13 Dimitrios Vasilas , Marc Shapiro , Bradley King
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