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State-machine replication, a fundamental approach to designing fault-tolerant services, requires commands to be executed in the same order by all replicas. Moreover, command execution must be deterministic: each replica must produce the…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-11-26 Parisa Jalili Marandi , Carlos Eduardo Bezerra , Fernando Pedone

State machine replication is standard approach to fault tolerance. One of the key assumptions of state machine replication is that replicas must execute operations deterministically and thus serially. To benefit from multi-core servers,…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-15 Eduardo Alchieri , Fernando Dotti , Fernando Pedone

Executing smart contracts is a compute and storage-intensive task, which currently dominates modern blockchain's performance. Given that computers are becoming increasingly multicore, concurrency is an attractive approach to improve…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-14 Yaron Hay , Roy Friedman

State-machine replication, a fundamental approach to fault tolerance, requires replicas to execute commands deterministically, which usually results in sequential execution of commands. Sequential execution limits performance and underuses…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-04-29 Parisa Jalili Marandi , Fernando Pedone

Linearizability is a well-known correctness property for concurrent and distributed systems. In the past, it was also used to prove the design and implementation of replicated state-machines correct. State-machine replication (SMR) is a…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-03 Franz J. Hauck , Alexander Heß

Data replication is crucial in modern distributed systems as a means to provide high availability. Many techniques have been proposed to utilize replicas to improve a system's performance, often requiring expensive coordination or…

Databases · Computer Science 2019-03-04 Yi Lu , Xiangyao Yu , Samuel Madden

Parallel processing is a principle which enables simultaneous implementation of anesthesia induction and operating room (OR) turnover with the aim of improving OR utilization. In this article, we study the problem of scheduling surgeries…

Optimization and Control · Mathematics 2022-01-03 Batuhan Celik , Serhat Gul , Melih Celik

In this paper, we present STAR, a new distributed in-memory database with asymmetric replication. By employing a single-node non-partitioned architecture for some replicas and a partitioned architecture for other replicas, STAR is able to…

Databases · Computer Science 2019-07-23 Yi Lu , Xiangyao Yu , Samuel Madden

There is increasing interest in using multicore processors to accelerate stream processing. For example, indexing sliding window content to enhance the performance of streaming queries is greatly improved by utilizing the computational…

Databases · Computer Science 2019-03-04 Amirhesam Shahvarani , Hans-Arno Jacobsen

State-space models (SSMs) have recently attention as an efficient alternative to computationally expensive attention-based models for sequence modeling. They rely on linear recurrences to integrate information over time, enabling fast…

Machine Learning · Computer Science 2026-01-01 Mahdi Karami , Ali Behrouz , Peilin Zhong , Razvan Pascanu , Vahab Mirrokni

There has been significant progress in understanding the parallelism inherent to iterative sequential algorithms: for many classic algorithms, the depth of the dependence structure is now well understood, and scheduling techniques have been…

Data Structures and Algorithms · Computer Science 2018-08-14 Dan Alistarh , Trevor Brown , Justin Kopinsky , Giorgi Nadiradze

As data-intensive applications grow, batch processing in limited-resource environments faces scalability and resource management challenges. Serverless computing offers a flexible alternative, enabling dynamic resource allocation and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-18 Amine Barrak , Emna Ksontini

The main goal of parallel processing is to provide users with performance that is much better than that of single processor systems. The execution of jobs is scheduled, which requires certain resources in order to meet certain criteria.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-07 Yang Cao , Fei Wu , Thomas Robertazzi

We propose Hybrid Transactional Replication (HTR), a novel replication scheme for highly dependable services. It combines two schemes: a transaction is executed either optimistically by only one service replica in the deferred update mode…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-01-26 Tadeusz Kobus , Maciej Kokociński , Paweł T. Wojciechowski

Current main memory database system architectures are still challenged by high contention workloads and this challenge will continue to grow as the number of cores in processors continues to increase. These systems schedule transactions…

Databases · Computer Science 2019-05-30 Yangjun Sheng , Anthony Tomasic , Tieying Zhang , Andrew Pavlo

We consider the problem of multiple sensor scheduling for remote state estimation of multiple process over a shared link. In this problem, a set of sensors monitor mutually independent dynamical systems in parallel but only one sensor can…

Systems and Control · Computer Science 2016-12-30 Duo Han , Junfeng Wu , Yilin Mo , Lihua Xie

Synchronous Mirroring (SM) is a standard approach to building highly-available and fault-tolerant enterprise storage systems. SM ensures strong data consistency by maintaining multiple exact data replicas and synchronously propagating every…

This paper considers the classical state machine replication (SMR) problem in a distributed system model inspired by cross-chain exchanges. We propose a novel SMR protocol adapted for this model. Each state machine transition takes $O(n)$…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-15 Yingjie Xue , Maurice Herlihy

The Map-Reduce computing framework rose to prominence with datasets of such size that dozens of machines on a single cluster were needed for individual jobs. As datasets approach the exabyte scale, a single job may need distributed…

Data Structures and Algorithms · Computer Science 2016-10-31 Riley Murray , Samir Khuller , Megan Chao

The aim of the paper is to introduce general techniques in order to optimize the parallel execution time of sorting on a distributed architectures with processors of various speeds. Such an application requires a partitioning step. For…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-16 Christophe Cérin , Jean-Christophe Dubacq , Jean-Louis Roch , the SafeScale Collaboration
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