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The performance of anytime algorithms can be improved by simultaneously solving several instances of algorithm-problem pairs. These pairs may include different instances of a problem (such as starting from a different initial state),…

Artificial Intelligence · Computer Science 2011-06-28 L. Finkelstein , S. Markovitch , E. Rivlin

Building concurrent spatial trees is more complicated than binary search trees since a space hierarchy should be preserved during modifications. We present a non-blocking quadtree-quadboost-that supports concurrent insert, remove, move, and…

Data Structures and Algorithms · Computer Science 2016-07-13 Keren Zhou , Guangming Tan , Wei Zhou

We consider a parallel system of $m$ identical machines prone to unpredictable crashes and restarts, trying to cope with the continuous arrival of tasks to be executed. Tasks have different computational requirements (i.e., processing time…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-21 Elli Zavou , Antonio Fernández Anta

The spatial join is a popular operation in spatial database systems and its evaluation is a well-studied problem. As main memories become bigger and faster and commodity hardware supports parallel processing, there is a need to revamp…

Databases · Computer Science 2020-05-25 Dimitrios Tsitsigkos , Panagiotis Bouros , Nikos Mamoulis , Manolis Terrovitis

It is well known that modern functional programming languages are naturally amenable to parallel programming. Achieving efficient parallelism using functional languages, however, remains difficult. Perhaps the most important reason for this…

Programming Languages · Computer Science 2018-02-20 Adrien Guatto , Sam Westrick , Ram Raghunathan , Umut Acar , Matthew Fluet

Research in automatic parallelization of loop-centric programs started with static analysis, then broadened its arsenal to include dynamic inspection-execution and speculative execution, the best results involving hybrid static-dynamic…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-11-30 Riyadh Baghdadi , Albert Cohen , Cedric Bastoul , Louis-Noel Pouchet , Lawrence Rauchwerger

Over the past few years, self-attention is shining in the field of deep learning, especially in the domain of natural language processing(NLP). Its impressive effectiveness, along with ubiquitous implementations, have aroused our interest…

Machine Learning · Computer Science 2020-12-03 Mingfei Yu , Masahiro Fujita

With distributed computing and mobile applications, synchronizing diverging replicas of data structures is a more and more common problem. We use algebraic methods to reason about filesystem operations, and introduce a simplified definition…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-24 Elod Pal Csirmaz

Among the many possible approaches for the parallelization of self-organizing networks, and in particular of growing self-organizing networks, perhaps the most common one is producing an optimized, parallel implementation of the standard…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-31 Giacomo Parigi , Angelo Stramieri , Danilo Pau , Marco Piastra

This note makes an observation that significantly simplifies a number of previous parallel, two-way merge algorithms based on binary search and sequential merge in parallel. First, it is shown that the additional merge step of distinguished…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-07-02 Jesper Larsson Träff

Minimum Spanning Tree (MST) is an important graph algorithm that has wide ranging applications in the areas of computer networks, VLSI routing, wireless communications among others. Today virtually every computer is built out of multi-core…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-15 Suryanarayana Murthy Durbhakula

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

Long context inference scenarios have become increasingly important for large language models, yet they introduce significant computational latency. While prior research has optimized long-sequence inference through operators, model…

Computation and Language · Computer Science 2025-11-10 Wei Shao , Lingchao Zheng , Pengyu Wang , Peizhen Zheng , Jun Li , Yuwei Fan

Current algorithms for large-scale industrial optimization problems typically face a trade-off: they either require exponential time to reach optimal solutions, or employ problem-specific heuristics. To overcome these limitations, we…

Quantum Physics · Physics 2025-10-16 Matteo Vandelli , Francesco Ferrari , Daniele Dragoni

As numerous machine learning and other algorithms increase in complexity and data requirements, distributed computing becomes necessary to satisfy the growing computational and storage demands, because it enables parallel execution of…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-21 Pei Peng , Emina Soljanin , Philip Whiting

In this work, we investigate the potential utility of parallelization for meeting real-time constraints and minimizing energy. We consider malleable Gang scheduling of implicit-deadline sporadic tasks upon multiprocessors. We first show the…

Operating Systems · Computer Science 2013-02-08 Nathan Fisher , Joël Goossens , Pradeep M. Hettiarachchi , Antonio Paolillo

Parametric linear programming is a central operation for polyhedral computations, as well as in certain control applications.Here we propose a task-based scheme for parallelizing it, with quasi-linear speedup over large problems.This type…

Computational Geometry · Computer Science 2020-10-01 Camille Coti , David Monniaux , Hang Yu

The prefix sum operation is a useful primitive with a broad range of applications. For database systems, it is a building block of many important operators including join, sort and filter queries. In this paper, we study different methods…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-25 Wangda Zhang , Yanbin Wang , Kenneth A. Ross

Optimization of searching the best possible action depending on various states like state of environment, system goal etc. has been a major area of study in computer systems. In any search algorithm, searching best possible solution from…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-10 Shubhendra Pal Singhal , M. Sridevi

Inspired by recent successes with parallel optimization techniques for solving Boolean satisfiability, we investigate a set of strategies and heuristics that aim to leverage parallel computing to improve the scalability of neural network…

Logic in Computer Science · Computer Science 2020-08-24 Haoze Wu , Alex Ozdemir , Aleksandar Zeljić , Ahmed Irfan , Kyle Julian , Divya Gopinath , Sadjad Fouladi , Guy Katz , Corina Pasareanu , Clark Barrett