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Related papers: Handling Parallelism in a Concurrency Model

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With the advent of multi-core processors and their fast expansion, it is quite clear that {\em parallel computing} is now a genuine requirement in Computer Science and Engineering (and related) curriculum. In addition to the pervasiveness…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-13 Claude Tadonki

Software caches optimize the performance of diverse storage systems, databases and other software systems. Existing works on software caches automatically resort to fully associative cache designs. Our work shows that limited associativity…

Hardware Architecture · Computer Science 2021-09-08 Dolev Adas , Gil Einziger , Roy Friedman

Regions of nested loops are a common feature of High Performance Computing (HPC) codes. In shared memory programming models, such as OpenMP, these structure are the most common source of parallelism. Parallelising these structures requires…

Programming Languages · Computer Science 2012-05-14 Adrian Jackson , Orestis Agathokleous

Concurrency, the art of doing many things at the same time is slowly becoming a science. It is very difficult to master, yet it arises all over modern computing systems, both when the communication medium is shared memory and when it is by…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-12-17 Sergio Rajsbaum , Michel Raynal

We provide a taxonomy of concurrency models for BDI frameworks, elicited by analysing state-of-the-art technologies, and aimed at helping both BDI designers and developers in making informed decisions. Comparison among BDI technologies…

Multiagent Systems · Computer Science 2025-01-30 Martina Baiardi , Samuele Burattini , Giovanni Ciatto , Danilo Pianini , Andrea Omicini , Alessandro Ricci

Concurrent linearizable access to shared objects can be prohibitively expensive in a high contention workload. Many applications apply ad-hoc techniques to eliminate the need of synchronous atomic updates, which may result in…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-11 Deepthi Devaki Akkoorath , José Brandão , Annette Bieniusa , Carlos Baquero

This article presents an automatic approach to quickly derive a good solution for hardware resource partition and task granularity for task-based parallel applications on heterogeneous many-core architectures. Our approach employs a…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-10 Peng Zhang , Jianbin Fang , Canqun Yang , Chun Huang , Tao Tang , Zheng Wang

The mutual-exclusion property of locks stands in the way to scalability of parallel programs on many-core architectures. Locks do not allow progress guarantees, because a task may fail inside a critical section and keep holding a lock that…

Programming Languages · Computer Science 2018-06-20 Johann Blieberger , Bernd Burgstaller

Constraint Handling Rules is an effective concurrent declarative programming language and a versatile computational logic formalism. CHR programs consist of guarded reactive rules that transform multisets of constraints. One of the main…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-09 Thom Fruehwirth

The processor accelerators are effective because they are working not (completely) on principles of stored program computers. They use some kind of parallelism, and it is rather hard to program them effectively: a parallel architecture by…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-26 János Végh

A novel parallel patterns library, Groovy Parallel Patterns, is presented which, from the outset, has been designed to exploit more general process parallelism than the usual data and task parallel architectures. The library executes on a…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-23 Jon Kerridge , Neil Urquhart

Sequential computation is well understood but does not scale well with current technology. Within the next decade, systems will contain large numbers of processors with potentially thousands of processors per chip. Despite this, many…

Hardware Architecture · Computer Science 2015-11-17 James Hanlon

Because most optimisations to achieve higher computational performance eventually are limited, parallelism that scales is required. Parallelised hardware alone is not sufficient, but software that matches the architecture is required to…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-11 Oskar Schirmer

To achieve high performance on modern computers, it is vital to map algorithmic parallelism to that inherent in the hardware. From an application developer's perspective, it is also important that code can be maintained in a portable manner…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-06-20 Alan Gray , Kevin Stratford

Neural algorithmic reasoners are parallel processors. Teaching them sequential algorithms contradicts this nature, rendering a significant share of their computations redundant. Parallel algorithms however may exploit their full…

Machine Learning · Computer Science 2024-01-04 Valerie Engelmayer , Dobrik Georgiev , Petar Veličković

As quantum computers continue to improve and support larger, more complex computations, smart control hardware and compilers are needed to efficiently leverage the capabilities of these systems. This paper introduces a novel approach to…

Quantum Physics · Physics 2025-11-19 Folkert de Ronde , Alexander Knapen , Stephan Wong , Sebastian Feld

We consider the problem of selecting the best variable-value strategy for solving a given problem in constraint programming. We show that the recent Embarrassingly Parallel Search method (EPS) can be used for this purpose. EPS proposes to…

Artificial Intelligence · Computer Science 2016-04-25 Anthony Palmieri , Jean-Charles Régin , Pierre Schaus

Ensuring constraint satisfaction is a key requirement for safety-critical systems, which include most robotic platforms. For example, constraints can be used for modeling joint position/velocity/torque limits and collision avoidance.…

Robotics · Computer Science 2025-09-04 Elias Fontanari , Gianni Lunardi , Matteo Saveriano , Andrea Del Prete

Co-scheduling of jobs in data-centers is a challenging scenario, where jobs can compete for resources yielding to severe slowdowns or failed executions. Efficient job placement on environments where resources are shared requires awareness…

Machine Learning · Computer Science 2020-07-07 David Buchaca Prats , Joan Marcual , Josep Lluís Berral , David Carrera

Parallel programming remains a daunting challenge, from the struggle to express a parallel algorithm without cluttering the underlying synchronous logic, to describing which devices to employ in a calculation, to correctness. Over the…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-10 Patrick Diehl , Steven R. Brandt , Hartmut Kaiser
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