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To efficiently exploit the resources of new many-core architectures, integrating dozens or even hundreds of cores per chip, parallel programming models have evolved to expose massive amounts of parallelism, often in the form of fine-grained…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-05-14 Andi Drebes , Karine Heydemann , Antoniu Pop , Albert Cohen , Nathalie Drach

Existing data race detectors for task-based programs incur significant run time and space overheads. The overheads arise because of frequent lookups in fine-grained tree data structures to check whether two accesses can happen in parallel.…

Programming Languages · Computer Science 2022-04-06 Shivam Kumar , Anupam Agrawal , Swarnendu Biswas

Multicore parallel programming has some very difficult problems such as deadlocks during synchronizations and race conditions brought by concurrency. Added to the difficulty is the lack of a simple, well-accepted computing model for…

Programming Languages · Computer Science 2010-12-09 Yibing Wang

One of the main advantages of Logic Programming (LP) is that it provides an excellent framework for the parallel execution of programs. In this work we investigate novel techniques to efficiently exploit parallelism from real-world…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-07-27 Vítor Santos Costa , Inês Dutra , Ricardo Rocha

In this paper, we address some of the key limitations to realizing a generic heterogeneous parallel programming model for quantum-classical heterogeneous platforms. We discuss our experience in enabling user-level multi-threading in QCOR as…

This paper addresses the monitoring of logic-independent linear-time user-provided properties in multi-threaded component-based systems. We consider intrinsically independent components that can be executed concurrently with a centralized…

Software Engineering · Computer Science 2017-01-24 Hosein Nazarpour , Yliès Falcone , Saddek Bensalem , Marius Bozga

The active-time scheduling problem considers the problem of scheduling preemptible jobs with windows (release times and deadlines) on a parallel machine that can schedule up to $g$ jobs during each timestep. The goal in the active-time…

Data Structures and Algorithms · Computer Science 2022-07-27 Nairen Cao , Jeremy T. Fineman , Shi Li , Julián Mestre , Katina Russell , Seeun William Umboh

We investigate the application of active inference in developing energy-efficient control agents for manufacturing systems. Active inference, rooted in neuroscience, provides a unified probabilistic framework integrating perception,…

Machine Learning · Computer Science 2025-05-28 Yavar Taheri Yeganeh , Mohsen Jafari , Andrea Matta

Real-time systems, particularly those used in domains like automated driving, are increasingly adopting neural networks. From this trend arises the need for high-performance hardware exhibiting predictable timing behavior. While…

Hardware Architecture · Computer Science 2026-02-26 Maximilian Kirschner , Konstantin Dudzik , Ben Krusekamp , Jürgen Becker

Shared memory multiprocessors come back to popularity thanks to rapid spreading of commodity multi-core architectures. As ever, shared memory programs are fairly easy to write and quite hard to optimise; providing multi-core programmers…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-09-10 Marco Aldinucci , Massimo Torquati , Massimiliano Meneghin

This article introduces a highly parallel algorithm for molecular dynamics simulations with short-range forces on single node multi- and many-core systems. The algorithm is designed to achieve high parallel speedups for strongly…

Computational Physics · Physics 2013-11-20 R. Meyer

Verifying multi-threaded programs is becoming more and more important, because of the strong trend to increase the number of processing units per CPU socket. We introduce a new configurable program analysis for verifying multi-threaded…

Logic in Computer Science · Computer Science 2016-12-23 Dirk Beyer , Karlheinz Friedberger

State-of-the-art machine learning frameworks support a wide variety of design features to enable a flexible machine learning programming interface and to ease the programmability burden on machine learning developers. Identifying and using…

Machine Learning · Computer Science 2020-07-01 Yu Emma Wang , Carole-Jean Wu , Xiaodong Wang , Kim Hazelwood , David Brooks

Multicore systems present on-board memory hierarchies and communication networks that influence performance when executing shared memory parallel codes. Characterising this influence is complex, and understanding the effect of particular…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-01 O. G. Lorenzo , M. L. Becoña , T. F. Pena , J. C. Cabaleiro , J. A. Lorenzo , F. F. Rivera

Based on the two observations that diverse applications perform better on different multicore architectures, and that different phases of an application may have vastly different resource requirements, Pal et al. proposed a novel…

Programming Languages · Computer Science 2016-06-21 Sanjiva Prasad

Measurements of absolute runtime are useful as a summary of performance when studying parallel visualization and analysis methods on computational platforms of increasing concurrency and complexity. We can obtain even more insights by…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-07 E. Wes Bethel , David Camp , Talita Perciano , Colleen Heinemann

We propose a memory-model-aware static program analysis method for accurately analyzing the behavior of concurrent software running on processors with weak consistency models such as x86-TSO, SPARC-PSO, and SPARC-RMO. At the center of our…

Programming Languages · Computer Science 2017-09-29 Markus Kusano , Chao Wang

Heterogeneous parallel systems are widely spread nowadays. Despite their availability, their usage and adoption are still limited, and even more rarely they are used to full power. Indeed, compelling new technologies are constantly…

Performance · Computer Science 2015-11-23 Baptiste Delporte , Roberto Rigamonti , Alberto Dassatti

Input-output robustness appears in various different forms in the literature, such as robustness of AI models to adversarial or semantic perturbations and individual fairness of AI models that make decisions about humans. We propose runtime…

Artificial Intelligence · Computer Science 2025-06-03 Ashutosh Gupta , Thomas A. Henzinger , Konstantin Kueffner , Kaushik Mallik , David Pape

A Runtime Verification (RV) framework that supports online, at-speed verification of properties that can change dynamically (during in-field operations) will benefit a large variety of applications. Several state-of-the-art RV frameworks…

Logic in Computer Science · Computer Science 2026-03-23 Chirantan Hebballi , Akash Poptani , Amrutha Benny , Rajshekar Kalayappan , Sandeep Chandran , Ramchandra Phawade