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Asynchronous Many-task (AMT) runtime systems have gained increasing acceptance in the HPC community due to the performance improvements offered by fine-grained tasking runtime systems. At the same time, C++ standardization efforts are…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-09 Tianyi Zhang , Shahrzad Shirzad , Patrick Diehl , R. Tohid , Weile Wei , Hartmut Kaiser

We evaluate and compare four contemporary and emerging runtimes for high-performance computing(HPC) applications: Cilk, Charm++, ParalleX and AM++. We compare along three bases: programming model, execution model and the implementation on…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-02 Abhishek Kulkarni , Andrew Lumsdaine

To achieve scalability with today's heterogeneous HPC resources, we need a dramatic shift in our thinking; MPI+X is not enough. Asynchronous Many Task (AMT) runtime systems break down the global barriers imposed by the Bulk Synchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-09 Thomas Heller , Patrick Diehl , Zachary Byerly , John Biddiscombe , Hartmut Kaiser

OpenMP has been the de facto standard for single node parallelism for more than a decade. Recently, asynchronous many-task runtime (AMT) systems have increased in popularity as a new programming paradigm for high performance computing…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-20 Tianyi Zhang , Shahrzad Shirzad , Bibek Wagle , Adrian S. Lemoine , Patrick Diehl , Hartmut Kaiser

Asynchronous Many-Task (AMT) runtimes offer a productive alternative to the Message Passing Interface (MPI). However, the diverse AMT landscape makes fair comparisons challenging. Task Bench, proposed by Slaughter et al., addresses this…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-16 Torben R. Lahnor , Mia Reitz , Jonas Posner , Patrick Diehl

Despite the various research initiatives and proposed programming models, efficient solutions for parallel programming in HPC clusters still rely on a complex combination of different programming models (e.g., OpenMP and MPI), languages…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-08-16 Hervé Yviquel , Marcio Pereira , Emílio Francesquini , Guilherme Valarini , Gustavo Leite , Pedro Rosso , Rodrigo Ceccato , Carla Cusihualpa , Vitoria Dias , Sandro Rigo , Alan Souza , Guido Araujo

The ongoing convergence of HPC and cloud computing presents a fundamental challenge: HPC applications, designed for static and homogeneous supercomputers, are ill-suited for the dynamic, heterogeneous, and volatile nature of the cloud.…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-17 Aditya Bhosale , Advait Tahilyani , Laxmikant Kale , Sara Kokkila-Schumacher

On modern supercomputers, asynchronous many task systems are emerging to address the new architecture of computational nodes. Through this shift of increasing cores per node, a new programming model with the focus on handle the fine-grain…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-02 Patrick Diehl , Prashant K. Jha , Hartmut Kaiser , Robert Lipton , Martin Levesque

Asynchronous Many-Task (AMT) systems offer a potential solution for efficiently programming complicated scientific applications on extreme-scale heterogeneous architectures. However, they exhibit different communication needs from…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-18 Jiakun Yan , Hartmut Kaiser , Marc Snir

The HPC community shows a keen interest in creating diversity in the CPU ecosystem. The advent of Arm-based processors provides an alternative to the existing HPC ecosystem, which is primarily dominated by x86 processors. In this paper, we…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-26 Nikunj Gupta , Rohit Ashiwal , Bine Brank , Sateesh K. Peddoju , Dirk Pleiter

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

Parallel algorithms relying on synchronous parallelization libraries often experience adverse performance due to global synchronization barriers. Asynchronous many-task runtimes offer task futurization capabilities that minimize or remove…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-05 Alexander Strack , Christopher Taylor , Patrick Diehl , Dirk Pflüger

Developing parallel algorithms efficiently requires careful management of concurrency across diverse hardware architectures. C++ executors provide a standardized interface that simplifies the development process, allowing developers to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-22 Karame Mohammadiporshokooh , Steven R. Brandt , Hartmut Kaiser

Due to increasing core counts in modern processors, several task-based runtimes emerged, including the C++ Standard Library for Concurrency and Parallelism (HPX). Although the asynchronous many-task runtime HPX allows implicit communication…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-08 Alexander Strack , Dirk Pflüger

The increasing complexity of HPC architectures and the growing adoption of irregular scientific algorithms demand efficient support for asynchronous, multithreaded communication. This need is especially pronounced with Asynchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-27 Jiakun Yan , Marc Snir , Yanfei Guo

Asymmetric multicore processors (AMPs) couple high-performance big cores and low-power small cores with the same instruction-set architecture but different features, such as clock frequency or microarchitecture. Previous work has shown that…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-13 Juan Carlos Saez , Fernando Castro , Manuel Prieto-Matias

Fast multipole methods (FMM) on distributed mem- ory have traditionally used a bulk-synchronous model of com- municating the local essential tree (LET) and overlapping it with computation of the local data. This could be perceived as an…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-05-30 Mustafa AbdulJabbar , Rio Yokota , David Keyes

Large Language Models (LLM) show strong abilities in code generation, but their skill in creating efficient parallel programs is less studied. This paper explores how LLMs generate task-based parallel code from three kinds of input prompts:…

Programming Languages · Computer Science 2026-02-27 Linus Bantel , Moritz Strack , Alexander Strack , Dirk Pflüger

OpenMP is the de-facto standard for shared memory systems in High-Performance Computing (HPC). It includes a task-based model that offers a high-level of abstraction to effectively exploit highly dynamic structured and unstructured…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-12 Chenle Yu , Sara Royuela , Eduardo Quiñones

The current trend of multicore architectures on shared memory systems underscores the need of parallelism. While there are some programming model to express parallelism, thread programming model has become a standard to support these system…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-12-13 D. T. Hasta , A. B. Mutiara
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