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Maximizing parallelism level in applications can be achieved by minimizing overheads due to load imbalances and waiting time due to memory latencies. Compiler optimization is one of the most effective solutions to tackle this problem. The…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-29 Zahra Khatami , Hartmut Kaiser , J. Ramanujam

The performance of many parallel applications depends on loop-level parallelism. However, manually parallelizing all loops may result in degrading parallel performance, as some of them cannot scale desirably to a large number of threads. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-07 Zahra Khatami , Lukas Troska , Hartmut Kaiser , J. Ramanujam , Adrian Serio

Exascale systems, expected to emerge by the end of the next decade, will require the exploitation of billion-way parallelism at multiple hierarchical levels in order to achieve the desired sustained performance. The task of assessing future…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-09-27 Matthew Anderson , Maciej Brodowicz , Hartmut Kaiser , Thomas Sterling

Experience shows that on today's high performance systems the utilization of different acceleration cards in conjunction with a high utilization of all other parts of the system is difficult. Future architectures, like exascale clusters,…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-07 Patrick Diehl , Madhavan Seshadri , Thomas Heller , Hartmut Kaiser

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

On the way to Exascale, programmers face the increasing challenge of having to support multiple hardware architectures from the same code base. At the same time, portability of code and performance are increasingly difficult to achieve as…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-14 Thomas Heller , Hartmut Kaiser , Patrick Diehl , Dietmar Fey , Marc Alexander Schweitzer

Traditional heterogeneous parallel algorithms, designed for heterogeneous clusters of workstations, are based on the assumption that the absolute speed of the processors does not depend on the size of the computational task. This assumption…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-09-15 Alexey Lastovetsky , Ravi Reddy , Vladimir Rychkov , David Clarke

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

In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-12 Jose Nunez-Yanez , Mohammad Hosseinabady , Moslem Amiri , Andrés Rodríguez , Rafael Asenjo , Angeles Navarro , Rubén Gran-Tejero , Darío Suárez-Gracia

A heterogeneous architecture composed by a host and an accelerator must frequently deal with situations where several independent tasks are available to be offloaded onto the accelerator. These tasks can be generated by concurrent…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-03 A. J. Lázaro-Muñoz , J. M. González-Linares , J. Gómez-Luna , N. Guil

Modern HPC systems are increasingly relying on greater core counts and wider vector registers. Thus, applications need to be adapted to fully utilize these hardware capabilities. One class of applications that can benefit from this increase…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-16 James Vance , Zhen-Hao Xu , Nikita Tretyakov , Torsten Stuehn , Markus Rampp , Sebastian Eibl , Christoph Junghans , André Brinkmann

This paper investigates co-scheduling algorithms for processing a set of parallel applications. Instead of executing each application one by one, using a maximum degree of parallelism for each of them, we aim at scheduling several…

Data Structures and Algorithms · Computer Science 2013-05-01 Guillaume Aupy , Manu Shantharam , Anne Benoit , Yves Robert , Padma Raghavan

The introduction of Intel(R) Xeon Phi(TM) coprocessors opened up new possibilities in development of highly parallel applications. The familiarity and flexibility of the architecture together with compiler support integrated into the Intel…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-11-26 Jiri Dokulil , Enes Bajrovic , Siegfried Benkner , Sabri Pllana , Martin Sandrieser , Beverly Bachmayer

Parallelization is needed everywhere, from laptops and mobile phones to supercomputers. Among parallel programming models, task-based programming has demonstrated a powerful potential and is widely used in high-performance scientific…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-18 Paul Cardosi , Bérenger Bramas

Many important computational problems require utilization of high performance computing (HPC) systems that consist of multi-level structures combining higher and higher numbers of devices with various characteristics. Utilizing full power…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-21 Paweł Rościszewski

High-performance computing systems are more and more often based on accelerators. Computing applications targeting those systems often follow a host-driven approach in which hosts offload almost all compute-intensive sections of the code…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-15 E. Calore , A. Gabbana , S. F. Schifano , R. Tripiccione

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

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

Heterogeneous multi-core architectures combine a few "host" cores, optimized for single-thread performance, with many small energy-efficient "accelerator" cores for data-parallel processing, on a single chip. Offloading a computation to the…

Hardware Architecture · Computer Science 2025-11-11 Luca Colagrande , Luca Benini

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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