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The aim of parallel computing is to increase an application performance by executing the application on multiple processors. OpenMP is an API that supports multi platform shared memory programming model and shared-memory programs are…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-11-12 Vibha Rajput , Alok Katiyar

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

Accelerated computing is widely used in high-performance computing. Therefore, it is crucial to experiment and discover how to better utilize GPUGPUs latest generations on relevant applications. In this paper, we present results and share…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-13 Baodi Shan , Mauricio Araya-Polo

In this proceedings we discuss the motivation, implementation details, and performance of a new physics code base called Grid. It is intended to be more performant, more general, but similar in spirit to QDP++\cite{QDP}. Our approach is to…

High Energy Physics - Lattice · Physics 2015-12-14 Peter Boyle , Azusa Yamaguchi , Guido Cossu , Antonin Portelli

Parallel computing is a standard approach to achieving high-performance computing (HPC). Three commonly used methods to implement parallel computing include: 1) applying multithreading technology on single-core or multi-core CPUs; 2)…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-18 Xinyao Yi

An existing hybrid MPI-OpenMP scheme is augmented with a CUDA-based fine grain parallelization approach for multidimensional distributed Fourier transforms, in a well-characterized pseudospectral fluid turbulence code. Basics of the hybrid…

Computational Physics · Physics 2018-08-07 Duane Rosenberg , Pablo D. Mininni , Raghu Reddy , Annick Pouquet

Heterogeneous systems are becoming more common on High Performance Computing (HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task to obtain optimal performance on the GPU. Approaches to simplifying this task include…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-01-11 Marek Blazewicz , Steven R. Brandt , Peter Diener , David M. Koppelman , Krzysztof Kurowski , Frank Löffler , Erik Schnetter , Jian Tao

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

We present details of our implementation of the Wuppertal adaptive algebraic multigrid code DD-$\alpha$AMG on SIMD architectures, with particular emphasis on the Intel Xeon Phi processor (KNC) used in QPACE 2. As a smoother, the algorithm…

Computational Physics · Physics 2015-12-15 Simon Heybrock , Matthias Rottmann , Peter Georg , Tilo Wettig

Nowadays, subsequence similarity search is required in a wide range of time series mining applications: climate modeling, financial forecasts, medical research, etc. In most of these applications, the Dynamic TimeWarping (DTW) similarity…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-09 Yana Kraeva , Mikhail Zymbler

In addition to hardware wall-time restrictions commonly seen in high-performance computing systems, it is likely that future systems will also be constrained by energy budgets. In the present work, finite difference algorithms of varying…

Mathematical Software · Computer Science 2017-09-29 Satya P. Jammy , Christian T. Jacobs , David J. Lusher , Neil D. Sandham

Manycore processors feature a high number of general-purpose cores designed to work in a multithreaded fashion. Recent manycore processors are kept coherent using scalable distributed directories. A paramount example is the Intel Mesh…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-11-12 Steve Kommrusch , Marcos Horro , Louis-Noël Pouchet , Gabriel Rodríguez , Juan Touriño

As is intrinsic to the fundamental goal of quantum computing, classical simulation of quantum algorithms is notoriously demanding in resource requirements. Nonetheless, simulation is critical to the success of the field and a requirement…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-01 W. Michael Brown , Anurag Ramesh , Thomas Lubinski , Thien Nguyen , David E. Bernal Neira

While parallelism remains the main source of performance, architectural implementations and programming models change with each new hardware generation, often leading to costly application re-engineering. Most tools for performance…

Programming Languages · Computer Science 2022-07-04 William S. Moses , Ivan R. Ivanov , Jens Domke , Toshio Endo , Johannes Doerfert , Oleksandr Zinenko

Energy consumption is increasingly becoming a limiting factor to the design of faster large-scale parallel systems, and development of energy-efficient and energy-aware applications is today a relevant issue for HPC code-developer…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-06 E. Calore , A. Gabbana , S. F. Schifano , R. Tripiccione

The prospects of quantum computing have driven efforts to realize fully functional quantum processing units (QPUs). Recent success in developing proof-of-principle QPUs has prompted the question of how to integrate these emerging processors…

Emerging Technologies · Computer Science 2015-12-10 Keith A. Britt , Travis S. Humble

Offload of MPI collectives to network devices, e.g., NICs and switches, is being implemented as an effective mechanism to improve application performance by reducing inter- and intra-node communication and bypassing MPI software layers.…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-01 Pouya Haghi , Ryan Marshall , Po Hao Chen , Anthony Skjellum , Martin Herbordt

MPI derived datatypes are an abstraction that simplifies handling of non-contiguous data in MPI applications. These datatypes are recursively constructed at runtime from primitive Named Types defined in the MPI standard. More recently, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-22 Carl Pearson , Kun Wu , I-Hsin Chung , Jinjun Xiong , Wen-Mei Hwu

With at least 50 cores, Intel Xeon Phi is a true many-core architecture. Featuring fairly powerful cores, two cache levels, and very fast interconnections, the Xeon Phi can get a theoretical peak of 1000 GFLOPs and over 240 GB/s. These…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-23 Jianbin Fang , Ana Lucia Varbanescu , Henk Sips , Lilun Zhang , Yonggang Che , Chuanfu Xu

The strategy of using CUDA-compatible GPUs as a parallel computation solution to improve the performance of programs has been more and more widely approved during the last two years since the CUDA platform was released. Its benefit extends…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-01-12 Chang Xu , Steven R. Kirk , Samantha Jenkins