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相关论文: 300x Faster Matlab using MatlabMPI

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The true costs of high performance computing are currently dominated by software. Addressing these costs requires shifting to high productivity languages such as Matlab. MatlabMPI is a Matlab implementation of the Message Passing Interface…

天体物理学 · 物理学 2015-05-26 Jeremy Kepner , Stan Ahalt

MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI currently implements the basic six functions that are the core of the MPI…

天体物理学 · 物理学 2007-05-23 Jeremy Kepner

MATLAB has emerged as one of the languages most commonly used by scientists and engineers for technical computing, with ~1,000,000 users worldwide. The compute intensive nature of technical computing means that many MATLAB users have codes…

天体物理学 · 物理学 2015-05-26 Nadya Bliss , Jeremy Kepner

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…

分布式、并行与集群计算 · 计算机科学 2010-12-13 D. T. Hasta , A. B. Mutiara

The Message-Passing Interface (MPI) and C++ form the backbone of high-performance computing, but MPI only provides C and Fortran bindings. While this offers great language interoperability, high-level programming languages like C++ make…

分布式、并行与集群计算 · 计算机科学 2024-11-13 Tim Niklas Uhl , Matthias Schimek , Lukas Hübner , Demian Hespe , Florian Kurpicz , Christoph Stelz , Peter Sanders

The Message Passing Interface (MPI) is the most commonly used application programming interface for process communication on current large-scale parallel systems. Due to the scale and complexity of modern parallel architectures, it is…

分布式、并行与集群计算 · 计算机科学 2016-09-05 Sascha Hunold , Alexandra Carpen-Amarie , Felix Donatus Lübbe , Jesper Larsson Träff

The Message Passing Interface (MPI) has been extremely successful as a portable way to program high-performance parallel computers. This success has occurred in spite of the view of many that message passing is difficult and that other…

分布式、并行与集群计算 · 计算机科学 2007-05-23 William D. Gropp

The Message Passing Interface (MPI) is widely used in parallel, high-performance programming, yet writing bug-free software that uses MPI remains difficult. We introduce DafnyMPI, a novel, scalable approach to formally verifying MPI…

编程语言 · 计算机科学 2025-12-23 Aleksandr Fedchin , Antero Mejr , Hari Sundar , Jeffrey S. Foster

The Message Passing Interface (MPI) is the prevalent programming model used on today's supercomputers. Therefore, MPI library developers are looking for the best possible performance (shortest run-time) of individual MPI functions across…

分布式、并行与集群计算 · 计算机科学 2016-05-30 Sascha Hunold , Alexandra Carpen-Amarie

Message Passing Interface (MPI) is a foundational programming model for high-performance computing. MPI libraries traditionally employ network interconnects (e.g., Ethernet and InfiniBand) and network protocols (e.g., TCP and RoCE) with…

分布式、并行与集群计算 · 计算机科学 2025-12-16 Xi Wang , Bin Ma , Jongryool Kim , Byungil Koh , Hoshik Kim , Dong Li

Message Passing Interface (MPI) is widely used to implement parallel programs. Although Windowsbased architectures provide the facilities of parallel execution and multi-threading, little attention has been focused on using MPI on these…

分布式、并行与集群计算 · 计算机科学 2011-05-31 Alaa Ismail Elnashar

Matlab is one of the most widely used mathematical computing environments in technical computing. It has an interactive environment which provides high performance computing (HPC) procedures and easy to use. Parallel computing with Matlab…

分布式、并行与集群计算 · 计算机科学 2014-07-28 Zaid Abdi Alkareem Alyasseri

The progression of communication in the Message Passing Interface (MPI) is not well defined, yet it is critical for application performance, particularly in achieving effective computation and communication overlap. The opaque nature of MPI…

分布式、并行与集群计算 · 计算机科学 2024-07-16 Hui Zhou , Robert Latham , Ken Raffenetti , Yanfei Guo , Rajeev Thakur

Comprehending the performance bottlenecks at the core of the intricate hardware-software interactions exhibited by highly parallel programs on HPC clusters is crucial. This paper sheds light on the issue of automatically asynchronous MPI…

分布式、并行与集群计算 · 计算机科学 2023-09-06 Ayesha Afzal , Georg Hager , Stefano Markidis , Gerhard Wellein

This paper explores the integration of MPI-based synchronization techniques into distributed fuzzing frameworks, highlighting possible substantial performance improvements compared to traditional filesystem-based synchronization methods. By…

软件工程 · 计算机科学 2025-12-02 Pierciro Caliandro , Matteo Ciccaglione , Alessandro Pellegrini

Scale-out parallel processing based on MPI is a 25-year-old standard with at least another decade of preceding history of enabling technologies in the High Performance Computing community. Newer frameworks such as MapReduce, Hadoop, and…

分布式、并行与集群计算 · 计算机科学 2017-07-18 Brandon L. Morris , Anthony Skjellum

Python has become a dominant programming language for emerging areas like Machine Learning (ML), Deep Learning (DL), and Data Science (DS). An attractive feature of Python is that it provides easy-to-use programming interface while allowing…

分布式、并行与集群计算 · 计算机科学 2022-08-26 Nawras Alnaasan , Arpan Jain , Aamir Shafi , Hari Subramoni , Dhabaleswar K Panda

As we have entered Exascale computing, the faults in high-performance systems are expected to increase considerably. To compensate for a higher failure rate, the standard checkpoint/restart technique would need to create checkpoints at a…

分布式、并行与集群计算 · 计算机科学 2023-10-26 Sarthak Joshi , Sathish Vadhiyar

The large variety of production implementations of the message passing interface (MPI) each provide unique and varying underlying algorithms. Each emerging supercomputer supports one or a small number of system MPI installations, tuned for…

分布式、并行与集群计算 · 计算机科学 2023-09-15 Amanda Bienz , Derek Schafer , Anthony Skjellum

Finely tuning MPI applications and understanding the influence of keyparameters (number of processes, granularity, collective operationalgorithms, virtual topology, and process placement) is critical toobtain good performance on…

分布式、并行与集群计算 · 计算机科学 2022-01-10 Tom Cornebize , Arnaud Legrand
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