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Related papers: Parallel Work Inflation, Memory Effects, and their…

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Task parallelism is designed to simplify the task of parallel programming. When executing a task parallel program on modern NUMA architectures, it can fail to scale due to the phenomenon called work inflation, where the overall processing…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-08 Justin Deters , Jiaye Wu , Yifan Xu , I-Ting Angelina Lee

Researchers working on the automatic parallelization of programs have long known that too much parallelism can be even worse for performance than too little, because spawning a task to be run on another CPU incurs overheads.…

Programming Languages · Computer Science 2011-09-08 Paul Bone , Zoltan Somogyi , Peter Schachte

Evaluating how well a whole system or set of subsystems performs is one of the primary objectives of performance testing. We can tell via performance assessment if the architecture implementation meets the design objectives. Performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-15 Donald Ene Vincent Ike Anireh

In the recent years it can be observed increasing popularity of parallel processing using multi-core processors, local clusters, GPU and others. Moreover, currently one of the main requirements the IT users is the reduction of maintaining…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-05 Łukasz P. Olech , Jan Kwiatkowski

In competitive parallel computing, the identical copies of a code in a phase of a sequential program are assigned to processor cores and the result of the fastest core is adopted. In the literature, it is reported that a superlinear speedup…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-22 Naoki Yonezawa

After Amdahl's trailblazing work, many other authors proposed analytical speedup models but none have considered the limiting effect of the memory wall. These models exploited aspects such as problem-size variation, memory size,…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-11 Alex F. A. Furtunato , Kyriakos Georgiou , Kerstin Eder , Samuel Xavier-de-Souza

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

Parallel programming models can encourage performance portability by moving the responsibility for work assignment and data distribution from the programmer to a runtime system. However, analyzing the resulting implicit memory allocations,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-14 Fabian Knorr , Philip Salzmann , Peter Thoman , Thomas Fahringer

The unknown parameters of simulation models often need to be calibrated using observed data. When simulation models are expensive, calibration is usually carried out with an emulator. The effectiveness of the calibration process can be…

Computation · Statistics 2024-12-03 Özge Sürer , Stefan M. Wild

In some models of parallel computation, jobs are split into smaller tasks and can be executed completely asynchronously. In other situations the parallel tasks have constraints that require them to synchronize their start and possibly…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-17 Brenton Walker , Markus Fidler

This paper introduces the \emph{serial-parallel decision problem}. Consider an online scheduler that receives a series of tasks, where each task has both a parallel and a serial implementation. The parallel implementation has the advantage…

Data Structures and Algorithms · Computer Science 2024-05-21 William Kuszmaul , Alek Westover

In recent years, various means of efficiently detecting changepoints in the univariate setting have been proposed, with one popular approach involving minimising a penalised cost function using dynamic programming. In some situations, these…

Methodology · Statistics 2018-10-09 S. O. Tickle , I. A. Eckley , P. Fearnhead , K. Haynes

Selecting optimal intervals of checkpointing an application is important for minimizing the run time of the application in the presence of system failures. Most of the existing efforts on checkpointing interval selection were developed for…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-02 K. Raghavendra , Sathish S Vadhiyar

With the spread of multi- and many-core processors more and more typical task is to re-implement some source code written originally for a single processor to run on more than one cores. Since it is a serious investment, it is important to…

Performance · Computer Science 2016-07-25 János Végh , Péter Molnár , József Vásárhelyi

In high performance computing environments, we observe an ongoing increase in the available numbers of cores. This development calls for re-emphasizing performance (scalability) analysis and speedup laws as suggested in the literature…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-16 Guido Schryen

Parallel application I/O performance often does not meet user expectations. Additionally, slight access pattern modifications may lead to significant changes in performance due to complex interactions between hardware and software. These…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-19 Julian M. Kunkel , Eugen Betke , Matt Bryson , Philip Carns , Rosemary Francis , Wolfgang Frings , Roland Laifer , Sandra Mendez

Empirical studies are fundamental in assessing the effectiveness of implementations of branch-and-bound algorithms. The complexity of such implementations makes empirical study difficult for a wide variety of reasons. Various attempts have…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-21 Stephen J. Maher , Ted K. Ralphs , Yuji Shinano

Different from sequential programs, parallel programs possess their own characteristics which are difficult to analyze in the multi-process or multi-thread environment. This paper presents an innovative method to automatically analyze the…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-06-09 Xu Liu , Jianfeng Zhan , Bibo Tu , Ming Zou , Dan Meng

As large language models (LLMs) have shown great success in many tasks, they are used in various applications. While a lot of works have focused on the efficiency of single-LLM application (e.g., offloading, request scheduling, parallelism…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-24 Jingzhi Fang , Yanyan Shen , Yue Wang , Lei Chen

Today, very large amounts of data are produced and stored in all branches of society including science. Mining these data meaningfully has become a considerable challenge and is of the broadest possible interest. The size, both in numbers…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-11 Andreas Vitalis
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