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Parallel computing is very important to accelerate the performance of software systems. Additionally, considering that a recurring challenge is to process high data volumes continuously, stream processing emerged as a paradigm and software…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-14 Adriano Vogel , Sören Henning , Esteban Perez-Wohlfeil , Otmar Ertl , Rick Rabiser

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

Today, many scientific and engineering areas require high performance computing to perform computationally intensive experiments. For example, many advances in transport phenomena, thermodynamics, material properties, computational…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-07-15 K. G. Kapanova , J. M. Sellier

The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark…

Machine Learning · Computer Science 2017-03-03 Randal S. Olson , William La Cava , Patryk Orzechowski , Ryan J. Urbanowicz , Jason H. Moore

High Performance Computing (HPC) aims at providing reasonably fast computing solutions to scientific and real life problems. The advent of multicore architectures is noticeable in the HPC history, because it has brought the underlying…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-07 Claude Tadonki

The prevalence of scientific workflows with high computational demands calls for their execution on various distributed computing platforms, including large-scale leadership-class high-performance computing (HPC) clusters. To handle the…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-10 Tainã Coleman , Henri Casanova , Ketan Maheshwari , Loïc Pottier , Sean R. Wilkinson , Justin Wozniak , Frédéric Suter , Mallikarjun Shankar , Rafael Ferreira da Silva

MLPerf, an emerging machine learning benchmark suite strives to cover a broad range of applications of machine learning. We present a study on its characteristics and how the MLPerf benchmarks differ from some of the previous deep learning…

Machine Learning · Computer Science 2019-08-27 Snehil Verma , Qinzhe Wu , Bagus Hanindhito , Gunjan Jha , Eugene B. John , Ramesh Radhakrishnan , Lizy K. John

The fragmented landscape of quantum computer benchmarks, characterized by system-specific tools and inconsistent evaluation methodologies, hinders reliable cross-platform performance assessment. We introduce Metriq, an open-source…

HEPScore is a new CPU benchmark created to replace the HEPSPEC06 benchmark that is currently used by the WLCG for procurement, computing resource pledges and performance studies. The development of the new benchmark, based on HEP…

Applying post selection in each step of an iterated protocol leads to sensitive quantum dynamics that may be utilized to test and benchmark current quantum computers. An example of this type of protocols was originally proposed for the task…

Quantum Physics · Physics 2024-10-10 Adrian Ortega , Orsolya Kálmán , Tamás Kiss

The emergence of quantum computers as a new computational paradigm has been accompanied by speculation concerning the scope and timeline of their anticipated revolutionary changes. While quantum computing is still in its infancy, the…

CPU scheduling is the reason behind the performance of multiprocessing and in time-shared operating systems. Different scheduling criteria are used to evaluate Central Processing Unit Scheduling algorithms which are based on different…

Operating Systems · Computer Science 2022-05-17 Raghav Dalmia , Aryaman Sinha , Ruchi Verma , P. K. Gupta

The design of general purpose processors relies heavily on a workload gathering step in which representative programs are collected from various application domains. Processor performance, when running the workload set, is profiled using…

Performance · Computer Science 2018-01-05 Elie M. Shaccour , Mohammad M. Mansour

Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. Therefore, it is envisioned that a large-scale, geographically dispersed,…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-17 Blesson Varghese , Nan Wang , David Bermbach , Cheol-Ho Hong , Eyal de Lara , Weisong Shi , Christopher Stewart

The ability to collect statistics about the execution of a program within a CPU is of the utmost importance across all fields of computing since it allows characterizing the timing performance of a program. This capability is even more…

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

In the field of scientific computing, one often finds several alternative software packages (with open or closed source code) for solving a specific problem. These packages sometimes even use alternative methodological approaches, e.g.,…

The DEEP projects have developed a variety of hardware and software technologies aiming at improving the efficiency and usability of next generation high-performance computers. They evolve around an innovative concept for heterogeneous…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-11 Anke Kreuzer , Jorge Amaya , Norbert Eicker , Estela Suarez

The technological development of increasingly larger quantum processors on different quantum platforms raises the problem of how to fairly compare their performance, known as quantum benchmarking of quantum processors. This is a challenge…

Quantum Physics · Physics 2026-03-11 Arturo Acuaviva , David Aguirre , Rubén Peña , Mikel Sanz

Recent advances in probabilistic modelling have led to a large number of simulation-based inference algorithms which do not require numerical evaluation of likelihoods. However, a public benchmark with appropriate performance metrics for…

Machine Learning · Statistics 2021-04-12 Jan-Matthis Lueckmann , Jan Boelts , David S. Greenberg , Pedro J. Gonçalves , Jakob H. Macke