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During the past sixty years, a lot of effort has been made regarding the productive efficiency. Such endeavours provided an extensive bibliography on this subject, culminating in two main methods, named the Stochastic Frontier Analysis…

Optimization and Control · Mathematics 2019-08-14 Anibal Galindro , Micael Santos , Delfim F. M. Torres , Ana Marta-Costa

The continuous evolution of software projects necessitates the implementation of changes to enhance performance and reduce defects. This research explores effective strategies for learning and implementing useful changes in software…

Software Engineering · Computer Science 2025-04-18 Kartik Gupta

Throughput-oriented computing via co-running multiple applications in the same machine has been widely adopted to achieve high hardware utilization and energy saving on modern supercomputers and data centers. However, efficiently co-running…

Performance · Computer Science 2023-03-29 Hao Xu , Shuang Song , Ze Mao

Shared memory programming models usually provide worksharing and task constructs. The former relies on the efficient fork-join execution model to exploit structured parallelism; while the latter relies on fine-grained synchronization among…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-04-08 M. Maronas , K. Sala , S. Mateo , E. Ayguadé , V. Beltran Barcelona Supercomputing Center

We consider robust resource allocation of services in Clouds. More specifically, we consider the case of a large public or private Cloud platform that runs a relatively small set of large and independent services. These services are…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-22 Olivier Beaumont , Lionel Eyraud-Dubois , Paul Renaud-Goud

Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal…

Software Engineering · Computer Science 2021-01-15 Martin Shepperd , Stephen G. MacDonell

With the rapid development of big data technologies, how to dig out useful information from massive data becomes an essential problem. However, using machine learning algorithms to analyze large data may be time-consuming and inefficient on…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-14 Jiajun Shen

Performance of clustering algorithms is evaluated with the help of accuracy metrics. There is a great diversity of clustering algorithms, which are key components of many data analysis and exploration systems. However, there exist only few…

Data Structures and Algorithms · Computer Science 2019-02-18 Artem Lutov , Mourad Khayati , Philippe Cudré-Mauroux

The overall problem addressed in this paper is the long-standing problem of program correctness, and in particular programs that describe systems of parallel executing processes. We propose a new method for proving correctness of parallel…

Programming Languages · Computer Science 2023-02-10 Frank S. de Boer , Einar Broch Johnsen , Violet Ka I Pun , Silvia Lizeth Tapia Tarifa

In the bi-objective branch-and-bound literature, a key ingredient is objective branching, i.e. to create smaller and disjoint sub-problems in the objective space, obtained from the partial dominance of the lower bound set by the upper bound…

Data Structures and Algorithms · Computer Science 2023-09-26 Nicolas Forget , Sophie N. Parragh

Branch and bound algorithms have been developed for reliability analysis of coherent systems. They exhibit a set of advantages; in particular, they can find a computationally efficient representation of a system failure or survival event,…

Optimization and Control · Mathematics 2024-10-31 Ji-Eun Byun , Hyeuk Ryu , Daniel Straub

CFD users of supercomputers usually resort to rule-of-thumb methods to select the number of subdomains (partitions) when relying on MPI-based parallelization. One common approach is to set a minimum number of elements or cells per…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-30 G. Houzeaux , R. M. Badia , R. Borrell , D. Dosimont , J. Ejarque , M. Garcia-Gasulla , V. López

In this paper, we evaluate the performance of various parallel optimization methods for Kernel Support Vector Machines on multicore CPUs and GPUs. In particular, we provide the first comparison of algorithms with explicit and implicit…

Machine Learning · Computer Science 2014-04-04 Stephen Tyree , Jacob R. Gardner , Kilian Q. Weinberger , Kunal Agrawal , John Tran

The paper introduces PDSP-Bench, a novel benchmarking system designed for a systematic understanding of performance of parallel stream processing in a distributed environment. Such an understanding is essential for determining how Stream…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-16 Pratyush Agnihotri , Boris Koldehofe , Roman Heinrich , Carsten Binnig , Manisha Luthra

We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core - MIC) with a microscopy image analysis application. We experimentally evaluate the performance of computing devices on core…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-15 George Teodoro , Tahsin Kurc , Guilherme Andrade , Jun Kong , Renato Ferreira , Joel Saltz

Embedded Systems combine one or more processor cores with dedicated logic running on an ASIC or FPGA to meet design goals at reasonable cost. It is achieved by profiling the application with variety of aspects like performance, memory…

Performance · Computer Science 2013-12-12 Rajendra Patel , Arvind Rajwat

Sampling-based planning algorithms are the most common probabilistically complete algorithms and are widely used on many robot platforms. Within this class of algorithms, many variants have been proposed over the last 20 years, yet there is…

Robotics · Computer Science 2015-08-11 Mark Moll , Ioan A. Sucan , Lydia E. Kavraki

Since the advent of parallel algorithms in the C++17 Standard Template Library (STL), the STL has become a viable framework for creating performance-portable applications. Given multiple existing implementations of the parallel algorithms,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-12 Ruben Laso , Diego Krupitza , Sascha Hunold

Research in automatic parallelization of loop-centric programs started with static analysis, then broadened its arsenal to include dynamic inspection-execution and speculative execution, the best results involving hybrid static-dynamic…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-11-30 Riyadh Baghdadi , Albert Cohen , Cedric Bastoul , Louis-Noel Pouchet , Lawrence Rauchwerger

The processor accelerators are effective because they are working not (completely) on principles of stored program computers. They use some kind of parallelism, and it is rather hard to program them effectively: a parallel architecture by…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-26 János Végh
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