scholarly journals The Maximum Common Subgraph Problem: A Parallel and Multi-Engine Approach

Computation ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 48 ◽  
Author(s):  
Stefano Quer ◽  
Andrea Marcelli ◽  
Giovanni Squillero
Keyword(s):  
Divide And Conquer ◽  
Parallel Applications ◽  
Practical Applications ◽  
Original Algorithm ◽  
Maximum Common Subgraph ◽  
Thread Pool ◽  
Cuda Programming ◽  
On Line ◽  
Gpu Architectures ◽  
Many Core

The maximum common subgraph of two graphs is the largest possible common subgraph, i.e., the common subgraph with as many vertices as possible. Even if this problem is very challenging, as it has been long proven NP-hard, its countless practical applications still motivates searching for exact solutions. This work discusses the possibility to extend an existing, very effective branch-and-bound procedure on parallel multi-core and many-core architectures. We analyze a parallel multi-core implementation that exploits a divide-and-conquer approach based on a thread pool, which does not deteriorate the original algorithmic efficiency and it minimizes data structure repetitions. We also extend the original algorithm to parallel many-core GPU architectures adopting the CUDA programming framework, and we show how to handle the heavily workload-unbalance and the massive data dependency. Then, we suggest new heuristics to reorder the adjacency matrix, to deal with “dead-ends”, and to randomize the search with automatic restarts. These heuristics can achieve significant speed-ups on specific instances, even if they may not be competitive with the original strategy on average. Finally, we propose a portfolio approach, which integrates all the different local search algorithms as component tools; such portfolio, rather than choosing the best tool for a given instance up-front, takes the decision on-line. The proposed approach drastically limits memory bandwidth constraints and avoids other typical portfolio fragility as CPU and GPU versions often show a complementary efficiency and run on separated platforms. Experimental results support the claims and motivate further research to better exploit GPUs in embedded task-intensive and multi-engine parallel applications.

Heuristic Algorithms for Waste Load Allocation in a River Basin

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1057-1064 ◽  
Author(s):  
Vijay Joshi ◽  
Prasad Modak
Keyword(s):  
Dynamic Programming ◽  
Heuristic Algorithms ◽  
Water Quality Management ◽  
User Preferences ◽  
Theory And Practice ◽  
Waste Load Allocation ◽  
Practical Applications ◽  
Waste Load ◽  
On Line ◽  
The One

Waste load allocation for rivers has been a topic of growing interest. Dynamic programming based algorithms are particularly attractive in this context and are widely reported in the literature. Codes developed for dynamic programming are however complex, require substantial computer resources and importantly do not allow interactions of the user. Further, there is always resistance to utilizing mathematical programming based algorithms for practical applications. There has been therefore always a gap between theory and practice in systems analysis in water quality management. This paper presents various heuristic algorithms to bridge this gap with supporting comparisons with dynamic programming based algorithms. These heuristics make a good use of the insight gained in the system's behaviour through experience, a process akin to the one adopted by field personnel and therefore can readily be understood by a user familiar with the system. Also they allow user preferences in decision making via on-line interaction. Experience has shown that these heuristics are indeed well founded and compare very favourably with the sophisticated dynamic programming algorithms. Two examples have been included which demonstrate such a success of the heuristic algorithms.

Proximal policy optimization with model-based methods

2022 ◽  
pp. 1-12
Author(s):  
Shuailong Li ◽  
Wei Zhang ◽  
Huiwen Zhang ◽  
Xin Zhang ◽  
Yuquan Leng
Keyword(s):  
Reinforcement Learning ◽  
State Of The Art ◽  
Transition Model ◽  
Practical Applications ◽  
Original Algorithm ◽  
Policy Performance ◽  
Model Based ◽  
Model Free ◽  
Future State ◽  
Policy Optimization

Model-free reinforcement learning methods have successfully been applied to practical applications such as decision-making problems in Atari games. However, these methods have inherent shortcomings, such as a high variance and low sample efficiency. To improve the policy performance and sample efficiency of model-free reinforcement learning, we propose proximal policy optimization with model-based methods (PPOMM), a fusion method of both model-based and model-free reinforcement learning. PPOMM not only considers the information of past experience but also the prediction information of the future state. PPOMM adds the information of the next state to the objective function of the proximal policy optimization (PPO) algorithm through a model-based method. This method uses two components to optimize the policy: the error of PPO and the error of model-based reinforcement learning. We use the latter to optimize a latent transition model and predict the information of the next state. For most games, this method outperforms the state-of-the-art PPO algorithm when we evaluate across 49 Atari games in the Arcade Learning Environment (ALE). The experimental results show that PPOMM performs better or the same as the original algorithm in 33 games.

scholarly journals Electrostatic Sensor Application for On-Line Monitoring of Wind Turbine Gearboxes

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3574 ◽  
Author(s):  
Huijie Mao ◽  
Hongfu Zuo ◽  
Han Wang
Keyword(s):  
Wind Turbine ◽  
Wear Debris ◽  
Bench Test ◽  
Recognition Method ◽  
Wind Turbine Gearbox ◽  
Practical Applications ◽  
Electrostatic Induction ◽  
Oil Flow ◽  
On Line ◽  
Application Potential

The oil-line electrostatic sensor (OLES) is a new online monitoring technology for wear debris based on the principle of electrostatic induction that has achieved good measurement results under laboratory conditions. However, for practical applications, the utility of the sensor is still unclear. The aim of this work was to investigate in detail the application potential of the electrostatic sensor for wind turbine gearboxes. Firstly, a wear debris recognition method based on the electrostatic sensor with two-probes is proposed. Further, with the wind turbine gearbox bench test, the performance of the electrostatic sensor and the effectiveness of the debris recognition method are comprehensively evaluated. The test demonstrates that the electrostatic sensor is capable of monitoring the debris and indicating the abnormality of the gearbox effectively using the proposed method. Moreover, the test also reveals that the background signal of the electrostatic sensor is related to the oil temperature and oil flow rate, but has no relationship to the working conditions of the gearbox. This research brings the electrostatic sensor closer to practical applications.

scholarly journals Static Mapping with Dynamic Switching of Multiple Data-Parallel Applications on Embedded Many-Core SoCs

2014 ◽  
Vol E97.D (11) ◽  
pp. 2827-2834 ◽  
Author(s):  
Ittetsu TANIGUCHI ◽  
Junya KAIDA ◽  
Takuji HIEDA ◽  
Yuko HARA-AZUMI ◽  
Hiroyuki TOMIYAMA
Keyword(s):  
Parallel Applications ◽  
Data Parallel ◽  
Dynamic Switching ◽  
Multiple Data ◽  
Many Core

Design and Development of an Instructional Program for Teaching Programming Processes to Gifted Students Using Scratch

2018 ◽  
pp. 61-99 ◽  
Author(s):  
Hatice Yıldız Durak ◽  
Tolga Güyer
Keyword(s):  
Resource Sharing ◽  
Computer Literacy ◽  
Gifted Students ◽  
Instructional Program ◽  
Practical Applications ◽  
Qualitative Research Study ◽  
Fourth Grade Students ◽  
On Line ◽  
Grade Level Differences ◽  
Student Independence

This chapter examines practical applications of an educational program designed to teach Turkish gifted second, third, and fourth grade students programming using Scratch, an online programming website (https://scratch.mit.edu). This qualitative research study was conducted with gifted identified students in an elementary school in Ankara's Altındağ district. Qualitative data collection methods were used. The study found program strengths included practical orientation, student independence, student free expression, computer literacy, and interdisciplinary connections. Additionally, providing a variety of tools and equipment, using Scratch, having a course web site, and on-line resource sharing were also seen as strengths by the participants. Perceived weaknesses were technical difficulties, the limited number of course hours, some of Scratch's negative features, inadequate help at particular points, and negative situations caused by gender and grade level differences. Results indicate preliminary knowledge of participant computer literacy as important to programming success.

Design and Development of an Instructional Program for Teaching Programming Processes to Gifted Students Using Scratch

2022 ◽  
pp. 127-155
Author(s):  
Hatice Yıldız Durak ◽  
Tolga Güyer
Keyword(s):  
Resource Sharing ◽  
Computer Literacy ◽  
Gifted Students ◽  
Instructional Program ◽  
Practical Applications ◽  
Qualitative Research Study ◽  
Fourth Grade Students ◽  
On Line ◽  
Grade Level Differences ◽  
Student Independence

This chapter examines practical applications of an educational program designed to teach Turkish gifted second, third, and fourth grade students programming using Scratch, an online programming website (https://scratch.mit.edu). This qualitative research study was conducted with gifted identified students in an elementary school in Ankara's Altındağ district. Qualitative data collection methods were used. The study found program strengths included practical orientation, student independence, student free expression, computer literacy, and interdisciplinary connections. Additionally, providing a variety of tools and equipment, using Scratch, having a course web site, and on-line resource sharing were also seen as strengths by the participants. Perceived weaknesses were technical difficulties, the limited number of course hours, some of Scratch's negative features, inadequate help at particular points, and negative situations caused by gender and grade level differences. Results indicate preliminary knowledge of participant computer literacy as important to programming success.

scholarly journals Service for parallel applications based on JINR cloud and HybriLIT resources

2019 ◽  
Vol 214 ◽  
pp. 07012 ◽  
Author(s):  
Nikita Balashov ◽  
Maxim Bashashin ◽  
Pavel Goncharov ◽  
Ruslan Kuchumov ◽  
Nikolay Kutovskiy ◽  
...  
Keyword(s):  
High Performance ◽  
Cloud Service ◽  
Parallel Applications ◽  
Cloud Infrastructure ◽  
Modular Architecture ◽  
Practical Applications ◽  
Speed Up ◽  
Scientific Results ◽  
Computational Resources ◽  
Performance Computing

Cloud computing has become a routine tool for scientists in many fields. The JINR cloud infrastructure provides JINR users with computational resources to perform various scientific calculations. In order to speed up achievements of scientific results the JINR cloud service for parallel applications has been developed. It consists of several components and implements a flexible and modular architecture which allows to utilize both more applications and various types of resources as computational backends. An example of using the Cloud&HybriLIT resources in scientific computing is the study of superconducting processes in the stacked long Josephson junctions (LJJ). The LJJ systems have undergone intensive research because of the perspective of practical applications in nano-electronics and quantum computing. In this contribution we generalize the experience in application of the Cloud&HybriLIT resources for high performance computing of physical characteristics in the LJJ system.

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