Risk-aware optimized quickest path computing technique for critical routing services

2021 ◽  
Vol 95 ◽  
pp. 107436
Author(s):  
Ashutosh Sharma ◽  
Piotr Cholda ◽  
Rajiv Kumar ◽  
Gaurav Dhiman
Keyword(s):  
Computing Technique ◽  
Quickest Path

scholarly journals Neuro-Inspired Computing with Spin-VCSELs

2021 ◽  
Vol 11 (9) ◽  
pp. 4232
Author(s):  
Krishan Harkhoe ◽  
Guy Verschaffelt ◽  
Guy Van der Sande
Keyword(s):  
Processing Speed ◽  
Delay Time ◽  
High Speed ◽  
State Of The Art ◽  
Polarization Modulation ◽  
Time Interval ◽  
Computing Technique ◽  
High Modulation ◽  
Short Time ◽  
Modulation Speed

Delay-based reservoir computing (RC), a neuromorphic computing technique, has gathered lots of interest, as it promises compact and high-speed RC implementations. To further boost the computing speeds, we introduce and study an RC setup based on spin-VCSELs, thereby exploiting the high polarization modulation speed inherent to these lasers. Based on numerical simulations, we benchmarked this setup against state-of-the-art delay-based RC systems and its parameter space was analyzed for optimal performance. The high modulation speed enabled us to have more virtual nodes in a shorter time interval. However, we found that at these short time scales, the delay time and feedback rate heavily influence the nonlinear dynamics. Therefore, and contrary to other laser-based RC systems, the delay time has to be optimized in order to obtain good RC performances. We achieved state-of-the-art performances on a benchmark timeseries prediction task. This spin-VCSEL-based RC system shows a ten-fold improvement in processing speed, which can further be enhanced in a straightforward way by increasing the birefringence of the VCSEL chip.

scholarly journals A Hydrodynamic-Based Robust Numerical Model for Debris Hazard and Risk Assessment

2021 ◽  
Vol 13 (14) ◽  
pp. 7955
Author(s):  
Yongde Kang ◽  
Jingming Hou ◽  
Yu Tong ◽  
Baoshan Shi
Keyword(s):  
Numerical Model ◽  
Debris Flow ◽  
Finite Volume ◽  
Graphics Processing Unit ◽  
Morphological Changes ◽  
Finite Volume Scheme ◽  
Processing Unit ◽  
Algebraic Equations ◽  
Flow Process ◽  
Computing Technique

Debris flow simulations are important in practical engineering. In this study, a graphics processing unit (GPU)-based numerical model that couples hydrodynamic and morphological processes was developed to simulate debris flow, transport, and morphological changes. To accurately predict the debris flow sediment transport and sediment scouring processes, a GPU-based parallel computing technique was used to accelerate the calculation. This model was created in the framework of a Godunov-type finite volume scheme and discretized into algebraic equations by the finite volume method. The mass and momentum fluxes were computed using the Harten, Lax, and van Leer Contact (HLLC) approximate Riemann solver, and the friction source terms were calculated using the proposed splitting point-implicit method. These values were evaluated using a novel 2D edge-based MUSCL scheme. The code was programmed using C++ and CUDA, which can run on GPUs to substantially accelerate the computation. After verification, the model was applied to the simulation of the debris flow process of an idealized example. The results of the new scheme better reflect the characteristics of the discontinuity of its movement and the actual law of the evolution of erosion and deposition over time. The research results provide guidance and a reference for the in-depth study of debris flow processes and disaster prevention and mitigation.

scholarly journals Internet packet routing: Application of a K-quickest path algorithm

2007 ◽  
Vol 181 (3) ◽  
pp. 1045-1054 ◽  
Author(s):  
João C.N. Clímaco ◽  
Marta M.B. Pascoal ◽  
José M.F. Craveirinha ◽  
M. Eugénia V. Captivo
Keyword(s):  
Packet Routing ◽  
Quickest Path

Utilization of Soft Computing Techniques in Sputtering Processes: A Review

2013 ◽  
Vol 832 ◽  
pp. 260-265
Author(s):  
Norlina M. Sabri ◽  
Mazidah Puteh ◽  
Mohamad Rusop Mahmood
Keyword(s):  
Soft Computing ◽  
Process Parameters ◽  
Optimization Techniques ◽  
Future Research ◽  
Film Properties ◽  
Reliable Technique ◽  
Computing Technique ◽  
Optimization Of Process Parameters ◽  
Soft Computing Techniques ◽  
Soft Computing Technique

This paper presents an overview of research works on the utilizing of soft computing in the optimization of process parameters and in the prediction of thin film properties in sputtering processes. The papers from this review were obtained from relevant databases and from various scientific journals. The papers collected were published from 2008 to 2012. The focus of the review is to provide an outlook on the utilization of soft computing techniques in sputtering processes. Based on the review, the soft computing techniques which have been applied so far are ANN, GA and Fuzzy Logic. The first finding of this review is that soft computing technique is a promising and more reliable approach to optimize and predict process parameters compared to the traditional methods. The second finding is that the utilizing of soft computing techniques in sputtering processes are still limited and still in exploratory phase as they have not yet been extensively and stably applied. The techniques applied are also limited to ANN, GA and Fuzzy, whereas the exploration into other techniques is also necessary to be conducted in order to seek the most reliable technique and so as to expand the application of soft computing approach. Future research could focus on the exploration of other soft computing techniques for optimization in order to find the best optimization techniques based on the specific processes.

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