scholarly journals IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 93830-93846 ◽  
Author(s):  
Naoki Ishikawa
Keyword(s):  
Parallel Algorithms ◽  
Open Source ◽  
Massively Parallel ◽  
Reproducible Research ◽  
Index Modulation

scholarly journals Massively Parallel Algorithms for Distance Approximation and Spanners

2021 ◽  
Author(s):  
Amartya Shankha Biswas ◽  
Michal Dory ◽  
Mohsen Ghaffari ◽  
Slobodan Mitrović ◽  
Yasamin Nazari
Keyword(s):  
Parallel Algorithms ◽  
Massively Parallel ◽  
Distance Approximation

Practical aspects and experiences Scalable massively parallel algorithms for computational nanoelectronics

1997 ◽  
Vol 22 (14) ◽  
pp. 1931-1963 ◽  
Author(s):  
Xiaodong Wang ◽  
Vwani P. Roychowdhury ◽  
Pratheep Balasingam
Keyword(s):  
Parallel Algorithms ◽  
Massively Parallel

Massively parallel algorithms from physics and biology

2001 ◽  
Vol 77 (2) ◽  
pp. 201-250
Author(s):  
Lishan Kang ◽  
Yuanxiang Li ◽  
Zhengjun Pan ◽  
Jun He ◽  
David J. Evans
Keyword(s):  
Parallel Algorithms ◽  
Massively Parallel

Massively Parallel Open Source Encoding for Adaptive Streaming

SMPTE 2018 ◽  
2018 ◽  
Author(s):  
Alexander Giladi ◽  
Blake Orth ◽  
Douglas Bay ◽  
David Leach ◽  
Alex Balk
Keyword(s):  
Open Source ◽  
Massively Parallel ◽  
Adaptive Streaming ◽  
Source Encoding

scholarly journals GemPy 1.0: open-source stochastic geological modeling and inversion

2019 ◽  
Vol 12 (1) ◽  
pp. 1-32 ◽  
Author(s):  
Miguel de la Varga ◽  
Alexander Schaaf ◽  
Florian Wellmann
Keyword(s):  
Open Source ◽  
Code Generation ◽  
Raw Material ◽  
Reproducible Research ◽  
Geological Modeling ◽  
Fault Surface ◽  
Wide Range ◽  
Geological Models ◽  
Density Values ◽  
Efficient Code

Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications, ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research and applications in geological surveys. A wide range of methods exist to generate geological models. However, the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geomodeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D geological models, including fault networks, fault–surface interactions, unconformities and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (Theano) that enables a direct execution on GPUs. The functionality can be separated into the core aspects required to generate 3-D geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to machine-learning and Bayesian inference frameworks and thus a path to stochastic geological modeling and inversions. In addition, we provide methods to analyze model topology and to compute gravity fields on the basis of the geological models and assigned density values. In summary, we provide a basis for open scientific research using geological models, with the aim to foster reproducible research in the field of geomodeling.

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