Towards implementation of cellular automata in Microbial Fuel Cells. by Michail-Antisthenis I Tsompanas, Andrew Adamatzky, Georgios Ch Sirakoulis, John Greenman, Ioannis Ieropoulos

“…Arrays of MFCs could, in principle, act as massive-parallel computing devices with local connectivity between elementary processors. …”
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MOLOCH computer code for molecular-dynamics simulation of processes in condensed matter by Derbenev I.V., Ionov G.V., Dremov V.V., Sapozhnikov F.A., Chizhkova N.E.

“…It is a parallel code suitable for massive parallel computing. Modern programming techniques were used to make the code almost 100% efficient. …”
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FOCUS: fast Monte Carlo approach to coherence of undulator sources by M. Siano, G. Geloni, B. Paroli, D. Butti, T. Lefèvre, S. Mazzoni, G. Trad, U. Iriso, A. A. Nosych, L. Torino, M. A. C. Potenza

“…The core structure of the code, which is written in the language C++ accelerated with CUDA, combines an analytical description of the emitted electric fields and massively parallel computations on GPUs. The combination is rigorously justified by a statistical description of synchrotron radiation based on a Fourier optics approach. …”
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A GPU-accelerated parallel shooting algorithm for analysis of radio frequency and microwave integrated circuits by Liu, Xue-Xin, Yu, Hao, Tan, Sheldon X.-D.

“…The resulting periodic Arnoldi shooting method is very amenable for massive parallel computing, such as GPUs. Second, the periodic Arnoldi-based GMRES solver in the shooting-Newton method is parallelized on the recent NVIDIA Tesla GPU platforms. …”
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Multi-scale computational modelling in biology and physiology. by Southern, J, Pitt-Francis, J, Whiteley, J, Stokeley, D, Kobashi, H, Nobes, R, Kadooka, Y, Gavaghan, D

“…As even more complex models are developed over the coming few years, it will be necessary to develop new methods to model them (in particular in coupling across the interface between stochastic and deterministic processes) and new techniques will be required to compute their solutions efficiently on massively parallel computers. We outline how we envisage these developments occurring.…”

Unconstraint assignment problem : a molecular computing approach by Zuwairie, Ibrahim, Yusei, Tsuboi, Osamu, Ono, Marzuki, Khalid

“…During the massively parallel computation in atest tube, a series of bio-molecular reactions are employed and the output encoded also by DNA molecules can be printed andread out by electrophoretical fluorescent method. …”

Intrinsic Turbulence Stabilization in a Stellarator by P. Xanthopoulos, G. G. Plunk, A. Zocco, P. Helander

“…The magnetic surfaces of modern stellarators are characterized by complex, carefully optimized shaping and exhibit locally compressed regions of strong turbulence drive. Massively parallel computer simulations of plasma turbulence reveal, however, that stellarators also possess two intrinsic mechanisms to mitigate the effect of this drive. …”
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Simulation of a novel multiprocessor system based on dataflow principles by Zhou, Mo, S.M. Massachusetts Institute of Technology

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A Relaxed Quantization Training Method for Hardware Limitations of Resistive Random Access Memory (ReRAM)-Based Computing-in-Memory by Wei-Chen Wei, Chuan-Jia Jhang, Yi-Ren Chen, Cheng-Xin Xue, Syuan-Hao Sie, Jye-Luen Lee, Hao-Wen Kuo, Chih-Cheng Lu, Meng-Fan Chang, Kea-Tiong Tang

“…Nonvolatile computing-in-memory (nvCIM) exhibits high potential for neuromorphic computing involving massive parallel computations and for achieving high energy efficiency. nvCIM is especially suitable for deep neural networks, which are required to perform large amounts of matrix-vector multiplications. …”
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MemCA: All-Memristor Design for Deterministic and Probabilistic Cellular Automata Hardware Realization by Vasileios Ntinas, Iosif-Angelos Fyrigos, Rafailia-Eleni Karamani, Nikolaos Vasileiadis, Panagiotis Dimitrakis, Antonio Rubio, Georgios Ch. Sirakoulis

“…Inspired by the behavior of natural systems, Cellular Automata (CA) tackle the demanding long-distance information transfer of conventional computers by the massive parallel computation performed by a set of locally-coupled dynamical nodes. …”
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‘The Equator–Pole grid system’: an overset grid system for the sphere, with an optimal uniformity property by Göran Starius

“…The rectangular structure of the grids makes highly efficient implementation on massively parallel computer systems possible. Numerical experiments with the new grid system are carried out for two advection examples, namely smooth deformational flow and rotation of the Cosine bell, and for the test problems 2, 3, and 6 from Williamson et al., concerning the non-linear shallow water equations. …”
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TCN enhanced novel malicious traffic detection for IoT devices by Liu Xin, Liu Ziang, Zhang Yingli, Zhang Wenqiang, Lv Dong, Zhou Qingguo

“…Time Convolutional Network (TCN) is a high-speed neural network suitable for massively parallel computation. In this paper, we propose Multi-class S-TCN, an improved network supporting multiple classifications based on TCN for the practical needs of IoT scenarios. …”
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Parallel graph algorithms in constant adaptive rounds: theory meets practice by Behnezhad, Soheil, Dhulipala, Laxman, Esfandiari, Hossein, Lacki, Jakub, Mirrokni, Vahab, Schudy, Warren

“…In particular, we focus on the Adaptive Massively Parallel Computation (AMPC) model, which is a theoretical model that captures MapReduce-like computation augmented with a distributed hash table. …”
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An improved CUDA-based implementation of differential evolution on GPU by Raimondo, Federico, Forbes, Florence, Ong, Yew Soon, Qin, A. K.

“…Modern GPUs enable widely affordable personal computers to carry out massively parallel computation tasks. NVIDIA's CUDA technology provides a wieldy parallel computing platform. …”
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Dynamic communication performance of a Hierarchical 3D-Torus network by Rahman, M.M. Hafizur, Sato, Yukinori, Miura, Yasuyuki, Inoguchi, Yasushi

“…A Hierarchical 3D-Torus (H3DT) network is a 3D-torus network of multiple basic modules, in which the basic modules are 3D-mesh networks, has been proposed for efficient 3D massively parallel computers. The static network performance, the number of vertical links for 3D implementation, and the VLSI layout area of the H3DT network was investigated. …”
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Stochastic Computing Emulation of Memristor Cellular Nonlinear Networks by Oscar Camps, Mohamad Moner Al Chawa, Stavros G. Stavrinides, Rodrigo Picos

“…Cellular Nonlinear Networks (CNN) are a concept introduced in 1988 by Leon Chua and Lin Yang as a bio-inspired architecture capable of massively parallel computation. Since then, CNN have been enhanced by incorporating designs that incorporate memristors to profit from their processing and memory capabilities. …”
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Overview of the PALM model system 6.0 by B. Maronga, B. Maronga, S. Banzhaf, C. Burmeister, T. Esch, R. Forkel, D. Fröhlich, V. Fuka, K. F. Gehrke, J. Geletič, S. Giersch, T. Gronemeier, G. Groß, W. Heldens, A. Hellsten, F. Hoffmann, F. Hoffmann, F. Hoffmann, A. Inagaki, E. Kadasch, F. Kanani-Sühring, K. Ketelsen, B. A. Khan, C. Knigge, C. Knigge, H. Knoop, P. Krč, M. Kurppa, H. Maamari, A. Matzarakis, M. Mauder, M. Pallasch, D. Pavlik, J. Pfafferott, J. Resler, S. Rissmann, E. Russo, E. Russo, E. Russo, M. Salim, M. Salim, M. Schrempf, J. Schwenkel, G. Seckmeyer, S. Schubert, M. Sühring, R. von Tils, R. von Tils, L. Vollmer, L. Vollmer, S. Ward, B. Witha, B. Witha, H. Wurps, J. Zeidler, S. Raasch

“…The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in <span class="cit" id="xref_text.1"><a href="#bib1.bibx73">Maronga et al.…”
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Design and fabrication of networks for bacterial computing by Falco C M J M van Delft, Ayyappasamy Sudalaiyadum Perumal, Anja van Langen-Suurling, Charles de Boer, Ondřej Kašpar, Viola Tokárová, Frank W A Dirne, Dan V Nicolau

“…Non-deterministic polynomial (NP-) complete problems, whose number of possible solutions grows exponentially with the number of variables, require by necessity massively parallel computation. Because sequential computers, such as solid state-based ones, can solve only small instances of these problems within a reasonable time frame, parallel computation using motile biological agents in nano- and micro-scale networks has been proposed as an alternative computational paradigm. …”
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spiNNlink: FPGA-Based Interconnect for the Million-Core SpiNNaker System by Luis A. Plana, Jim Garside, Jonathan Heathcote, Jeffrey Pepper, Steve Temple, Simon Davidson, Mikel Lujan, Steve Furber

“…SpiNNaker is a massively-parallel computer system optimized for the simulation, in real time, of very large networks of spiking neurons. …”
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Symmetric and folded Tori connected Torus Network by Rahman, M.M. Hafizur, Inoguchi, Yasushi, Faisal, Faiz Al, Kundu, Monoz Kumar

“…Hierarchical interconnection networks provide high performance at low cost by exploring the locality that exists in the communication patterns of massively parallel computers. A Symmetric Tori connected Torus Network (STTN) is a 2D-torus network of multiple basic modules, in which the basic modules are 2D-torus networks that are hierarchically interconnected for higher-level networks. …”
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