The following 478 citations reference one of the FLAME GPU publications.

  1. PD Vouzis and NV Sahinidis, GPU-BLAST: using graphics processors to accelerate protein sequence alignment (2011) - 273 Citations

  2. P Richmond and D Walker and S Coakley, High performance cellular level agent-based simulation with FLAME for the GPU (2010) - 199 Citations

  3. JO Dada and P Mendes, Multi-scale modelling and simulation in systems biology (2011) - 178 Citations

  4. E Bartocci and P Lió, Computational modeling, formal analysis, and tools for systems biology (2016) - 151 Citations

  5. L Dematté and D Prandi, GPU computing for systems biology (2010) - 147 Citations

  6. M Kiran and P Richmond and M Holcombe and LS Chin, FLAME: simulating large populations of agents on parallel hardware architectures (2010) - 115 Citations

  7. S Coakley and M Gheorghe and M Holcombe, Exploitation of high performance computing in the flame agent-based simulation framework (2012) - 107 Citations

  8. MS Nobile and P Cazzaniga and A Tangherloni, Graphics processing units in bioinformatics, computational biology and systems biology (2017) - 91 Citations

  9. S Christley and B Lee and X Dai and Q Nie, Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms (2010) - 72 Citations

  10. GB White, The community cyber security maturity model (2011) - 63 Citations

  11. HR Parry and M Bithell, Large scale agent-based modelling: A review and guidelines for model scaling (2012) - 63 Citations

  12. E Rustico and G Bilotta and A Herault, Advances in multi-GPU smoothed particle hydrodynamics simulations (2012) - 62 Citations

  13. GA Northrop and PF Lu, A semi-custom design flow in high-performance microprocessor design (2001) - 54 Citations

  14. D Tartarini and E Mele, Adult stem cell therapies for wound healing: biomaterials and computational models (2016) - 52 Citations

  15. A Marshall-Colon and SP Long and DK Allen and G Allen, Crops in silico: generating virtual crops using an integrative and multi-scale modeling platform (2017) - 51 Citations

  16. W Tang and DA Bennett and S Wang, A parallel agent-based model of land use opinions (2011) - 46 Citations

  17. MJ Korth and N Tchitchek and AG Benecke and MG Katze, Systems approaches to influenza-virus host interactions and the pathogenesis of highly virulent and pandemic viruses (2013) - 44 Citations

  18. J Jones, Influences on the formation and evolution of Physarum polycephalum inspired emergent transport networks (2011) - 43 Citations

  19. N Jagiella and D Rickert and FJ Theis and J Hasenauer, Parallelization and high-performance computing enables automated statistical inference of multi-scale models (2017) - 41 Citations

  20. T Karmakharm and P Richmond and DM Romano, Agent-based Large Scale Simulation of Pedestrians With Adaptive Realistic Navigation Vector Fields. (2010) - 38 Citations

  21. A Borzabadi-Farahani, An overview of selected orthodontic treatment need indices (2011) - 38 Citations

  22. H Kaul and Y Ventikos, Investigating biocomplexity through the agent-based paradigm (2015) - 38 Citations

  23. T Karmakharm and P Richmond and DM Romano, Agent-based Large Scale Simulation of Pedestrians With Adaptive Realistic Navigation Vector Fields. (2010) - 38 Citations

  24. W Tang and DA Bennett, Reprint of: Parallel agent-based modeling of spatial opinion diffusion accelerated using graphics processing units (2012) - 35 Citations

  25. P Richmond and S Coakley, Cellular level agent based modelling on the graphics processing unit (2009) - 35 Citations

  26. A Erlichson and BA Nayfeh and JP Singh, The benefits of clustering in shared address space multiprocessors: An applications-driven investigation (1995) - 32 Citations

  27. P Richmond and D Romano, Template-driven agent-based modeling and simulation with CUDA (2011) - 31 Citations

  28. JL Cross and E Hamner and C Bartley, Arts & Bots: application and outcomes of a secondary school robotics program (2015) - 31 Citations

  29. M Gutiérrez and P Gregorio-Godoy, A New Improved and Extended Version of the Multicell Bacterial Simulator gro (2017) - 31 Citations

  30. X Rubio-Campillo, Pandora: A versatile agent-based modelling platform for social simulation (2014) - 29 Citations

  31. MJ Gibson and EC Keedwell and DA Savić, An investigation of the efficient implementation of cellular automata on multi-core CPU and GPU hardware (2015) - 28 Citations

  32. AV Husselmann and KA Hawick, Simulating species interactions and complex emergence in multiple flocks of boids with gpus (2011) - 28 Citations

  33. CE Vincenot, How new concepts become universal scientific approaches: insights from citation network analysis of agent-based complex systems science (2018) - 27 Citations

  34. H Kaul and Z Cui and Y Ventikos, A multi-paradigm modeling framework to simulate dynamic reciprocity in a bioreactor (2013) - 27 Citations

  35. K Zia and K Farrahi and A Riener and A Ferscha, An agent-based parallel geo-simulation of urban mobility during city-scale evacuation (2013) - 27 Citations

  36. E Rustico and G Bilotta and G Gallo and A Herault, Smoothed particle hydrodynamics simulations on multi-GPU systems (2012) - 26 Citations

  37. CM Glen and ML Kemp and EO Voit, Agent-based modeling of morphogenetic systems: Advantages and challenges (2019) - 26 Citations

  38. C Hüning and M Adebahr and T Thiel-Clemen, Modeling & simulation as a service with the massive multi-agent system MARS (2016) - 25 Citations

  39. N Fachada and VV Lopes and RC Martins and AC Rosa, Parallelization strategies for spatial agent-based models (2017) - 24 Citations

  40. L Dematte, Smoldyn on graphics processing units: massively parallel Brownian dynamics simulations (2011) - 24 Citations

  41. S Scarle, Implications of the Turing completeness of reaction-diffusion models, informed by GPGPU simulations on an XBox 360: Cardiac arrhythmias, re-entry and the Halting … (2009) - 24 Citations

  42. W Tang and M Jia, Global sensitivity analysis of a large agent-based model of spatial opinion exchange: A heterogeneous multi-GPU acceleration approach (2014) - 23 Citations

  43. G Vigueras and JM Orduna and M Lozano, A distributed visualization system for crowd simulations (2011) - 23 Citations

  44. F Azuaje, Computational discrete models of tissue growth and regeneration (2011) - 22 Citations

  45. Y Mualla and W Bai and S Galland and C Nicolle, Comparison of agent-based simulation frameworks for unmanned aerial transportation applications (2018) - 21 Citations

  46. B Hernandez and H Pérez and I Rudomin and S Ruiz, Simulating and visualizing real-time crowds on GPU clusters (2014) - 21 Citations

  47. P Heywood and S Maddock and J Casas and D Garcia, Data-parallel agent-based microscopic road network simulation using graphics processing units (2018) - 20 Citations

  48. P Heywood and S Maddock and J Casas and D Garcia, Data-parallel agent-based microscopic road network simulation using graphics processing units (2018) - 20 Citations

  49. G Laville and K Mazouzi and C Lang and N Marilleau, MCMAS: a toolkit to benefit from many-core architecure in agent-based simulation (2013) - 20 Citations

  50. P Heywood and S Maddock and J Casas and D Garcia, Data-parallel agent-based microscopic road network simulation using graphics processing units (2018) - 20 Citations

  51. D Dranidis and K Bratanis and F Ipate, JSXM: A tool for automated test generation (2012) - 19 Citations

  52. F Lorig and N Dammenhayn and DJ Müller and IJ Timm, Measuring and comparing scalability of agent-based simulation frameworks (2015) - 19 Citations

  53. S Ruiz and B Hernández and A Alvarado, Reducing memory requirements for diverse animated crowds (2013) - 19 Citations

  54. J Wang and N Rubin and H Wu and S Yalamanchili, Accelerating simulation of agent-based models on heterogeneous architectures (2013) - 18 Citations

  55. DG Harvey and AG Fletcher and JM Osborne, A parallel implementation of an off-lattice individual-based model of multicellular populations (2015) - 17 Citations

  56. M Falk and M Ott and T Ertl and M Klann and H Koeppl, Parallelized agent-based simulation on CPU and graphics hardware for spatial and stochastic models in biology (2011) - 17 Citations

  57. X Li and W Cai and SJ Turner, Supporting efficient execution of continuous space agent‐based simulation on GPU (2016) - 17 Citations

  58. W Chen and K Ward and Q Li and V Kecman, Agent based modeling of blood coagulation system: implementation using a GPU based high speed framework (2011) - 17 Citations

  59. P Richmond and L Buesing and M Giugliano and E Vasilaki, Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations (2011) - 16 Citations

  60. B Cosenza and N Popov and B Juurlink and P Richmond, OpenABL: a domain-specific language for parallel and distributed agent-based simulations (2018) - 16 Citations

  61. B Cosenza and N Popov and B Juurlink and P Richmond, OpenABL: a domain-specific language for parallel and distributed agent-based simulations (2018) - 16 Citations

  62. K DeMarco and E Squires and M Day and C Pippin, Simulating collaborative robots in a massive multi-agent game environment (scrimmage) (2019) - 16 Citations

  63. U Erra and B Frola and V Scarano, BehaveRT: a GPU-based library for autonomous characters (2010) - 16 Citations

  64. DM Rhodes and SA Smith and M Holcombe and EE Qwarnstrom, Computational modelling of NF-κB activation by IL-1RI and its co-receptor TILRR, predicts a role for cytoskeletal sequestration of IκBα in inflammatory … (2015) - 15 Citations

  65. BSS Onggo, Running agent-based models on a discrete-event simulator (2010) - 15 Citations

  66. G D’Angelo and S Ferretti and V Ghini, Distributed hybrid simulation of the internet of things and smart territories (2018) - 15 Citations

  67. A Saprykin and N Chokani and RS Abhari, GEMSim: A GPU-accelerated multi-modal mobility simulator for large-scale scenarios (2019) - 15 Citations

  68. N Seekhao and C Shung and J JaJa, Real-time agent-based modeling simulation with in-situ visualization of complex biological systems: A case study on vocal fold inflammation and healing (2016) - 15 Citations

  69. F Michel, Intégration du calcul sur GPU dans la plate-forme de simulation multi-agent générique TurtleKit 3 (2013) - 15 Citations

  70. C Márquez and E César and J Sorribes, A load balancing schema for agent-based spmd applications (2013) - 15 Citations

  71. F Messina and G Pappalardo, Exploiting gpus to simulate complex systems (2013) - 15 Citations

  72. J Xiao and P Andelfinger and D Eckhoff and W Cai, A survey on agent-based simulation using hardware accelerators (2019) - 15 Citations

  73. D Moser and A Riener and K Zia, Comparing parallel simulation of social agents using cilk and opencl (2011) - 15 Citations

  74. J Xiao and P Andelfinger and D Eckhoff and W Cai, A survey on agent-based simulation using hardware accelerators (2019) - 15 Citations

  75. H Bai and MD Rolfe and W Jia and S Coakley, Agent-Based Modeling of Oxygen-Responsive Transcription Factors in Escherichia coli (2014) - 14 Citations

  76. F Michel, Translating Agent Perception Computations into Environmental Processes in Multi‐Agent‐Based Simulations: A means for Integrating Graphics Processing Unit … (2013) - 14 Citations

  77. MK Chimeh and P Richmond, Simulating heterogeneous behaviours in complex systems on GPUs (2018) - 14 Citations

  78. P Richmond and MK Chimeh, Flame gpu: Complex system simulation framework (2017) - 14 Citations

  79. P Richmond and MK Chimeh, Flame gpu: Complex system simulation framework (2017) - 14 Citations

  80. F Borges and A Gutierrez-Milla and E Luque, Care HPS: A high performance simulation tool for parallel and distributed agent-based modeling (2017) - 14 Citations

  81. J Wąs and H Mróz and P Topa, GPGPU computing for microscopic simulations of crowd dynamics (2015) - 14 Citations

  82. AV Husselmann and KA Hawick, Spatial agent-based modelling and simulations-a review (2011) - 14 Citations

  83. MK Chimeh and P Richmond, Simulating heterogeneous behaviours in complex systems on GPUs (2018) - 14 Citations

  84. P Richmond and MK Chimeh, Flame gpu: Complex system simulation framework (2017) - 14 Citations

  85. P Richmond and MK Chimeh, Flame gpu: Complex system simulation framework (2017) - 14 Citations

  86. P Richmond and MK Chimeh, Flame gpu: Complex system simulation framework (2017) - 14 Citations

  87. X Li and W Cai and SJ Turner, Cloning agent-based simulation (2017) - 13 Citations

  88. MA Rahman and RC Muniyandi, Review of GPU implementation to process of RNA sequence on cancer (2018) - 13 Citations

  89. X Li and W Cai and SJ Turner, Cloning agent-based simulation (2017) - 13 Citations

  90. W Blewitt and G Ushaw and G Morgan, Applicability of gpgpu computing to real-time ai solutions in games (2013) - 12 Citations

  91. E Hermellin and F Michel, GPU Delegation: Toward a Generic Approach for Developing MABS using GPU Programming (2016) - 12 Citations

  92. M Soheilypour and MRK Mofrad, Agent‐based modeling in molecular systems biology (2018) - 12 Citations

  93. P Germann and M Marin-Riera and J Sharpe, [**ya   a: GPU-powered Spheroid Models for Mesenchyme and Epithelium**](https://www.sciencedirect.com/science/article/pii/S2405471219300687) (2019) - 12 Citations

  94. M Yang and P Andelfinger and W Cai and A Knoll, Evaluation of conflict resolution methods for agent-based simulations on the GPU (2018) - 12 Citations

  95. MF McGuire and MS Iyengar and DW Mercer, Computational approaches for translational clinical research in disease progression (2011) - 11 Citations

  96. S Coakley and P Richmond and M Gheorghe and S Chin, Large-scale simulations with FLAME (2016) - 11 Citations

  97. G Cordasco and V Scarano and C Spagnuolo, Distributed MASON: A scalable distributed multi-agent simulation environment (2018) - 11 Citations

  98. S Coakley and P Richmond and M Gheorghe and S Chin, Large-scale simulations with FLAME (2016) - 11 Citations

  99. S Coakley and P Richmond and M Gheorghe and S Chin, Large-scale simulations with FLAME (2016) - 11 Citations

  100. M Burkitt and D Walker and DM Romano and A Fazeli, Modelling sperm behaviour in a 3D environment (2011) - 10 Citations

  101. P Richmond, Resolving conflicts between multiple competing agents in parallel simulations (2014) - 10 Citations

  102. J Li and V Sharma and N Ganesan, Simulation and study of large-scale bacteria-materials interactions via bioscape enabled by gpus (2012) - 10 Citations

  103. G Laville and K Mazouzi and C Lang, Using GPU for multi-agent soil simulation (2013) - 10 Citations

  104. P Richmond, Resolving conflicts between multiple competing agents in parallel simulations (2014) - 10 Citations

  105. T Karmakharm and P Richmond, Large Scale Pedestrian Multi-Simulation for a Decision Support Tool. (2012) - 10 Citations

  106. M Burkitt and D Walker and DM Romano and A Fazeli, Modelling sperm behaviour in a 3D environment (2011) - 10 Citations

  107. P Richmond, Resolving conflicts between multiple competing agents in parallel simulations (2014) - 10 Citations

  108. P Richmond, Resolving conflicts between multiple competing agents in parallel simulations (2014) - 10 Citations

  109. S Tamrakar and P Richmond and RM D’Souza, PI-FLAME: A parallel immune system simulator using the FLAME graphic processing unit environment (2017) - 9 Citations

  110. F Cicirelli and L Nigro, An agent framework for high performance simulations over multi-core clusters (2013) - 9 Citations

  111. G An and S Christley, Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling (2012) - 9 Citations

  112. VN Leonenko and NV Pertsev and M Artzrouni, Using high performance algorithms for the hybrid simulation of disease dynamics on CPU and GPU (2015) - 9 Citations

  113. L Dematté, Parallel particle-based reaction diffusion: a GPU implementation (2010) - 9 Citations

  114. DM Romano and L Lomax, NARCSim an agent-based illegal drug market simulation (2009) - 9 Citations

  115. L Juanzi and XU Bin and Y Wenjun and C Dewei, Sewsip: semantic based web services integration in p2p (2005) - 9 Citations

  116. S Tamrakar and P Richmond and RM D’Souza, PI-FLAME: A parallel immune system simulator using the FLAME graphic processing unit environment (2017) - 9 Citations

  117. J Lifflander and GC Evans and A Arya, Dynamic scheduling for work agglomeration on heterogeneous clusters (2012) - 8 Citations

  118. M Burkitt and D Walker and DM Romano and A Fazeli, Computational modelling of maternal interactions with spermatozoa: potentials and prospects (2011) - 8 Citations

  119. P Taillandier and M Bourgais and A Drogoul, Using parallel computing to improve the scalability of models with BDI agents (2017) - 8 Citations

  120. S Konur and M Kiran and M Gheorghe, Agent-based high-performance simulation of biological systems on the GPU (2015) - 8 Citations

  121. P Tučník and V Bureš, Experimental evaluation of suitability of selected multi-criteria decision-making methods for large-scale agent-based simulations (2016) - 8 Citations

  122. B Herd, Statistical runtime verification of agent-based simulations (2015) - 8 Citations

  123. Z Li and X Guan and R Li and H Wu, 4d-sas: A distributed dynamic-data driven simulation and analysis system for massive spatial agent-based modeling (2016) - 8 Citations

  124. D Agarwal, Crayons: An azure cloud based parallel system for GIS overlay operations (2012) - 8 Citations

  125. A Pellegrini and F Quaglia, Programmability and performance of parallel ECS-based simulation of multi-agent exploration models (2014) - 7 Citations

  126. A Voss and JY You and E Yen and HY Chen and S Lin, Scalable social simulation: investigating population-scale phenomena using commodity computing (2010) - 7 Citations

  127. RE Falconer and AN Houston, Visual simulation of soil-microbial system using GPGPU technology (2015) - 7 Citations

  128. E Hermellin and F Michel, Gpu environmental delegation of agent perceptions: Application to reynolds’s boids (2015) - 7 Citations

  129. N Seekhao and J JaJa and L Mongeau, In situ visualization for 3D agent-based vocal fold inflammation and repair simulation (2017) - 7 Citations

  130. G Pérez-Rodríguez and M Pérez-Pérez, High performance computing for three-dimensional agent-based molecular models (2016) - 7 Citations

  131. M Starzec and G Starzec and A Byrski and W Turek, Distributed ant colony optimization based on actor model (2019) - 7 Citations

  132. M Cardinot and C O’Riordan and J Griffith and M Perc, Evoplex: A platform for agent-based modeling on networks (2019) - 7 Citations

  133. O Rihawi and Y Secq and P Mathieu, Relaxing synchronization constraints in distributed agent-based simulations (2013) - 7 Citations

  134. C Montañola-Sales and BSS Onggo and J Casanovas-Garcia, Approaching parallel computing to simulating population dynamics in demography (2016) - 6 Citations

  135. N Seekhao and C Shung and J JaJa and L Mongeau, High-performance agent-based modeling applied to vocal fold inflammation and repair (2018) - 6 Citations

  136. MJ Gibson and EC Keedwell and D Savić, Understanding the efficient parallelisation of cellular automata on CPU and GPGPU hardware (2013) - 6 Citations

  137. L Gill and EA Hathway and E Lange and E Morgan, Coupling real-time 3D landscape models with microclimate simulations (2013) - 6 Citations

  138. H Perez and B Hernandez and I Rudomin, Task-based crowd simulation for heterogeneous architectures (2016) - 6 Citations

  139. N Bezirgiannis and I Prasetya, HLogo: A parallel Haskell variant of NetLogo (2016) - 6 Citations

  140. N Seekhao and C Shung and J JaJa and L Mongeau, High-performance agent-based modeling applied to vocal fold inflammation and repair (2018) - 6 Citations

  141. B Herd and S Miles and P McBurney and M Luck, : A Monte Carlo Model Checker for Multiagent-Based Simulations (2015) - 6 Citations

  142. L Chen and B Liu and H Hu and Q Zheng, A layered malware detection model using VMM (2012) - 6 Citations

  143. H Perez and B Hernandez and I Rudomin, Task-based crowd simulation for heterogeneous architectures (2016) - 6 Citations

  144. N Seekhao and C Shung and J JaJa and L Mongeau, High-performance agent-based modeling applied to vocal fold inflammation and repair (2018) - 6 Citations

  145. A Jeannin-Girardon and P Ballet and V Rodin, An efficient biomechanical cell model to simulate large multi-cellular tissue morphogenesis: application to cell sorting simulation on GPU (2013) - 5 Citations

  146. F Michel, GPU environmental delegation of agent perceptions for MABS (2012) - 5 Citations

  147. S Christley and G An, Agent-based modeling in translational systems biology (2013) - 5 Citations

  148. T Spiesser and C Kühn and M Krantz and E Klipp, The MYpop toolbox: Putting yeast stress responses in cellular context on single cell and population scales (2016) - 5 Citations

  149. L Martí-Bonmatí and Á Alberich-Bayarri, PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers (2020) - 5 Citations

  150. Y Song and S Yang and J Lei, ParaCells: A GPU architecture for cell-centered models in computational biology (2018) - 5 Citations

  151. N Ganesan and J Li and V Sharma and H Jiang, Process simulation of complex biological pathways in physical reactive space and reformulated for massively parallel computing platforms (2015) - 5 Citations

  152. MK Chimeh and P Heywood and M Pennisi and F Pappalardo, Parallelisation strategies for agent based simulation of immune systems (2019) - 5 Citations

  153. E Hermellin and F Michel and J Ferber, Systèmes Multi-Agents et GPGPU: état des lieux et directions pour l’avenir (2014) - 5 Citations

  154. PA Laplante, Encyclopedia of computer science and technology (2017) - 5 Citations

  155. C Márquez and E César and J Sorribes, Agent migration in HPC systems using FLAME (2013) - 5 Citations

  156. CJ Wright and P McMinn and J Gallardo, Towards the automatic identification of faulty multi-agent based simulation runs using MASTER (2012) - 5 Citations

  157. M Starzec and G Starzec and A Byrski and W Turek, Desynchronization in distributed Ant Colony Optimization in HPC environment (2020) - 5 Citations

  158. P Sethia, High performance multi-agent system based simulations (2011) - 5 Citations

  159. A Husselmann, Data-parallel structural optimisation in agent-based modelling (2014) - 5 Citations

  160. M Springer and H Masuhara, Ikra-Cpp: A C++/CUDA DSL for object-oriented programming with structure-of-arrays layout (2018) - 5 Citations

  161. LZ Granville and GAF de Sá Coelho, An architecture for automated replacement of QoS policies (2002) - 5 Citations

  162. Y Song and S Yang and J Lei, ParaCells: A GPU architecture for cell-centered models in computational biology (2018) - 5 Citations

  163. D Dharma and C Jonathan, Material point method based fluid simulation on GPU using compute shader (2017) - 5 Citations

  164. E Hermellin and F Michel and J Ferber, Systèmes Multi-Agents et GPGPU: état des lieux et directions pour l’avenir (2014) - 5 Citations

  165. MK Chimeh and P Heywood and M Pennisi and F Pappalardo, Parallelisation strategies for agent based simulation of immune systems (2019) - 5 Citations

  166. G Laville and C Lang and B Herrmann, MCMAS: A toolkit for developing agent-based simulations on many-core architectures (2015) - 5 Citations

  167. AG Salguero and AJ Tomeu-Hardasmal, Dynamic load balancing strategy for parallel tumor growth simulations (2019) - 4 Citations

  168. R Lefticaru and LF Macías-Ramos and IM Niculescu, Agent-Based Simulation of Kernel P Systems with Division Rules Using FLAME (2016) - 4 Citations

  169. M Keenan and I Komarov and RM D’Souza, Novel graphics processing unit-based parallel algorithms for understanding species diversity in forests (2012) - 4 Citations

  170. A Jeannin-Girardon and P Ballet, Large scale tissue morphogenesis simulation on heterogenous systems based on a flexible biomechanical cell model (2015) - 4 Citations

  171. L Cui and J Chen and Y Hu and J Xiong and Z Feng, Acceleration of multi-agent simulation on FPGAs (2011) - 4 Citations

  172. C Braun and M Daub and A Schöll and G Schneider, Parallel simulation of apoptotic receptor-clustering on GPGPU many-core architectures (2012) - 4 Citations

  173. JC Steuben, Massively parallel engineering simulations on graphics processors: parallelization, synchronization, and approximation (2014) - 4 Citations

  174. RA Williams, An agent-based model of the IL-1 stimulated nuclear factor-kappa B signalling pathway (2014) - 4 Citations

  175. L Kosiachenko and N Hart and M Fukuda, MASS CUDA: a general GPU parallelization framework for agent-based models (2019) - 4 Citations

  176. L Cui and J Chen and Y Hu and J Xiong and Z Feng, Acceleration of multi-agent simulation on FPGAs (2011) - 4 Citations

  177. RB Greaves and FAC Polack and J Forrester, CoSMoS in the context of social-ecological systems research (2012) - 4 Citations

  178. RA Williams, An agent-based model of the IL-1 stimulated nuclear factor-kappa B signalling pathway (2014) - 4 Citations

  179. M Kiran and K Maiyama and H Mir, Agent-based modelling as a service on amazon EC2: opportunities and challenges (2015) - 4 Citations

  180. JR Bilbao-Castro and G Barrionuevo, Weaver: A multiagent, spatial-explicit and high-performance framework to study complex ecological networks (2015) - 4 Citations

  181. D Liu and S Xu, A combined concept location method for java programs (2007) - 4 Citations

  182. S Tripodi and P Ballet and V Rodin, GPU implementation and performance analysis of reactive agents having division and mobility capacities (2012) - 4 Citations

  183. L Cui and J Chen and Y Hu and J Xiong and Z Feng, Acceleration of multi-agent simulation on FPGAs (2011) - 4 Citations

  184. M Shirvani and G Kesserwani and P Richmond, Agent-based simulator of dynamic flood-people interactions (2019) - 4 Citations

  185. LK Luhunu, Survey of template-based code generation (2017) - 4 Citations

  186. M Callejas-Cuervo and HA Valero-Bustos, Measurement of service quality of a public transport system, through agent-based simulation software (2019) - 4 Citations

  187. M Shirvani and G Kesserwani and P Richmond, Agent-based simulator of dynamic flood-people interactions (2019) - 4 Citations

  188. H Gehlot and X Zhan and X Qian and C Thompson, A-RESCUE 2.0: A High-Fidelity, Parallel, Agent-Based Evacuation Simulator (2019) - 4 Citations

  189. E Kosiachenko, Efficient GPU Parallelization of the Agent-Based Models Using MASS CUDA Library (2018) - 3 Citations

  190. C Montañola-Sales and X Rubio-Campillo, Large-scale social simulation, dealing with complexity challenges in high performance environments (2014) - 3 Citations

  191. W Marurngsith and Y Mongkolsin, Creating gpu-enabled agent-based simulations using a pdes tool (2013) - 3 Citations

  192. Q Zhang and RR Vatsavai and A Shashidharan, Agent based urban growth modeling framework on Apache Spark (2016) - 3 Citations

  193. E Hermellin and F Michel, Overview of case studies on adapting mabs models to gpu programming (2016) - 3 Citations

  194. B Cosenza, Behavioral spherical harmonics for long-range agents’ interaction (2015) - 3 Citations

  195. MF McGuire, Pathway semantics: An algebraic data driven algorithm to generate hypotheses about molecular patterns underlying disease progression (2011) - 3 Citations

  196. A Ţurcanu and L Mierlă and F Ipate and A Stefanescu, Modelling and Analysis of E. coli Respiratory Chain (2014) - 3 Citations

  197. W Marurngsith, Computing Platforms for Large-Scale Multi-Agent Simulations: The Niche for Heterogeneous Systems (2014) - 3 Citations

  198. C Montañola Sales, Large-scale simulation of population dynamics for socio-demographic analysis (2015) - 3 Citations

  199. A Liberman and D Kario and M Mussel and J Brill, Cell studio: A platform for interactive, 3D graphical simulation of immunological processes (2018) - 3 Citations

  200. G Laville, Exécution efficace de systèmes multi-agents sur GPU (2014) - 3 Citations

  201. 贺毅辉， 叶晨， 刘志忠， 彭伟, 基于 CUDA 的大规模群体行为实时仿真并行实现及优化 (2012) - 3 Citations

  202. E Hermellin and F Michel, Délégation GPU des perceptions agents: Application aux boids de reynolds (2015) - 3 Citations

  203. E Hermellin and F Michel and J Ferber, État de l’art sur les simulations multi-agents et le GPGPU Évolution et perspectives de recherches (2015) - 3 Citations

  204. O Kurdi, Crowd modelling and simulation (2017) - 3 Citations

  205. R McCarthy and LEK Achenie, Agent-based modeling–Proof of concept application to membrane separation and hydrogen storage in a MOF (2017) - 3 Citations

  206. M Kiran, X-machines for Agent-based Modeling: FLAME Perspectives (2017) - 3 Citations

  207. C Wang and C Yu and H Wu and X Chen and Y Li and X Zhang, A platform for stock market simulation with distributed agent-based modeling (2014) - 3 Citations

  208. JAR Marshall and A Reina and T Bose, Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths (2019) - 3 Citations

  209. A Petkova and C Hughes and N Deo, Accelerating the distributed simulations of agent-based models using community detection (2016) - 3 Citations

  210. G Laville, Exécution efficace de systèmes multi-agents sur GPU (2014) - 3 Citations

  211. E Kosiachenko, Efficient GPU Parallelization of the Agent-Based Models Using MASS CUDA Library (2018) - 3 Citations

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  213. E Hermellin and F Michel, Overview of case studies on adapting mabs models to gpu programming (2016) - 3 Citations

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