{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:23:21Z","timestamp":1760243001175,"version":"build-2065373602"},"reference-count":20,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2015,2,27]],"date-time":"2015-02-27T00:00:00Z","timestamp":1424995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>General Purpose (use of) Graphics Processing Units (GPGPU) is a promising technology for simulation upscaling; in particular for bottom\u2013up modelling approaches seeking to translate micro-scale system processes to macro-scale properties. Many existing simulations of soil ecosystems do not recover the emergent system scale properties and this may be a consequence of \u201cmissing\u201d information at finer scales. Interpretation of model output can be challenging and we advocate the \u201cbuilt-in\u201d visual simulation afforded by GPGPU implementations. We apply this GPGPU approach to a reaction\u2013diffusion soil ecosystem model with the intent of linking micro (micron) and core (cm) spatial scales to investigate how microbes respond to changing environments and the consequences on soil respiration. The performance is evaluated in terms of computational speed up, spatial upscaling and visual feedback. We conclude that a GPGPU approach can significantly improve computational efficiency and offers the potential added benefit of visual immediacy. For massive spatial domains distribution over GPU devices may still be required.<\/jats:p>","DOI":"10.3390\/computation3010058","type":"journal-article","created":{"date-parts":[[2015,2,27]],"date-time":"2015-02-27T10:08:39Z","timestamp":1425031719000},"page":"58-71","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Visual Simulation of Soil-Microbial System Using  GPGPU Technology"],"prefix":"10.3390","volume":"3","author":[{"given":"Ruth","family":"Falconer","sequence":"first","affiliation":[{"name":"SIMBIOS. School of Science, Engineering and Technology, Abertay University,  Dundee DD1 1HG, UK"}]},{"given":"Alasdair","family":"Houston","sequence":"additional","affiliation":[{"name":"SIMBIOS. School of Science, Engineering and Technology, Abertay University,  Dundee DD1 1HG, UK"}]}],"member":"1968","published-online":{"date-parts":[[2015,2,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1615","DOI":"10.1126\/science.1231923","article-title":"Roots and associated fungi drive long-term carbon sequestration in boreal forest","volume":"339","author":"Clemmensen","year":"2013","journal-title":"Science"},{"key":"ref_2","first-page":"1727","article-title":"Biomass recycling and the origin of phenotype in fungal mycelia","volume":"272","author":"Falconer","year":"2005","journal-title":"Proc. Biol. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.ecolmodel.2012.08.008","article-title":"Soil fungal dynamics: Parameterisation and sensitivity analysis of modelled physiological processes, soil architecture and carbon distribution","volume":"248","author":"Cazelles","year":"2013","journal-title":"Ecol. Modell."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1097\/SS.0b013e318241133a","article-title":"Emergent Behavior of Soil Fungal Dynamics: Influence of Soi","volume":"177","author":"Falconer","year":"2012","journal-title":"J. Soil Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1558","DOI":"10.1111\/j.0030-1299.2007.15885.x","article-title":"Biomass recycling: A key to efficient foraging by fungal colonies","volume":"116","author":"Falconer","year":"2007","journal-title":"Oikos"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1016\/j.soilbio.2009.02.031","article-title":"Soil carbon and nitrogen mineralization: Theory and models across scales","volume":"41","author":"Manzoni","year":"2009","journal-title":"Soil Biol. Biochem."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1111\/j.1365-2486.2012.02665.x","article-title":"Soil organic matter turnover is governed by accessibility not recalcitrance","volume":"18","author":"Dungait","year":"2012","journal-title":"Glob. Chang. Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.soilbio.2012.04.008","article-title":"Combining X-Ray CT and 3D printing technology to produce microcosms with replicable, complex pore geometries","volume":"51","author":"Otten","year":"2012","journal-title":"Soil Biol. Biochem."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1302","DOI":"10.1098\/rsif.2011.0679","article-title":"Microbial diversity affects self-organization of the soil-microbe system with consequences for function","volume":"9","author":"Crawford","year":"2012","journal-title":"J. R. Soc. Interface"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e83661","DOI":"10.1371\/journal.pone.0083661","article-title":"Impact of matric potential and pore size distribution on growth dynamics of filamentous and non-filamentous soil bacteria","volume":"8","author":"Wolf","year":"2013","journal-title":"PLoS One"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e87217","DOI":"10.1371\/journal.pone.0087217","article-title":"Spatial ecology of bacteria at the microscale in soil","volume":"9","author":"Raynaud","year":"2014","journal-title":"PLoS One"},{"key":"ref_12","first-page":"3477","article-title":"Modelling and quantifying the effect of heterogeneity in soil physical conditions on fungal growth","volume":"7","author":"Pajor","year":"2010","journal-title":"Biogeosci. Discuss."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1890\/10-0525.1","article-title":"Fungal colonization in soils with different management histories: Modeling growth in three-dimensional pore volumes","volume":"21","author":"Kravchenko","year":"2011","journal-title":"Ecol. Appl."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"155","DOI":"10.5598\/imafungus.2010.01.02.07","article-title":"Modelling fungal colonies and communities: Challenges and opportunities","volume":"1","author":"Falconer","year":"2010","journal-title":"IMA Fungus"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.chemolab.2011.03.009","article-title":"Simulation of reaction\u2013diffusion processes in three dimensions using CUDA","volume":"108","author":"Lagzi","year":"2011","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1093\/bib\/bbp073","article-title":"High performance cellular level agent-based simulation with FLAME for the GPU","volume":"11","author":"Richmond","year":"2010","journal-title":"Brief. Bioinform."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s00791-008-0086-0","article-title":"A framework for exploring numerical solutions of advection\u2013reaction\u2013diffusion equations using a GPU-based approach","volume":"12","author":"Sanderson","year":"2008","journal-title":"Comput. Vis. Sci."},{"key":"ref_18","unstructured":"Fung, J. DirectCompute Lecture Series 210: GPU Optimizations and Performance. Available online: http:\/\/channel9.msdn.com\/Blogs\/gclassy\/DirectCompute-Lecture-Series-210-GPU-Optimizations-and-Performance."},{"key":"ref_19","unstructured":"Fernando, M., and Pharr, R. (2005). GPU Gems 2: Programming Techniques for High-Performance Graphics and General-Purpose Computation, Addison Wesley. [1st ed.]."},{"key":"ref_20","unstructured":"Whitehead, N., and Fit-Florea, A. (2011). Precision & Performance: Floating Point and IEEE 754 Compliance for NVIDIA GPUs, NVIDIA. Technical Report, rn (A+ B) 21 (2011) 1-1874919424."}],"container-title":["Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-3197\/3\/1\/58\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:43:00Z","timestamp":1760215380000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-3197\/3\/1\/58"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,2,27]]},"references-count":20,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,3]]}},"alternative-id":["computation3010058"],"URL":"https:\/\/doi.org\/10.3390\/computation3010058","relation":{},"ISSN":["2079-3197"],"issn-type":[{"type":"electronic","value":"2079-3197"}],"subject":[],"published":{"date-parts":[[2015,2,27]]}}}