{"id":193,"date":"2025-08-26T09:48:57","date_gmt":"2025-08-26T07:48:57","guid":{"rendered":"https:\/\/www.msnobile.eu\/?page_id=193"},"modified":"2025-08-26T14:56:12","modified_gmt":"2025-08-26T12:56:12","slug":"gpu-powered-simulation","status":"publish","type":"page","link":"https:\/\/www.msnobile.eu\/index.php\/gpu-powered-simulation\/","title":{"rendered":"GPU-powered simulation"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Thanks to libraries like CUDA, modern GPUs offer the possibility of offloading a large amount of calculations to thousands of cores in a SIMD fashion. This is particularly useful when working with simulators and a large number of independent runs of the same model are necessary to investigate its emergent properties. I started developing GPU-powered simulators in 2011 for my Master&#8217;s degree thesis, and I keep doing that nowadays. Here is a partial list of our projects:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/github.com\/aresio\/cupSODA\">cupSODA<\/a>: coarse-grained adaptive deterministic biochemical simulation <\/li>\n\n\n\n<li><a href=\"https:\/\/docs.pysb.org\/en\/stable\/modules\/simulator.html\">pySB\/cupSODA<\/a>: cupSODA was integrated into the pySB rule-based modeling framework <\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/aresio\/cuTauLeaping\">cuTauLeaping<\/a>: coarse-grained adaptive stochastic biochemical simulation<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/aresio\/ginsoda\">ginSODA<\/a>: coarse-grained adaptive deterministic simulation of arbitrary ODE-based models<\/li>\n\n\n\n<li><a href=\"https:\/\/gitlab.com\/andreatangherloni\/ficos\">FiCoS<\/a>: fine- and coarse-grained adaptive deterministic biochemical simulation<\/li>\n\n\n\n<li><a href=\"https:\/\/www.unive.it\/pag\/49569\/\">SDEGnO<\/a>: GPU-accelerated stochastic simulation of cosmic rays propagation within the heliosphere <\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/aresio\/ProCell\">cuProCell<\/a>: GPU-powered stochastic simulation of cell proliferation<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/aresio\/HERESY\">HERESY<\/a>: accelerated simulation of reaction systems<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Thanks to libraries like CUDA, modern GPUs offer the possibility of offloading a large amount of calculations to thousands of cores in a SIMD fashion. This is particularly useful when working with simulators and a large number of independent runs of the same model are necessary to investigate its emergent properties. I started developing GPU-powered&nbsp;&hellip;<\/p>\n","protected":false},"author":1,"featured_media":258,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-193","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages\/193","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/comments?post=193"}],"version-history":[{"count":5,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages\/193\/revisions"}],"predecessor-version":[{"id":260,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages\/193\/revisions\/260"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/media\/258"}],"wp:attachment":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/media?parent=193"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}