{"id":3858,"date":"2011-05-10T06:30:21","date_gmt":"2011-05-10T06:30:21","guid":{"rendered":"http:\/\/hgpu.org\/?p=3858"},"modified":"2011-05-10T06:30:21","modified_gmt":"2011-05-10T06:30:21","slug":"efficient-parallelization-of-the-stochastic-simulation-algorithm-for-chemically-reacting-systems-on-the-graphics-processing-unit","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=3858","title":{"rendered":"Efficient Parallelization of the Stochastic Simulation Algorithm for Chemically Reacting Systems On the Graphics Processing Unit"},"content":{"rendered":"<p>The small number of some reactant molecules in biological systems formed by living cells can result in dynamical behavior which cannot be captured by traditional deterministic models. In such a problem, a more accurate simulation can be obtained with discrete stochastic simulation (Gillespie&#8217;s stochastic simulation algorithm &#8211; SSA). Many stochastic realizations are required to capture accurate statistical information of the solution. This carries a very high computational cost. The current generation of graphics processing units (GPU) is well-suited to this task. In this paper we describe our implementation and present some computational experiments illustrating the power of this technology for this important and challenging class of problems.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The small number of some reactant molecules in biological systems formed by living cells can result in dynamical behavior which cannot be captured by traditional deterministic models. In such a problem, a more accurate simulation can be obtained with discrete stochastic simulation (Gillespie&#8217;s stochastic simulation algorithm &#8211; SSA). Many stochastic realizations are required to capture [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[10,66,89,3],"tags":[1781,1790,14,20,183,861],"class_list":["post-3858","post","type-post","status-publish","format-standard","hentry","category-biology","category-chemistry","category-nvidia-cuda","category-paper","tag-biology","tag-chemistry","tag-cuda","tag-nvidia","tag-nvidia-geforce-8800-gtx","tag-stochastic-simulation"],"views":2052,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3858","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3858"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3858\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3858"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3858"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3858"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}