{"id":13437,"date":"2015-02-06T22:13:59","date_gmt":"2015-02-06T20:13:59","guid":{"rendered":"http:\/\/hgpu.org\/?p=13437"},"modified":"2015-02-06T22:13:59","modified_gmt":"2015-02-06T20:13:59","slug":"extending-the-gotran-framework-latex-and-gpu-acceleration","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=13437","title":{"rendered":"Extending the Gotran framework: LATEX and GPU acceleration"},"content":{"rendered":"<p>Gotran provides a framework for working with systems of ordinary differential equations (ODEs): Its primary goal is to increase the workflow efficiency of computational modelling in biomedical research. The ODEs, given by the time derivative of state variables, are described in a Gotran form file and can be automatically translated into different outputs depending on the user&#8217;s needs. As of this writing, Gotran supports Python, MATLAB and C\/C++ outputs. In this thesis we present extensions to Gotran and their implementations, including automatic generation of LaTeX output and GPU acceleration on Nvidia graphics cards.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Gotran provides a framework for working with systems of ordinary differential equations (ODEs): Its primary goal is to increase the workflow efficiency of computational modelling in biomedical research. The ODEs, given by the time derivative of state variables, are described in a Gotran form file and can be automatically translated into different outputs depending on [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,3],"tags":[163,1782,14,810,20,1356,1470,923,922,513,390],"class_list":["post-13437","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computational-modelling","tag-computer-science","tag-cuda","tag-differential-equations","tag-nvidia","tag-nvidia-geforce-gt-650-m","tag-nvidia-geforce-gtx-titan","tag-odes","tag-ordinary-differential-equations","tag-python","tag-thesis"],"views":2914,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/13437","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=13437"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/13437\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=13437"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=13437"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=13437"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}