{"id":7217,"date":"2012-02-23T17:38:21","date_gmt":"2012-02-23T15:38:21","guid":{"rendered":"http:\/\/hgpu.org\/?p=7217"},"modified":"2012-02-23T17:38:21","modified_gmt":"2012-02-23T15:38:21","slug":"network-simulator-tools-and-gpu-parallel-systems","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7217","title":{"rendered":"Network Simulator Tools and GPU Parallel Systems"},"content":{"rendered":"<p>In this paper we discuss the possibilities for parallel implementations of network simulators. Specifically we investigate the options for porting parts of the simulator on GPU in order to utilize its resources and obtain faster simulations. We discuss few issues which are unsuitable for the GPU architecture, and we propose a possible work around for each of them. We introduce a design of parallel module that interconnects with a network simulator, while maintaining  transparency in aspect of the simulation modeler.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we discuss the possibilities for parallel implementations of network simulators. Specifically we investigate the options for porting parts of the simulator on GPU in order to utilize its resources and obtain faster simulations. We discuss few issues which are unsuitable for the GPU architecture, and we propose a possible work around for [&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":[11,89,90,3],"tags":[1782,14,948,20,1793,1006],"class_list":["post-7217","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-opencl","category-paper","tag-computer-science","tag-cuda","tag-networks","tag-nvidia","tag-opencl","tag-tesla-c2070"],"views":2466,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7217","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=7217"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7217\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7217"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7217"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7217"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}