{"id":5100,"date":"2011-08-15T16:03:41","date_gmt":"2011-08-15T13:03:41","guid":{"rendered":"http:\/\/hgpu.org\/?p=5100"},"modified":"2011-08-18T21:28:27","modified_gmt":"2011-08-18T18:28:27","slug":"fast-parallel-simulation-of-fiber-optical-communication-systems-accelerated-by-a-graphics-processing-unit","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5100","title":{"rendered":"Fast parallel simulation of fiber optical communication systems accelerated by a graphics processing unit"},"content":{"rendered":"<p>A parallel implementation of the split-step Fourier method utilizing the general purpose parallel computing architecture for graphics processing units CUDA is presented. Results of the GPU-implementation are compared to a conventional CPU-based approach regarding computation time and accuracy. We developed a novel implementation with a significantly higher accuracy than the CUDA intrinsic FFT in single precision mode yielding a high speed-up factor of up to 144 compared to a CPU implementation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A parallel implementation of the split-step Fourier method utilizing the general purpose parallel computing architecture for graphics processing units CUDA is presented. Results of the GPU-implementation are compared to a conventional CPU-based approach regarding computation time and accuracy. We developed a novel implementation with a significantly higher accuracy than the CUDA intrinsic FFT in single [&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":[11,89,3],"tags":[1782,14,207,20,373,321],"class_list":["post-5100","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-fft","tag-nvidia","tag-nvidia-geforce-gtx-275","tag-optics"],"views":1907,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5100","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=5100"}],"version-history":[{"count":1,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5100\/revisions"}],"predecessor-version":[{"id":5209,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5100\/revisions\/5209"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5100"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5100"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5100"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}