We present a 0.5 Petaflop\/s calculation of homogeneous isotropic turbulence in a cube of 2048^3 particles, using a highly parallel fast multipole method (FMM) using 2048 GPUs on the TSUBAME 2.0 system. We compare this particle-based code with a spectral DNS code under the same calculation condition and the same machine. The results of our particle-based turbulence simulation match quantitatively with that of the spectral method. The calculation time for one time step is approximately 30 seconds for both methods; this result shows that the scalability of the FMM starts to become an advantage over FFT-based methods beyond 2000 GPUs.<\/p>\n","protected":false},"excerpt":{"rendered":"
We present a 0.5 Petaflop\/s calculation of homogeneous isotropic turbulence in a cube of 2048^3 particles, using a highly parallel fast multipole method (FMM) using 2048 GPUs on the TSUBAME 2.0 system. We compare this particle-based code with a spectral DNS code under the same calculation condition and the same machine. The results of our […]<\/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":[89,104,3],"tags":[98,14,723,1795,628,20,931],"class_list":["post-4485","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-fluid-dynamics","category-paper","tag-computational-physics","tag-cuda","tag-fast-multipole-method","tag-fluid-dynamics","tag-numerical-analysis","tag-nvidia","tag-tesla-m2050"],"views":2094,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4485","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=4485"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4485\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4485"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4485"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4485"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}