{"id":965,"date":"2020-04-05T00:31:25","date_gmt":"2020-04-04T15:31:25","guid":{"rendered":"https:\/\/wp.study3.biz\/?p=965"},"modified":"2020-04-05T00:32:28","modified_gmt":"2020-04-04T15:32:28","slug":"ubuntu16-04-6-titan-v-x2-cuda-10-2-samples-nbodybenchmark-%e3%82%92%e5%8b%95%e4%bd%9c%e3%81%95%e3%81%9b%e3%81%a6%e3%81%bf%e3%81%9ftitan-v-x2-%e5%8d%98%e7%b2%be%e5%ba%a612572-154-gflop-s-titan-v-x2","status":"publish","type":"post","link":"https:\/\/wp.study3.biz\/?p=965","title":{"rendered":"Ubuntu16.04.6 TITAN V x2 CUDA 10.2 Samples nbodybenchmark \u3092\u52d5\u4f5c\u3055\u305b\u3066\u307f\u305fTITaN V x2 \u5358\u7cbe\u5ea6=12572.154 GFLOP\/s TITAN V x2 \u500d\u7cbe\u5ea6=5477.201 GFLOP\/s"},"content":{"rendered":"

chibi@1604:~\/NVIDIA_CUDA-10.2_Samples\/5_Simulations\/nbody$ cat \/etc\/os-release
\nNAME=”Ubuntu”
\nVERSION=”16.04.6 LTS (Xenial Xerus)”
\nID=ubuntu
\nID_LIKE=debian
\nPRETTY_NAME=”Ubuntu 16.04.6 LTS”
\nVERSION_ID=”16.04″
\nHOME_URL=”http:\/\/www.ubuntu.com\/”
\nSUPPORT_URL=”http:\/\/help.ubuntu.com\/”
\nBUG_REPORT_URL=”http:\/\/bugs.launchpad.net\/ubuntu\/”
\nVERSION_CODENAME=xenial
\nUBUNTU_CODENAME=xenial
\nchibi@1604:~\/NVIDIA_CUDA-10.2_Samples\/5_Simulations\/nbody$ nvcc -V
\nnvcc: NVIDIA (R) Cuda compiler driver
\nCopyright (c) 2005-2019 NVIDIA Corporation
\nBuilt on Wed_Oct_23_19:24:38_PDT_2019
\nCuda compilation tools, release 10.2, V10.2.89
\nchibi@1604:~\/NVIDIA_CUDA-10.2_Samples\/5_Simulations\/nbody$ .\/nbody –benchmark –
\n-numbodies=256000 -numdevices=2
\nRun “nbody -benchmark [-numbodies=<numBodies>]” to measure performance.
\n-fullscreen (run n-body simulation in fullscreen mode)
\n-fp64 (use double precision floating point values for simulation)
\n-hostmem (stores simulation data in host memory)
\n-benchmark (run benchmark to measure performance)
\n-numbodies=<N> (number of bodies (>= 1) to run in simulation)
\n-device=<d> (where d=0,1,2…. for the CUDA device to use)
\n-numdevices=<i> (where i=(number of CUDA devices > 0) to use for simulation)
\n-compare (compares simulation results running once on the default GPU and once on the CPU)
\n-cpu (run n-body simulation on the CPU)
\n-tipsy=<file.bin> (load a tipsy model file for simulation)<\/p>\n

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.<\/p>\n

number of CUDA devices = 2
\n> Windowed mode
\n> Simulation data stored in system memory
\n> Single precision floating point simulation
\n> 2 Devices used for simulation
\nGPU Device 0: “Volta” with compute capability 7.0<\/p>\n

> Compute 7.0 CUDA device: [TITAN V]
\n> Compute 7.0 CUDA device: [TITAN V]
\nnumber of bodies = 256000
\n256000 bodies, total time for 10 iterations: 1042.558 ms
\n= 628.608 billion interactions per second
\n= 12572.154 single-precision GFLOP\/s at 20 flops per interaction<\/strong>
\nchibi@1604:~\/NVIDIA_CUDA-10.2_Samples\/5_Simulations\/nbody$ .\/nbody -fp64 –bench
\nmark –numbodies=256000 -numdevices=2
\nRun “nbody -benchmark [-numbodies=<numBodies>]” to measure performance.
\n-fullscreen (run n-body simulation in fullscreen mode)
\n-fp64 (use double precision floating point values for simulation)
\n-hostmem (stores simulation data in host memory)
\n-benchmark (run benchmark to measure performance)
\n-numbodies=<N> (number of bodies (>= 1) to run in simulation)
\n-device=<d> (where d=0,1,2…. for the CUDA device to use)
\n-numdevices=<i> (where i=(number of CUDA devices > 0) to use for simulation)
\n-compare (compares simulation results running once on the default GPU and once on the CPU)
\n-cpu (run n-body simulation on the CPU)
\n-tipsy=<file.bin> (load a tipsy model file for simulation)<\/p>\n

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.<\/p>\n

number of CUDA devices = 2
\n> Windowed mode
\n> Simulation data stored in system memory
\n> Double precision floating point simulation
\n> 2 Devices used for simulation
\nGPU Device 0: “Volta” with compute capability 7.0<\/p>\n

Compute 7.0 CUDA device: [TITAN V]
\n> Compute 7.0 CUDA device: [TITAN V]
\nnumber of bodies = 256000
\n256000 bodies, total time for 10 iterations: 3589.571 ms
\n= 182.573 billion interactions per second
\n= 5477.201 double-precision GFLOP\/s at 30 flops per interaction<\/strong>
\nchibi@1604:~\/NVIDIA_CUDA-10.2_Samples\/5_Simulations\/nbody$<\/p><\/blockquote>\n

\"\"<\/p>\n

GPU\u6e29\u5ea6\u63a8\u79fb Ubuntu16.04.6 TITAN V x2 CUDA 10.2 Samples nbodybenchmark TITaN V x2 \u5358\u7cbe\u5ea6=12572.154 GFLOP s TITAN V x2 \u500d\u7cbe\u5ea6=5477.201 GFLOP s nvidia-smi<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

chibi@1604:~\/NVIDIA_CUDA-10.2_Samples\/5_Simulations\/nbody$ cat \/etc\/os-release NAME=”Ubuntu” VERSI … \u7d9a\u304d\u3092\u8aad\u3080 →<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[18,17],"tags":[],"class_list":["post-965","post","type-post","status-publish","format-standard","hentry","category-nvidia","category-ubuntu"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/posts\/965","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=965"}],"version-history":[{"count":3,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/posts\/965\/revisions"}],"predecessor-version":[{"id":1006,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/posts\/965\/revisions\/1006"}],"wp:attachment":[{"href":"https:\/\/wp.study3.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=965"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=965"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=965"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}