{"id":1067,"date":"2020-04-11T02:59:50","date_gmt":"2020-04-10T17:59:50","guid":{"rendered":"https:\/\/wp.study3.biz\/?p=1067"},"modified":"2020-04-11T03:01:34","modified_gmt":"2020-04-10T18:01:34","slug":"amd-2990wx-ubuntu-18-04-4-lts-titan-rtx-x2-cuda-10-2-namd-2-12-171025-stmv-virus-benchmark-%e3%82%92%e5%8b%95%e4%bd%9c%e3%81%95%e3%81%9b%e3%81%a6%e3%81%bf%e3%81%9f1066628-atoms-periodic-pme","status":"publish","type":"post","link":"https:\/\/wp.study3.biz\/?p=1067","title":{"rendered":"AMD 2990wx Ubuntu 18.04.4 LTS TITAN RTX x2 CUDA 10.2  namd 2.12-171025  STMV (virus) benchmark \u3092\u52d5\u4f5c\u3055\u305b\u3066\u307f\u305f(1,066,628 atoms, periodic, PME) 0.471472 days\/ns"},"content":{"rendered":"<p>chibi@1804:~$ sudo nvidia-docker run -it &#8211;rm nvcr.io\/hpc\/namd:2.12-171025 \/opt\/namd\/namd-multicore-memopt +p40 +setcpuaffinity +idlepoll \/workspace\/examples\/stmv\/stmv_pmecuda.namd<br \/>\nUnable to find image &#8216;nvcr.io\/hpc\/namd:2.12-171025&#8217; locally<br \/>\n2.12-171025: Pulling from hpc\/namd<br \/>\nf6fa9a861b90: Pull complete<br \/>\n2d93875543ec: Pull complete<br \/>\n407421ef3e7e: Pull complete<br \/>\nea9ffec33008: Pull complete<br \/>\nc695ce24f66e: Pull complete<br \/>\ncb6e6f26f62f: Pull complete<br \/>\n4ca5cacd5888: Pull complete<br \/>\n127359e380ae: Pull complete<br \/>\n09f52fb90f32: Pull complete<br \/>\nc8b4fccff7c3: Pull complete<br \/>\na898f5b12168: Pull complete<br \/>\n0c9fa151e12b: Pull complete<br \/>\ne9f9e8f970e4: Pull complete<br \/>\n6cb19c6e7375: Pull complete<br \/>\n76db9e80d16b: Pull complete<br \/>\nDigest: sha256:c9184f9b071f2197f20a0064ed47f9dc8deac9f007e03d384ecbaad28a754124<br \/>\nStatus: Downloaded newer image for nvcr.io\/hpc\/namd:2.12-171025<br \/>\nCharm++: standalone mode (not using charmrun)<br \/>\nCharm++&gt; Running in Multicore mode: 40 threads<br \/>\nCharm++&gt; Using recursive bisection (scheme 3) for topology aware partitions<br \/>\nConverse\/Charm++ Commit ID: v6.8.2<br \/>\nWarning&gt; Randomization of virtual memory (ASLR) is turned on in the kernel, thread migration may not work! Run &#8216;echo 0 &gt; \/proc\/sys\/kernel\/randomize_va_space&#8217; as root to disable it, or try running with &#8216;+isomalloc_sync&#8217;.<br \/>\nCharmLB&gt; Load balancer assumes all CPUs are same.<br \/>\nCharm++&gt; cpu affinity enabled.<br \/>\nCharm++&gt; Running on 1 unique compute nodes (64-way SMP).<br \/>\nCharm++&gt; cpu topology info is gathered in 0.033 seconds.<br \/>\nInfo: Built with CUDA version 9000<br \/>\nDid not find +devices i,j,k,&#8230; argument, using all<br \/>\nPe 22 physical rank 22 will use CUDA device of pe 32<br \/>\nPe 23 physical rank 23 will use CUDA device of pe 32<br \/>\nPe 7 physical rank 7 will use CUDA device of pe 16<br \/>\nPe 36 physical rank 36 will use CUDA device of pe 32<br \/>\nPe 13 physical rank 13 will use CUDA device of pe 16<br \/>\nPe 39 physical rank 39 will use CUDA device of pe 32<br \/>\nPe 14 physical rank 14 will use CUDA device of pe 16<br \/>\nPe 27 physical rank 27 will use CUDA device of pe 32<br \/>\nPe 4 physical rank 4 will use CUDA device of pe 16<br \/>\nPe 30 physical rank 30 will use CUDA device of pe 32<br \/>\nPe 1 physical rank 1 will use CUDA device of pe 16<br \/>\nPe 33 physical rank 33 will use CUDA device of pe 32<br \/>\nPe 37 physical rank 37 will use CUDA device of pe 32<br \/>\nPe 5 physical rank 5 will use CUDA device of pe 16<br \/>\nPe 34 physical rank 34 will use CUDA device of pe 32<br \/>\nPe 2 physical rank 2 will use CUDA device of pe 16<br \/>\nPe 38 physical rank 38 will use CUDA device of pe 32<br \/>\nPe 3 physical rank 3 will use CUDA device of pe 16<br \/>\nPe 9 physical rank 9 will use CUDA device of pe 16<br \/>\nPe 15 physical rank 15 will use CUDA device of pe 16<br \/>\nPe 11 physical rank 11 will use CUDA device of pe 16<br \/>\nPe 35 physical rank 35 will use CUDA device of pe 32<br \/>\nPe 12 physical rank 12 will use CUDA device of pe 16<br \/>\nPe 6 physical rank 6 will use CUDA device of pe 16<br \/>\nPe 25 physical rank 25 will use CUDA device of pe 32<br \/>\nPe 29 physical rank 29 will use CUDA device of pe 32<br \/>\nPe 24 physical rank 24 will use CUDA device of pe 32<br \/>\nPe 10 physical rank 10 will use CUDA device of pe 16<br \/>\nPe 21 physical rank 21 will use CUDA device of pe 32<br \/>\nPe 28 physical rank 28 will use CUDA device of pe 32<br \/>\nPe 8 physical rank 8 will use CUDA device of pe 16<br \/>\nPe 0 physical rank 0 will use CUDA device of pe 16<br \/>\nPe 26 physical rank 26 will use CUDA device of pe 32<br \/>\nPe 31 physical rank 31 will use CUDA device of pe 32<br \/>\nPe 20 physical rank 20 will use CUDA device of pe 32<br \/>\nPe 17 physical rank 17 will use CUDA device of pe 16<br \/>\nPe 19 physical rank 19 will use CUDA device of pe 16<br \/>\nPe 18 physical rank 18 will use CUDA device of pe 16<br \/>\nPe 32 physical rank 32 binding to CUDA device 1 on 344ba69a45c4: &#8216;TITAN RTX&#8217; Mem: 24219MB Rev: 7.5<br \/>\nPe 16 physical rank 16 binding to CUDA device 0 on 344ba69a45c4: &#8216;TITAN RTX&#8217; Mem: 24220MB Rev: 7.5<\/p>\n<p>Info: Benchmark time: 40 CPUs 0.0407352 s\/step <strong>0.471472<\/strong> days\/ns<\/p>\n<p>\u30c7\u30fc\u30bf\u8a73\u7d30 <a href=\"https:\/\/wp.study3.biz\/wp-content\/uploads\/2020\/03\/AMD-2990wx-Ubuntu-18.04.4-LTS-TITAN-RTX-x2-CUDA-10.2-namd-2.12-171025-STMV-virus-benchmark-1066628-atoms-periodic-PME-0.471472-days-ns.txt\">AMD 2990wx Ubuntu 18.04.4 LTS TITAN RTX x2 CUDA 10.2 namd 2.12-171025 STMV (virus) benchmark (1,066,628 atoms, periodic, PME) 0.471472 days ns<\/a><\/p>\n<p>GPU\u6e29\u5ea6\u63a8\u79fb <a href=\"https:\/\/wp.study3.biz\/wp-content\/uploads\/2020\/03\/AMD-2990wx-Ubuntu-18.04.4-LTS-TITAN-RTX-x2-CUDA-10.2-namd-2.12-171025-STMV-virus-benchmark-1066628-atoms-periodic-PME-0.471472-days-ns-nvidia-smi.txt\">AMD 2990wx Ubuntu 18.04.4 LTS TITAN RTX x2 CUDA 10.2 namd 2.12-171025 STMV (virus) benchmark (1,066,628 atoms, periodic, PME) 0.471472 days ns nvidia-smi<\/a><\/p>\n<p>\u53c2\u8003<a href=\"https:\/\/www.hpc-technologies.co.jp\/namd-benchmark\">\u30b5\u30a4\u30c8<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>chibi@1804:~$ sudo nvidia-docker run -it &#8211;rm nvcr.io\/hpc\/namd:2.12-171025 \/opt\/namd\/namd-multicore-memop &hellip; <a href=\"https:\/\/wp.study3.biz\/?p=1067\">\u7d9a\u304d\u3092\u8aad\u3080 <span class=\"meta-nav\">&rarr;<\/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-1067","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\/1067","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=1067"}],"version-history":[{"count":4,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/posts\/1067\/revisions"}],"predecessor-version":[{"id":1075,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=\/wp\/v2\/posts\/1067\/revisions\/1075"}],"wp:attachment":[{"href":"https:\/\/wp.study3.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1067"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1067"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wp.study3.biz\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1067"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}