chibi@1604:~$ cat /etc/os-release
NAME=”Ubuntu”
VERSION=”16.04.6 LTS (Xenial Xerus)”
ID=ubuntu
ID_LIKE=debian
PRETTY_NAME=”Ubuntu 16.04.6 LTS”
VERSION_ID=”16.04″
HOME_URL=”http://www.ubuntu.com/”
SUPPORT_URL=”http://help.ubuntu.com/”
BUG_REPORT_URL=”http://bugs.launchpad.net/ubuntu/”
VERSION_CODENAME=xenial
UBUNTU_CODENAME=xenial
chibi@1604:~$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89
chibi@1604:~$ sudo hddtemp /dev/sda
/dev/sda: WDC WD5000LPVX-22V0TT0: 24°C
chibi@1604:~$ nvidia-smi nvlink -c
GPU 0: GeForce RTX 2080 Ti (UUID: GPU-1ac935c2-557f-282e-14e5-3f749ffd63ac)
GPU 1: GeForce RTX 2080 Ti (UUID: GPU-13277ce5-e1e9-0cb1-8cee-6c9e6618e774)
chibi@1604:~$ sudo nvidia-docker run -it –rm nvcr.io/hpc/namd:2.12-171025 /opt/namd/namd-multicore-memopt +p40 +setcpuaffinity +idlepoll /workspace/examples/stmv/stmv_pmecuda.namd
[sudo] chibi のパスワード:
Charm++: standalone mode (not using charmrun)
Charm++> Running in Multicore mode: 40 threads
Charm++> Using recursive bisection (scheme 3) for topology aware partitions
Converse/Charm++ Commit ID: v6.8.2
Warning> Randomization of virtual memory (ASLR) is turned on in the kernel, thread migration may not work! Run ‘echo 0 > /proc/sys/kernel/randomize_va_space’ as root to disable it, or try running with ‘+isomalloc_sync’.
CharmLB> Load balancer assumes all CPUs are same.
Charm++> cpu affinity enabled.
Charm++> Running on 1 unique compute nodes (48-way SMP).
Charm++> cpu topology info is gathered in 0.003 seconds.
Info: Built with CUDA version 9000
Did not find +devices i,j,k,… argument, using all
Pe 39 physical rank 39 will use CUDA device of pe 32
Pe 36 physical rank 36 will use CUDA device of pe 32
Pe 15 physical rank 15 will use CUDA device of pe 16
Pe 19 physical rank 19 will use CUDA device of pe 16
Pe 10 physical rank 10 will use CUDA device of pe 16
Pe 34 physical rank 34 will use CUDA device of pe 32
Pe 9 physical rank 9 will use CUDA device of pe 16
Pe 33 physical rank 33 will use CUDA device of pe 32
Pe 12 physical rank 12 will use CUDA device of pe 16
Pe 22 physical rank 22 will use CUDA device of pe 32
Pe 17 physical rank 17 will use CUDA device of pe 16
Pe 14 physical rank 14 will use CUDA device of pe 16
Pe 27 physical rank 27 will use CUDA device of pe 32
Pe 3 physical rank 3 will use CUDA device of pe 16
Pe 38 physical rank 38 will use CUDA device of pe 32
Pe 31 physical rank 31 will use CUDA device of pe 32
Pe 7 physical rank 7 will use CUDA device of pe 16
Pe 23 physical rank 23 will use CUDA device of pe 32
Pe 8 physical rank 8 will use CUDA device of pe 16
Pe 6 physical rank 6 will use CUDA device of pe 16
Pe 4 physical rank 4 will use CUDA device of pe 16
Pe 30 physical rank 30 will use CUDA device of pe 32
Pe 28 physical rank 28 will use CUDA device of pe 32
Pe 21 physical rank 21 will use CUDA device of pe 32
Pe 20 physical rank 20 will use CUDA device of pe 32
Pe 11 physical rank 11 will use CUDA device of pe 16
Pe 35 physical rank 35 will use CUDA device of pe 32
Pe 29 physical rank 29 will use CUDA device of pe 32
Pe 5 physical rank 5 will use CUDA device of pe 16
Pe 2 physical rank 2 will use CUDA device of pe 16
Pe 26 physical rank 26 will use CUDA device of pe 32
Pe 1 physical rank 1 will use CUDA device of pe 16
Pe 25 physical rank 25 will use CUDA device of pe 32
Pe 18 physical rank 18 will use CUDA device of pe 16
Pe 24 physical rank 24 will use CUDA device of pe 32
Pe 37 physical rank 37 will use CUDA device of pe 32
Pe 13 physical rank 13 will use CUDA device of pe 16
Pe 0 physical rank 0 will use CUDA device of pe 16
Pe 16 physical rank 16 binding to CUDA device 0 on 7d2a3b9162ec: ‘GeForce RTX 2080 Ti’ Mem: 11018MB Rev: 7.5
Pe 32 physical rank 32 binding to CUDA device 1 on 7d2a3b9162ec: ‘GeForce RTX 2080 Ti’ Mem: 11019MB Rev: 7.5
Info: NAMD 2.12 for Linux-x86_64-multicore-CUDA-memopt
Info: Benchmark time: 40 CPUs 0.0304685 s/step 0.352644 days/ns 2391.72 MB memory
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