Re: No performance improvement with NAMD 3.0 alpha8 over namd 2.14 cuda

From: SHIVAM TIWARI (t.shivam_at_iitg.ac.in)
Date: Fri Sep 09 2022 - 10:44:58 CDT

Hi Josh,

Thanks for your reply, yes, I am using "CUDASOAintegrate on" in my configuration file.

regards
Shivam

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________________________________
From: Vermaas, Josh <vermaasj_at_msu.edu>
Sent: Friday, September 9, 2022 8:21:34 PM
To: namd-l_at_ks.uiuc.edu <namd-l_at_ks.uiuc.edu>; SHIVAM TIWARI <t.shivam_at_iitg.ac.in>
Subject: Re: namd-l: No performance improvement with NAMD 3.0 alpha8 over namd 2.14 cuda

Are you using the CUDASOAIntegrate codepath? Otherwise, NAMD 3 will fall back to the NAMD 2 code path, which is why the performance is identical. See the NVIDIA blogpost about what you need to change in your configuration files. https://urldefense.com/v3/__https://developer.nvidia.com/blog/delivering-up-to-9x-throughput-with-namd-v3-and-a100-gpu/__;!!DZ3fjg!6bejqz4cpnYiAqX0WhDH1tjFAb2_NFe85s2s02Ldw7_mgUjsMdKJmz7QnQv_eH7aPcyIXoJvlB4iSTERv4zlOA$

-Josh

From: <owner-namd-l_at_ks.uiuc.edu> on behalf of SHIVAM TIWARI <t.shivam_at_iitg.ac.in>
Reply-To: "namd-l_at_ks.uiuc.edu" <namd-l_at_ks.uiuc.edu>, SHIVAM TIWARI <t.shivam_at_iitg.ac.in>
Date: Friday, September 9, 2022 at 4:39 AM
To: namd-l <namd-l_at_ks.uiuc.edu>
Subject: namd-l: No performance improvement with NAMD 3.0 alpha8 over namd 2.14 cuda

Dear all,

I am comparing the performances of namd 3.0 (alpha 8) and namd 2.14 on a system of 257k atoms with nvidia tesla k40 as my GPU. However, I don't see any performance improvement with namd 3.0 and both codes(3 & 2.14) are giving a benchmark of around 4 ns/day. How to get the best performance out of the available computational resources? Following is the SLURM script I am using for NAMD 3.0.

#!/bin/sh

#BATCH -A

#SBATCH --nodes 1

#SBATCH --ntasks-per-node=4

#SBATCH --account=project

#SBATCH --gres=gpu:1

#SBATCH --qos=project

#SBATCH --partition=high

#SBATCH --mem=10gb

#SBATCH --error=job.%J.err

#SBATCH --output=job.%J.out

#SBATCH --time=10-00:00:00

#SBATCH --no-requeue

module purge

#PATH=$PATH:/apps/precompiled/namd/NAMD_2.14_Linux-x86_64-multicore-CUDA

PATH=$PATH:/scratch/proj/nsmswamireddy/NAMD_3.0alpha8_Linux-x86_64-multicore-CUDA

##charmexec=../NAMD_3.0alpha12_Linux-x86_64-multicore-CUDA/charmrun

##namdexec=../NAMD_3.0alpha12_Linux-x86_64-multicore-CUDA/namd3

charmrun namd3 +p $SLURM_NTASKS +setcpuaffinity +idlepoll prod.conf > pasr21.log

regards

shivam

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