/data/
Amber22 benchmarks

April 2023

The benchmark runs below used the Amber 20 Benchmark suite, downloadable from here.

Older benchmarks: [Amber 20] [Amber 18] Amber 16] [Amber 14]

Based on these benchmarks, there is a significant performance advantage to running Amber on the GPU nodes rather than on a CPU-only node.

CPU-only Benchmarks

Amber 22 with all patches as of July 2022, built with gcc 9.2.0, OpenMPI 4.1.3 (Biowulf module 'amber/22.gcc'), running under Rocky8
Hardware: 64 x 2.8 GHz (AMD Epyc 7543)

Explicit Solvent

Implicit Solvent

The benchmark above was run on a AMD Epyc 7543 @2.8GHz with 64 cores (128 hyperthreaded cores). As with other MD applications, the performance drops when more than 64 MPI processes (i.e. 1 process per physical core) are run. Thus, if running on CPUs, it is important to use the '--ntasks-per-core=1' flag when submitting the job, to ensure that only 1 MPI process is run on each physical core. If it is possible to run on a GPU node, you will get significantly better performance as shown in the benchmarks below.

GPU benchmarks

Amber 22 with all patches as of July 2022, built with gcc 9.2.0, CUDA 11.3, and OpenMPI 4.1.3 (Biowulf module 'amber/22-gpu'), running under Rocky8
Hardware:

Explicit Solvent (PME)

Implicit Solvent (GB)