![]() To provide a point of reference, we also give speedup numbers with respect to a GTX 1080 GPU (bar graphs). Also there is no consistent picture across all benchmark cases, so we will look at the results grouped by benchmark size, from small to large. While it is true that the NVIDIA GTX1080 and GTX1080Ti GPUs are not the current state of the art, their performance is still considerably better than that of CPU nodes from two generations ago. It might be tempting to just have a quick glance at these numbers and jump to the conclusion that the newest hardware will always give the best results unfortunately, it is not quite that easy. Please also note that ECC is disabled on the A40s in Alex. Since Gromacs may require considerable CPU processing power (depending on the case at hand), the GPU is not the only factor that influences the performance of the benchmarks. Depending on the hardware, different Gromacs versions were used: 2021.1 for all GPU types available in TinyGPU, version 2021.3 on A40 in Alex, and version 2021.4 on A100 in Alex. On TinyGPU and Alex, several GPUs are combined with one host CPU, i.e., each GPU has access only to a fraction of the host. This offloads all possible calculations to the GPU and pins the threads to the host CPU the number of OpenMP threads depends on how many CPU cores are available per GPU (i.e., 4 for our GTX1080, GTX1080TI, 8 on RTX2080TI, V100, and RTX3080, and 16 on the A40 and A100 in Alex). ntmpi 1 -ntomp $ntomp -pin on -pinstride 1 -nsteps 200000 -deffnm $benchmark_name ![]() a huge virus protein (1,066,628 atoms).įor running these benchmarks with Gromacs2021 on a GPU, the following command was executed: $ gmx mdrun -v -s $benchmark.tpr -nb gpu -pme gpu -bonded gpu -update gpu \.a protein membrane channel with explicit water (615,924 atoms), and.a protein in explicit water (170,320 atoms),.a protein inside a membrane surrounded by explicit water (80,289 atoms),.a short RNA piece with explicit water (31,889 atoms),.R-143a in hexane (20,248 atoms) with very high output rate,.The benchmark systems are identical to the ones we used for investigating the speedup of NVIDIA GPUs vs Intel Xeon Ice Lake. Alex has a total of 192 Nvidia A100 and 304 Nvidia A40 GPGPUs that will be available nation-wide soon we decided to run some Gromacs benchmarking tests of MD simulations of varying size to compare the new GPU hardware to that already available in TinyGPU. Has recently installed its new GPU cluster “Alex”, which is currently undergoing user-side testing until it is ready for general use.
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