We have a new collection of GPU accelerated Molecular Dynamics benchmark packages put together for GROMACS, NAMD 2, and NAMD 3-alpha10. (The benchmark packages will be available to the public soon.) In this post we present results for,
– 3 applications: GROMACS, NAND 2 and NAMD 3alpha10,
– 8 MD simulations,
– 12 different NVIDIA GPUs,
– 96 total results.
The GeForce RTX3070 has been released.
The RTX3070 is loaded with 8GB of memory making it less suited for compute task than the 3080 and 3090 GPUs. we have some preliminary results for TensorFlow, NAMD and HPCG.
The second new NVIDIA RTX30 series card, the GeForce RTX3090 has been released.
The RTX3090 is loaded with 24GB of memory making it a good replacement for the RTX Titan… at significantly less cost! The performance for Machine Learning and Molecular Dynamics on the RTX3090 is quite good, as expected.
The much anticipated NVIDIA GeForce RTX3080 has been released. How good is it with TensorFlow for machine learning? How about molecular dynamics with NAMD? I’ve got some preliminary numbers for you!
The new NVIDIA GeForce GTX 1080 and GTX 1070 GPU’s are out and I’ve received a lot of questions about NAMD performance. The short answer is — performance is great! I’ve got some numbers to back that up below. We’ve got new Broadwell Xeon and Core-i7 CPU’s thrown into the mix too. The new hardware refresh gives a nice step up in performance.
Molecular Dynamics programs can achieve very good performance on modern GPU accelerated workstations giving job performance that was only achievable using CPU compute clusters only a few years ago. The group at UIUC working on NAMD were early pioneers of using GPU’s for compute acceleration and NAMD has very good performance acceleration using NVIDIA CUDA. We show you how good that performance is on modern Nvidia GPU’s
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