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
Intel Skylake Core-i7 CPU — 256 GFLOP/s Linpack result with Intel Parallel Studio XE 2016 and MKL 11.3 vs 200 GFLOP/s using Intel Parallel Studio XE 2015 and MKL 11.2!
I have been butting heads with a particularly annoying bug that I hit frequently on installs since I work with systems that need to have kernel modules recompiled for CUDA and the Xeon Phi. I have it mostly figured out and have a fix in this post.
NVIDIA and PGI are offering “PGI Accelerator with OpenACC” free to academia (or 90 day trial for commercial users) under the banner “NVIDIA OpenACC Toolkit”. It’s about time!
Another amazing deal on Xeon Phi from Intel! This time you can get a 90% discount on a Phi 5110p and get the Intel Parallel Studio Cluster edition with a 1 year license for free.
Fedora 22 is full of new goodness like kernel 4.0 and gcc 5.1 and yes, you can install and run CUDA on it! It’s not officially supported but I did manage to get it working!
If you have done a fresh install of CentOS 6.6 or “updated” to it from a 6.5 install and you are setting up NVIDIA CUDA 6.5 you may be having trouble with a failed build of the nvidia-uvm kernel module. Read on for a fix …
POV-ray is an open source ray tracing package with a long history. It has been a favorite system performance testing package since it’s inception because of the heavy load it places on the CPU. It has had an SMP parallel implementation since the mid 2000’s and is often used as a multi-core CPU parallel performance benchmark on both Linux and Windows.
So lets try it on our Quad socket many-core systems!
I’m going to walk you through a basic install and configuration for a development system to do CUDA and OpenACC GPU programming. This is not a detailed howto but if you have some linux admin skills it will be a reasonable guide to get you started. We’ll do a basic NVIDIA GPU programming setup including CentOS 6.5, CUDA development environment and a PGI compiler setup with OpenACC. The most interesting part may be the OpenACC setup. OpenACC is a relatively new option for GPU programming and allows for a directive (pragma) based coding model.
We take a look at Quad Xeon and Quad Opteron performance and parallel scaling with Zemax OpticStudio including an analysis using Amdahl’s Law. Based on this analysis we then make performance predictions for other processors.
Puget Systems builds custom workstations, servers and storage solutions tailored for your work.
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