Designed and built specifically for professional workstations, NVIDIA Quadro GPUs power more than 200 professional applications across a broad range of industries including manufacturing, media and entertainment, sciences, and energy. Professionals trust them to realize their most ambitious visions
In this post I present some Multi-GPU scaling tests running TensorFlow on a very nice system with 8 1080Ti GPU’s. I use the Docker Workstation setup that I have recently written about. The job I ran for this testing was the “Billion Words Benchmark” using an LSTM model. Results were very good and better than expected.
This should be the last post in this series dealing with the Docker setup for accessing the NVIDIA NCG Docker registry on your workstation. There are a couple of configuration tuning changes that you may want to make. These will improve performance and ensure that you have proper system “user limit” resources to handle large application and job runs with docker.
In this video, Matt Granger breaks down the real world performance in the Adobe CC of a Puget Systems workstation versus similarly priced 2018 iMac Pro.
Despite how popular SOLIDWORKS is, there is a lot of outdated and simply inaccurate information on the web regarding what video card you should use. For this article I tested multiple graphics cards from the Quadro, GeForce, and Radeon Pro families at both 1080p and 4K resolutions – and quickly found that either things are now a lot simpler than in my past experience, or else something is no longer up to snuff regarding how we have tested SOLIDWORKS GPU performance in the past.
If your workflow depends on having 10-bit color support on your primary display, using a workstation graphics card is typically the only way to do so since most consumer cards do not support displaying 10-bit color. But do you really need a Quadro P6000 or can you use a much less expensive card like the Quadro P4000 or Radeon Pro WX 9100 without sacrificing very much performance?
This post will go through how to get access to the NVIDIA NGC container registry on your workstation. The first 3 posts in this series gave instructions on how to install and configure a base Ubuntu 16.04 workstation system with Docker and NVIDIA-Docker for a usable work-flow. With that taken care of we can get setup to use the many useful docker images in the NGC container registry for your local system.
Choosing a monitor may seem pretty basic, however, there are several things to consider to make sure you get the right monitor for your specific needs. This article describes how to do that.
The NVIDIA Titan V has many the features that are not useful in DaVinci Resolve, but it’s raw power allows it to give the highest single GPU playback performance of any GPU we have every tested.
In this post I’ll go through setting up Docker to use User-Namespaces. This is a very important step to achieving a comfortable docker work-flow on a personal Workstation. I will show you how to configure Docker so that instead of files and processes being owned by root they will be owned by your personal user account. This will make using Docker containers on your system safer and feel much the same as a “normally” installed application.
Puget Systems builds custom workstations, servers and storage solutions tailored for your work.
We provide:
Extensive performance testing
making you more productive and giving better value for your money
Reliable computers
with fewer crashes means more time working & less time waiting
Support that understands
your complex workflows and can get you back up & running ASAP
A proven track record
as shown by our case studies and customer testimonials
