The current JupyterHub version 2.5.1 does not allow user installed extension for JupyterLab when it is being served from JupyterHub. This should be remedied in version 3. However, even when this is “fixed” it is still useful to be able to install extensions globally for all users on a multi-user system. This note will show you how.
WSL on Windows 10 does not (currently) provide a direct way to copy a Linux distribution that was installed from the “Microsoft Store”. The following guide will show you a way to make a working copy of an installed distribution with a new name.
In this note I’ll go through creating self-signed SSL certificates and adding them to a JupyterHub configuration running on a LAN or VPN. This will allow encrypted access to the server using https in a browser.
This is a quick note about setting up a JupyterHub server and JupyterLab using conda with Anaconda Python.
On March 19, 2020 I did a webinar titled,
“AMD Threadripper 3rd Gen HPC Parallel Performance and Scaling ++(Xeon 3265W and EPYC 7742)”
The “++(Xeon 3265W and EPYC 7742)” part of that title was added after we had scheduled the webinar. It made the presentation a lot more interesting than the original Threadripper only title! This is a follow up post with the charts and plots of testing results presented in that webinar.
Is 32-cores enough? I had some testing time again on an AMD Threadripper 32-core 3970x and thought it would be interesting to compare that to the 64-core 3990x. In this post I take a comparative look at parallel performance and scaling for HPL Linpack, Python numpy and the NAMD molecular dynamics program.
64 cores is a lot of cores! How well will parallel applications scale on that many cores? The answer, of course, is, it depends on the application. In this post I look at Amdhal’s Law parallel scaling for HPL Linpack, Python numpy and the NAMD molecular dynamics program.
This note describes installing and configuring JupyterHub and JupyterLab on a “bare-metal” server.
64 cores! The latest AMD Threadripper is out, the 3990x 64-core. I’ve spent the last couple of days running benchmarks and have some results showing raw numerical compute performance using my standard CPU testing applications HPL Linpack and the molecular dynamics program NAMD. The 3990x is a great processor with exceptional performance. Especially for NAMD! (There were some difficulties and disappointments during the testing and I report those here too.)
This note describes creating an ISO image for a fully automatic, customized Ubuntu 18.04 server install.