Notes on "Notes" (new blog post format)
Written on December 31, 2019 by Dr Donald KinghornStarting 2020 off with an addition to my writing, "micro blogging" via GitHub Gists
NVIDIA (Computing Hardware) Company of the Decade!
Written on December 13, 2019 by Dr Donald KinghornIt's the end of the 2010's and start of 2020's. Time to reflect ...
SC19 A look at the high end of HPC
Written on December 10, 2019 by Dr Donald KinghornThe Super Computing conference annual US counterpart is always a great meeting. It's a chance to see the trend and get sentiment for the highest performance end of computing. I have written up a few observations and provided a few interesting links for SC19.
How To Use MKL with AMD Ryzen and Threadripper CPU's (Effectively) for Python Numpy (And Other Applications)
Written on November 27, 2019 by Dr Donald KinghornIn this post I'm going to show you a simple way to significantly speedup Python numpy compute performance on AMD CPU's when using Anaconda Python.
AMD Threadripper 3970x Compute Performance Linpack and NAMD
Written on November 25, 2019 by Dr Donald KinghornAMD Threadripper 3970x 32-core! ...The, third new AMD processor I've had the pleasure of trying recently. I'm running it through the same double precision floating point performance tests as the recently tested Ryzen processors, Linpack and NAMD.
AMD Ryzen 3950x Compute Performance Linpack and NAMD
Written on November 14, 2019 by Dr Donald KinghornThe, much anticipated, AMD Ryzen 3950x 16-core processor is out! As always the first thing I wanted know was the double precision floating point performance. My two favorite applications for a "first look" at a new CPU are Linpack and NAMD.
Workstation Setup for Docker with the New NVIDIA Container Toolkit (nvidia-docker2 is deprecated)
Written on September 13, 2019 by Dr Donald KinghornIt's time for a "Docker with NVIDIA GPU support" update. This post will guide you through a useful Workstation setup (including User-name-spaces and performance tuning) with the new versions of Docker and the NVIDIA GPU container toolkit.
AMD Ryzen 3900X vs Intel Xeon 2175W Python numpy - MKL vs OpenBLAS
Written on August 20, 2019 by Dr Donald KinghornIn this post I've done more testing with Ryzen 3900X looking at the effect of BLAS libraries on a simple but computationally demanding problem with Python numpy. The results may surprise you! I start with a little bit of history of Intel vs AMD performance to give you what may be a new perspective on the issue.
2 x RTX2070 Super with NVLINK TensorFlow Performance Comparison
Written on August 14, 2019 by Dr Donald KinghornThis is a short post showing a performance comparison with the RTX2070 Super and several GPU configurations from recent testing. The comparison is with TensorFlow running a ResNet-50 and Big-LSTM benchmark.
AMD 3900X (Brief) Compute Performance Linpack and NAMD
Written on July 26, 2019 by Dr Donald KinghornI was able to spend a little time with an AMD Ryzen 3900X. Of course the first thing I wanted know was the double precision floating point performance. My two favorite applications for a "first look" at a new processor are Linpack and NAMD. The Ryzen 3900X is a pretty impressive processor!
NVIDIA Docker2 with OpenGL and X Display Output
Written on July 11, 2019 by Dr Donald KinghornDocker is a great Workstation tool. It is mostly used for command-line application or servers but, ... What if you want to run an application in a container, AND, use an X Window GUI with it? What if you are doing development work with CUDA and are including OpenGL graphic visualization along with it? You CAN do that!
Install TensorFlow 2 beta1 (GPU) on Windows 10 and Linux with Anaconda Python (no CUDA install needed)
Written on June 26, 2019 by Dr Donald KinghornTensorFlow 2.0.0-beta1 is available now and ready for testing. What if you want to try it but don't want to mess with doing an NVIDIA CUDA install on your system. The official TensorFlow install documentations has you do that, but it's really not necessary.
How To Run Remote Jupyter Notebooks with SSH on Windows 10
Written on June 11, 2019 by Dr Donald KinghornBeing able to run Jupyter Notebooks on remote systems adds tremendously to the versatility of your workflow. In this post I will show a simple way to do this by taking advantage of some nifty features of secure shell (ssh). What I'll do is mostly OS independent but I am putting an emphasis on Windows 10 since many people are not familiar with tools like ssh on that OS.
How To Use SSH Client and Server on Windows 10
Written on May 31, 2019 by Dr Donald KinghornThis post is a setup guide and introduction to ssh client and server on Windows 10. Microsoft has a native OpenSSH client AND server on Windows. They are standard (and in stable versions) on Windows 10 since the 1809 "October Update". This guide should helpful to both Windows and Linux users who want better interoperability.
How To Install Docker and NVIDIA-Docker on Ubuntu 19.04
Written on May 7, 2019 by Dr Donald KinghornBeing able to get Docker and the NVIDIA-Docker runtime working on Ubuntu 19.04 makes this new and (currently) mostly unsupported Linux distribution a lot more useful. In this post I'll go through the steps that I used to get everything working nicely.
How to Install TensorFlow with GPU Support on Windows 10 (Without Installing CUDA) UPDATED!
Written on April 26, 2019 by Dr Donald KinghornThis post is the needed update to a post I wrote nearly a year ago (June 2018) with essentially the same title. This time I have presented more details in an effort to prevent many of the "gotchas" that some people had with the old guide. This is a detailed guide for getting the latest TensorFlow working with GPU acceleration without needing to do a CUDA install.
How To Install CUDA 10.1 on Ubuntu 19.04
Written on April 5, 2019 by Dr Donald KinghornUbuntu 19.04 will be released soon so I decided to see if CUDA 10.1 could be installed on it. Yes, it can and it seems to work fine. In this post I walk through the install and show that docker and nvidia-docker also work. I ran TensorFlow 2.0- alpha on Ubuntu 19.04 beta.
TensorFlow Performance with 1-4 GPUs -- RTX Titan, 2080Ti, 2080, 2070, GTX 1660Ti, 1070, 1080Ti, and Titan V
Written on March 14, 2019 by Dr Donald KinghornI have updated my TensorFlow performance testing. This post contains up-to-date versions of all of my testing software and includes results for 1 to 4 RTX and GTX GPU's. It gives a good comparative overview of most of the GPU's that are useful in a workstation intended for machine learning and AI development work.
Intel Xeon W-3175X and i9 9990XE Linpack and NAMD on Ubuntu 18.04
Written on February 28, 2019 by Dr Donald KinghornThere are 2 recent Intel processors that are really strange, the Xeon W-3175X 28-core, and the Core i9 9990XE overclocked 14-core. I was able to get a little time in on the these processors. I ran a couple of numerical compute performance tests with the Intel MKL Linpack benchmark and NAMD. I used the same system image that I had used recently to look at 3 Intel 8-core processors so I will include those results here as well. **There will be results for W-3175, 9990XE, 9800X, W-2145, and 9900K**.
RTX Titan TensorFlow performance with 1-2 GPUs (Comparison with GTX 1080Ti, RTX 2070, 2080, 2080Ti, and Titan V)
Written on January 30, 2019 by Dr Donald KinghornI've done some testing with 2 NVIDIA RTX Titan GPU's running machine learning jobs with TensorFlow. The RTX Titan is a great card but there is good news and bad news.
Numerical Computing Performance of 3 Intel 8-core CPUs - i9 9900K vs i7 9800X vs Xeon 2145W
Written on January 25, 2019 by Dr Donald KinghornIn this post I'll take a brief look at the numerical computing performance of three very capable 8-core processors -- i9 9900K, i9 9800X and Xeon 2145W All three are great CPU's but there are some significant differences that can cause confusion. I'll discuss these differences and see how the processors stack up when running Linpack and NAMD molecular dynamics simulations.
P2P peer-to-peer on NVIDIA RTX 2080Ti vs GTX 1080Ti GPUs
Written on January 11, 2019 by Dr Donald KinghornThere has been some concern about Peer-to-Peer (P2P) on the NVIDIA RTX Turing GPU's. P2P is not available over PCIe as it has been in past cards. It is available with very good performance when using NVLINK with 2 cards. I did some testing to see how the performance compared between the GTX 1080Ti and RTX 2080Ti. There were some interesting results!
AMD Threadripper and (1-4) NVIDIA 2080Ti and 2070 for NAMD Molecular Dynamics
Written on December 14, 2018 by Dr Donald KinghornIn my recent testing with the AMD Threadripper 2990WX is was impressed by the CPU based performance with the molecular dynamics program NAMD. NAMD makes a good benchmark for looking at CPU/GPU performance since it requires a balance and is usually limited by CPU. After some discussions I decided it would be good to look at multi-GPU performance with NAMD on Threadripper.
AMD Threadripper 2990WX 32-core vs Intel Xeon-W 2175 14-core - Linpack NAMD and Kernel Build Time
Written on December 6, 2018 by Dr Donald KinghornI recently wrote a post about building and running AMD Threadripper 2990WX with HPL Linpack - a "How-To". Most of the time I had with the processor went into getting that to work. However, I did run a few other test jobs that I thought the 2990WX would do well with. I compared that against my personal workstation with a Xeon-W 2175. In this post I share those test runs with you. It's not thorough testing by any means but it was interesting and I was surprised a couple of times with the results.
How to Run an Optimized HPL Linpack Benchmark on AMD Ryzen Threadripper -- 2990WX 32-core Performance
Written on November 30, 2018 by Dr Donald KinghornThe AMD Ryzen Threadripper 2990WX with 32 cores is an intriguing processor. I've been asked about performance for numerical computing and decided to find out how well it would do with my favorite benchmark the "High Performance Linpack" benchmark. This is used to rank Supercomputers on the Top500 list. It is not always simple to run this test since it can require building a few libraries from source. This includes the all important BLAS library which AMD has optimized in their BLIS package. I give you a complete How-To guide for getting this running to see what the 2990WX is capable of.