Peak
Accelerated Parallel Computing
with NVIDIA Tesla and GPU Compute
Peak delivers the highest possible compute performance into the hands of developers, scientists, and engineers to advance computing enabled discovery and solution of the world's most challenging computational problems.
Puget Systems has over 20 years experience designing and building high quality and high performance PCs. Our emphasis has always been on reliability, high performance, and quiet operation. We take this experience to the HPC sector with our Peak family of workstations and servers. Through in-house testing we do not blindly follow the industry -- we help lead it. We provide the products below as starting points that we feel cover some of the most compelling areas that we can contribute to the HPC community. Do you have a project that needs some serious compute power, and you don't know where to turn? Let us help, it's what we do!
Dr. Donald Kinghorn
Scientific Advisor for Puget Systems
Dr. Kinghorn has a 20+ year history with scientific and high performance computing and holds a BA in Mathematics/Chemistry and a PhD in Theoretical Chemistry. If you are looking for a HPC configuration, check out his HPC Blog.
Peak Single Xeon Tower
CustomizePayments starting at $155/month
A powerful enterprise-class tower developer workstation with support for four NVIDIA GPUs.
Peak Dual Xeon Tower
CustomizePayments starting at $271/month
A powerful enterprise-class tower developer workstation with support for dual NVIDIA Tesla or GPUs.
Peak 4 GPU 1U Server
CustomizePayments starting at $208/month
A powerful, enterprise-class 1U rackmount server with Intel Xeon processors and up to 4 NVIDIA Tesla or GPU cards.
Peak 8 GPU 4U Server
CustomizePayments starting at $361/month
A powerful, enterprise-class 4U rackmount server with dual Intel Xeon processors and up to 8 NVIDIA Tesla or GPU cards.
Design
Minimum noise and maximum performance, reliability and usability. Puget Peak is an evolutionary step from our custom systems experience. Genesis performance post-production, Summit server stability, Serenity silent design, Obsidian reliability and even the diminutive Echo have influenced Peak.
Performance
TeraFLOPS. Using Intel Xeon CPU's and the Intel MKL library, or the well established CUDA platform and libraries, there is tremendous potential for applications leveraging the computing power of both the CPU and the GPU.
Application
Ready for use. Peak systems are installed, configured and tested under load before they ship and will (optionally) arrive with the setup and tools you need to get started. Our CentOS setup will provide a configuration that can be the basis of your working environment.
Part of what makes our cooling both effective and quiet is that we specifically target the hot spots of each system. We place fans only where they are needed and only when they are needed. We then verify the final configuration with extensive testing, full load stress testing, and thermal imaging to ensure excellent cooling.
Example of Puget Systems targeted cooling
Without targeted cooling
With targeted cooling
We know that these PCs are intended for heavy, long duration workloads. We have designed them for long life with 24/7 load, and that is our primary design goal. Through targeted cooling and high quality thermal solutions, we are able to achieve an excellent low noise level while maintaining the cooling necessary for long term high load. Even better, since we are implementing a custom cooling plan for each order, if you have a preference of whether you'd like us to tune more aggressively in either direction (towards even quieter operation, or more extreme cooling), all you have to do is let us know!
Recommended Reading
Note: Self-Signed SSL Certificate for (local) JupyterHub
Written on 05/07/2020 by Dr Donald KinghornIn 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.
Note: JupyterHub with JupyterLab Install using Conda
Written on 04/17/2020 by Dr Donald KinghornThis is a quick note about setting up a JupyterHub server and JupyterLab using conda with Anaconda Python.
HPC Parallel Performance for 3rd gen Threadripper, Xeon 3265W and EPYC 7742 (HPL HPCG Numpy NAMD)
Written on 04/09/2020 by Dr Donald KinghornOn 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.
Adjusting to Working from Home - Don in Labs
Written on 04/03/2020 by Dr Donald KinghornI am the Scientific Computing adviser here at Puget Systems. Many of us are sharing our work-from-home stories for coping with the changes to our normal life and work routines during the COVID-19 quarantine. I have already been working from home for a few years and wanted to share my setup and offer some tips that I hope will encourage you if you are suddenly finding yourself bewildered by disruption to your work-life.
Threadripper 3990x vs 3970x Performance and Scaling (HPL, Numpy, NAMD plus GPUs)
Written on 03/06/2020 by Dr Donald KinghornIs 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.
Threadripper 3990x 64-core Parallel Scaling
Written on 02/25/2020 by Dr Donald Kinghorn64 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.
Note: How To Install JupyterHub on a Local Server
Written on 02/19/2020 by Dr Donald KinghornThis note describes installing and configuring JupyterHub and JupyterLab on a "bare-metal" server.
AMD Threadripper 3990x 64-core Linpack and NAMD Performance (Linux)
Written on 02/07/2020 by Dr Donald Kinghorn64 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.)
Note: Auto-Install Ubuntu with Custom Preseed ISO
Written on 01/30/2020 by Dr Donald KinghornThis note describes creating an ISO image for a fully automatic, customized Ubuntu 18.04 server install.
Note: Setup Git for PowerShell on Windows 10
Written on 01/24/2020 by Dr Donald KinghornHow to setup PowerShell nicely for using git with command completion and color highlighted shell prompt git status/action notifications.
Monthly Payment Options
We know that the purchase of a PC can be a large investment! Puget Systems is pleased to offer two options receive the best hardware for your workload with low, predictable, monthly payments:
Hardware and software never stops advancing, and the right PC for your workflow can quickly change over time. That's why Puget Systems has partnered with LiftForward to redefine ownership with business leasing, providing a 24-month subscription option. It's an easy way to get the best hardware today, while allowing you to upgrade to a new PC every two years! When your subscription is finished, your hardware is returned and is repurposed to start a new life in schools, developing countries, and communities in need. You then can repeat the process with brand new hardware, so you are always up to date.
Puget Systems has also partnered with Affirm to provide consumer financing, allowing you to make your purchase via easy monthly payments over 24 months. Enrolling is quick and easy. Enter a few pieces of information for a real-time decision. Checking your eligibility won't affect your credit score. Affirm has no hidden fees. You know up front exactly what you'll owe, with no hidden costs and no surprises.