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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.

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Puget Systems has over 19 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. Kinghorn

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.

  

Puget Peak Single Xeon Tower

Peak Single Xeon Tower

Customize

Payments starting at $139/month

A powerful enterprise-class tower developer workstation with support for four NVIDIA GPUs.

Puget Peak Dual Xeon Tower

Peak Dual Xeon Tower

Customize

Payments starting at $293/month

A powerful enterprise-class tower developer workstation with support for dual NVIDIA Tesla or GPUs.

Puget Peak 4 GPU 1U Server

Peak 4 GPU 1U Server

Customize

Payments starting at $204/month

A powerful, enterprise-class 1U rackmount server with Intel Xeon processors and up to 4 NVIDIA Tesla or GPU cards.

Puget Peak 8 GPU 4U Server

Peak 8 GPU 4U Server

Customize

Payments starting at $379/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

Read this article at https://www.pugetsystems.com/guides/1638
Dr Donald Kinghorn (Scientific Computing Advisor )

SC19 A look at the high end of HPC

Written on 12/10/2019 by Dr Donald Kinghorn

The 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.

Read this article at https://www.pugetsystems.com/guides/1637
Dr Donald Kinghorn (Scientific Computing Advisor )

How To Use MKL with AMD Ryzen and Threadripper CPU's (Effectively) for Python Numpy (And Other Applications)

Written on 11/27/2019 by Dr Donald Kinghorn

In 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.

Read this article at https://www.pugetsystems.com/guides/1631
Dr Donald Kinghorn (Scientific Computing Advisor )

AMD Threadripper 3970x Compute Performance Linpack and NAMD

Written on 11/25/2019 by Dr Donald Kinghorn

AMD 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.

Read this article at https://www.pugetsystems.com/guides/1617
Dr Donald Kinghorn (Scientific Computing Advisor )

AMD Ryzen 3950x Compute Performance Linpack and NAMD

Written on 11/14/2019 by Dr Donald Kinghorn

The, 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.

Read this article at https://www.pugetsystems.com/guides/1568
Dr Donald Kinghorn (Scientific Computing Advisor )

Workstation Setup for Docker with the New NVIDIA Container Toolkit (nvidia-docker2 is deprecated)

Written on 09/13/2019 by Dr Donald Kinghorn

It'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.

Read this article at https://www.pugetsystems.com/guides/1560
Dr Donald Kinghorn (Scientific Computing Advisor )

AMD Ryzen 3900X vs Intel Xeon 2175W Python numpy - MKL vs OpenBLAS

Written on 08/20/2019 by Dr Donald Kinghorn

In 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.

Read this article at https://www.pugetsystems.com/guides/1551
Dr Donald Kinghorn (Scientific Computing Advisor )

2 x RTX2070 Super with NVLINK TensorFlow Performance Comparison

Written on 08/14/2019 by Dr Donald Kinghorn

This 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.

Read this article at https://www.pugetsystems.com/guides/1540
Dr Donald Kinghorn (Scientific Computing Advisor )

AMD 3900X (Brief) Compute Performance Linpack and NAMD

Written on 07/26/2019 by Dr Donald Kinghorn

I 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!

Read this article at https://www.pugetsystems.com/guides/1527
Dr Donald Kinghorn (Scientific Computing Advisor )

NVIDIA Docker2 with OpenGL and X Display Output

Written on 07/11/2019 by Dr Donald Kinghorn

Docker 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!

Read this article at https://www.pugetsystems.com/guides/1520
Dr Donald Kinghorn (Scientific Computing Advisor )

Install TensorFlow 2 beta1 (GPU) on Windows 10 and Linux with Anaconda Python (no CUDA install needed)

Written on 06/26/2019 by Dr Donald Kinghorn

TensorFlow 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.

Read More