Sometimes complex machine learning and AI software development needs a head start. Well, that’s exactly what Puget Systems has done. Take a look:
Puget Systems Unveils New Series of Turnkey, Multi-User Machine Learning Development Servers
Puget Systems Embraces Small Research and EDU Groups Collaborating Remotely or On-Premise for Intensive AI, Machine Learning Software Development
Auburn, WA (August 10, 2020) – Puget Systems (www.pugetsystems.com) today announced it is unveiling a new series of pre-configured, turnkey AI and machine learning development servers specifically designed for small development teams, research and EDU departments who require a shared, remote and secure development environment that also allows for self-managed resource sharing.
The Puget Systems Machine Learning/AI Development Servers are pre-configured, web browser accessed, GPU-accelerated machines that integrate proven, open-source development platforms, and leverage a ready-to-use software stack to provide an easily extensible framework and environment on a system wide basis or by individual users. Additionally, the underlying Linux foundation together with NVIDIA GPU accelerated computing provides a solid base for modern ML/AI working environments, and is easily monitored and managed for single or multiple users with the browser based Cockpit interface.
“Our Machine Learning Development Servers have been designed and configured with hardware and software specifically validated and tested for this purpose,” said Jon Bach, president of Puget Systems. “Our Hardware validation team has chosen components in cooperation with Puget Systems Labs that meet high expectations of reliability under high performance heavy load. The software layer for system administration/maintenance and ML development was configured by our own in-house Scientific Computing Advisor, Dr. Donald Kinghorn. The configuration was developed with a sincere desire to provide a flexible and simple to use working environment for ML/AI and scientific researchers and developers, based on our many years of experience helping other researchers and developers overcome obstacles to their work.”At launch, Puget Systems is offering two configurations:
- 4-GPU Tower Server/Workstation
- Based on the Intel Xeon 64L platform with NVIDIA GPUs
- Configured as Server (no GUI) or Workstation (with Desktop GUI)
- 1U 4-GPU Server
- Based on Intel Xeon with NVIDIA GPUs
The open-source development software configurations integrated in both offerings include:
- Ubuntu legacy server 18.04 + development tools (optional Desktop install)
- Cockpit Web based System Administration interface
- JupyterHub serving the JupyterLab web based development interface
- Pre-configured JupyterLab “kernels” for ML/AI dev work
- Instructions for easily adding new or customized “kernels/environments”
Optimal development environments benefiting most from the new machine learning series include those which require:
- Shared remote resource for ML/AI development work for a small team that can self-manage resource sharing;
- Ability to access the systems from a LAN or VPN (the configuration is not intended for use on public networks without proper firewall protections by a network administrator);
- Class or workshop environments that need to temporally create accounts for several users. Note; GPU resources are limited, but for many educational purposes, CPU will provide support for many users.
- A high performance, well configured machine learning system for personal use, but with the ability to work from a preferred OS and device. Note: it is possible to easily add a desktop environment to the “tower” system for use as a conventional Workstation that still provides the advantages of the server configuration.
Key Attributes of the Puget Systems Machine Learning Development series include:
- Easy setup process so you can get to work faster. Use Cockpit to add users, login through JupyterHub or MS VScode and start working
- Remote Access via any modern web browser on any OS. Fully utilize the system from Windows, MacOS, Linux, or any device with a web browser. Connect from a PC, Laptop, ChromeBook, even a Tablet or Cell Phone
- Multi-user or single-user access; one system allows easy access for an entire team, class, or workshop with a simplified single-user/power-user experience.
- High performance hardware reduces development cycle iteration time with GPU accelerated computing and many-core CPUs.
- Ready to use with state of the art Machine Learning frameworks pre-installed enables users to easily add/remove customized environments to JupyterLab for all users or by individual users.
- Simplified system-administration means there is no requirement for specialized Linux knowledge. A browser-based administration interface for system maintenance and user management enables users to be easily added and removed, apply updates, and monitor usage. Terminal access is also available if needed from Cockpit, JupyterLab, VScode and SSH
- A task oriented, “how-to” documentation is included to enhance productivity, and administrator and user guides help with customization.
The Puget Systems Machine Learning Development Server series is available immediately, but to learn more or to speak with a consultant to determine the appropriate configurations for your organization, please visit https://www.pugetsystems.com/recommended/Recommended-Systems-for-Machine-Learning-Development-246.