We challenge
Web-based, easy-to-use integrated
GPU infrastructure anytime, anywhere
Efficient use of hardware resources
Reduce costs through management
Python, Virtualenv management function
Independent development
environment provided by each user
Common use of idle GPU systems
Additional input into complex
data analysis operations
Monitor and statistics overall
GPU usage to enable planned IT
investment and maintenance
Use development systems anytime, anywhere via the web
Access and use through various web browsers,
such as Explorer, Chrome, etc.
Provides a variety of GPU development environments
- GPU resource allocation functions
for various connectivity environments
(VNC, SSH terminal, Container terminal, etc.)
Submit the CLI command-based GPU task scheduler
Provides web-based dedicated GPU job submission form
Worklist viewable, resource usage information available
Ability to apply and manage virtual development environments
Creating a Python, Virtualenv
(virtual environment) per user via the Web
Provide a separate (only) Python
development environment for each user
Manage the generated Virtual Python
Development Environment Package
Container interlocking and using
In-house Container and External Container Repository
Synchronization Capabilities
Create and connect a Container - Fixed CPU Allocation
When creating a Container
Web-based Support Monitoring and System Usage Statistics
Distributed Multi GPU Integration Monitoring
GPU detailed usage status
(GPU, Memory, Power, Temperature Clock, etc.)
Provides GPU job log monitoring
Provides CPU, GPU scheduler task monitoring
Analyze CPU, GPU Usage Statistics by Period