AI Pub Dev: An MLOps tool
with web user interface

AI Pub Dev is built on Coaster, a container platform, designed to support efficient management of GPU infrastructure resources for your AI development and training.

AI Pub Dev is a resource management tool for AI development and training.

It enables the allocation of limited AI infrastructure to multiple AI developers, facilitating their efficient use of the allotted GPU infrastructure resources for their specific tasks. AI Pub Dev also allows the administrator to manage the GPU infrastructure resources according to various infrastructure patterns.

Discover AI Pub Dev's functions

With Coaster at its core, AI Pub Dev offers fully-managed services for model training as well as resource and workload management.

Service	Details
Create workload	Manages the user's development environment via Docker images
	Creates workspaces using development images
	Facilitates integration with Jupyter Notebook and TensorBoard
Model Training	Automatically allocates necessary resources for each AI training
Model Training	Enables applications for GPU and CPU resources
Resource Management	Restricts resource usage per user account
	Withdraws idle resources
	Manage workspace of each node & Set MIG for each node
	Monitors the entire infrastructure
Resource Group Management	(for manager) Create resource group and Set user's authorization
Resource Group Management	Edit resource group
Workload Management	Manages suspension/resumption of schedulers
Workload Management	Oversees job scheduling and prioritization
User history management	Manages resource usage history for each user account
User history management	Downloads usage history

Determine resource allocation
priorities with ease

Have you ever struggled with deciding on the priorities for allocating GPU infrastructure resources? With AI Pub Dev, you can easily manage and adjust the order of the resource allocation queue. The scheduler on/off function also allows you to respond flexibly to any changes that may occur.

Fragment MIG into the smallest units
for efficient resource management

AI Pub Dev enables you to fragment MIG into the smallest units, ranging from 1 to 7 fragments per GPU, ensuring optimal resource management. You can also set resource application limit policies for each user account.

Monitor the status and operation rate of GPU resources real time

Discover whether you are utilizing your GPU resources efficiently. Monitor real-time resource status and operation rates for each cluster, node, and project. Additionally, you can track the resource usage amount and utilization rate for each account.