Auto-Clustering Service Templates for Accessible HPC Deployment
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Solution Overview
Problem
The challenge of deploying high performance computing (HPC) systems is that they are difficult to use and require expensive IT expertise, making them inaccessible to non-expert users with limited budgets, especially when transitioning from monolithic workstation-based platforms to HPC platforms.
Innovation Solution
A system and method for automating the deployment of clusters of clusterable services, utilizing a controller to manage and configure compute, storage, and networking resources, including templates and scheduling, to provide seamless scaling and accessibility of HPC as a service (HPCaaS) to a wider audience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If HPC systems are deployed with traditional expert-driven configuration and management, then computational performance and resource utilization are optimized, but system complexity and cost of operation increase significantly
Solution Approach 1:
The system implements self-service through automated service templates that contain pre-configured clustering rules, dependencies, and deployment parameters. These templates enable the HPC system to automatically configure and manage its own cluster resources without requiring expert user intervention, thereby maintaining high computational performance while reducing system complexity and operational costs
Solution Approach 2:
The patent applies preliminary action by pre-configuring service templates with all necessary clustering rules, resource dependencies, and deployment parameters before actual cluster deployment. This advance preparation allows the system to automatically generate and manage cluster configurations, eliminating the need for complex manual setup while preserving optimized resource utilization
2Ease of operation
If manual configuration and deployment of HPC clusters is performed, then precise control over resource allocation is achieved, but ease of operation deteriorates for non-expert users
Solution Approach 1:
The patent introduces service templates as an intermediary layer between users and the complex HPC cluster configuration process. These templates act as mediators that translate simple user requests into detailed automated deployment instructions, making the system easy to operate for non-experts while maintaining the necessary automation capability through pre-defined clustering rules and resource management policies
3Ease of operation
If automated service templates with clustering rules are implemented, then ease of deployment improves for non-expert users, but initial system configuration complexity increases
Solution Approach 1:
The patent applies preliminary action by creating comprehensive service templates in advance that encapsulate all clustering rules, resource dependencies, and deployment parameters. This upfront configuration work, performed during system initialization rather than during each deployment, enables easy automated deployment for non-expert users while concentrating the configuration complexity in a one-time setup phase
Solution Approach 2:
The patent uses copying by creating reusable service template instances that can be replicated across multiple deployments. Once a service template is initially configured with all necessary clustering rules and dependencies, it can be copied and applied repeatedly to deploy multiple clusters with consistent configurations, thereby improving ease of deployment while amortizing the initial configuration effort across multiple uses
Data Source
AI summary
A system can be configured to automatically deploy clusters of clusterable services. For example, controller can deploy a plurality of copies of an application, and these applications can interdepend on each other. The controller can also configure a scheduler to manage (which may include load balancing) these applications. A service template used by the controller can include clustering rules, and these clustering rules can tell the controller how to connect those services. The clustering rules can be a set of logic instructions and/or templates that provide for the deployment of a service to a plurality of resources. Coupling instructions in the clustering rules define the coordination and interaction of separately booked physical and/or virtual resources and set up dependencies. The clustering rules define the use of information to scale up or scale down resources being used by a service.