Dynamic Event Handler Allocation for HPC Workloads
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Solution Overview
Problem
Conventional High Performance Computing (HPC) systems face inefficiencies in resource allocation and robustness due to dedicated computing resources, leading to suboptimal processing efficiency and increased costs, especially in handling computationally intensive workloads.
Innovation Solution
Implementing a network-based computing system with stateless event handlers that dynamically allocate computing resources based on event detection, utilizing a shared state system to manage computation results and allocate resources only when necessary, allowing for efficient parallelization and minimizing resource wastage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated computing resources are allocated to handle computationally intensive workloads, then processing reliability is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation where computing resources are not statically assigned but dynamically provisioned based on real-time workload demands. The system monitors application performance metrics and automatically adjusts resource allocation, transforming the static dedicated resource model into a dynamic adaptive model that resolves the contradiction between reliability and utilization efficiency.
Solution Approach 2:
The patent creates a shared computing resource pool that serves multiple applications and workloads simultaneously. Instead of dedicating separate resources to each application, the system enables a universal resource pool that can be flexibly allocated across different computational tasks, improving overall resource utilization while maintaining service reliability through multi-tenancy and resource sharing.
2Speed
If more computing resources are allocated to process computationally intensive workloads, then processing speed is improved, but processing costs increase
Solution Approach 1:
The patent implements partial resource allocation where computing resources are allocated based on the actual computational needs of each workload rather than providing full dedicated resources. The system analyzes workload characteristics and allocates only the necessary portion of computing resources required to achieve acceptable processing speeds, avoiding the waste of excessive resource allocation and reducing processing costs.
Solution Approach 2:
The patent dynamically adjusts resource allocation parameters such as CPU allocation, memory allocation, and compute node provisioning based on workload demands. By changing these parameters adaptively rather than maintaining fixed high-level allocations, the system achieves adequate processing speed while optimizing resource utilization and reducing energy consumption and processing costs.
3Productivity
If computing resources are dynamically allocated based on event detection, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary resource management layer that sits between the computing resources and applications. This intermediary layer handles the complexity of event detection, resource allocation decisions, and coordination, shielding applications from the underlying system complexity while enabling efficient dynamic resource allocation. The intermediary manages the complexity by providing standardized interfaces and abstracting the dynamic allocation mechanisms.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors application performance, resource utilization metrics, and workload characteristics. This feedback information is used to automatically adjust resource allocation decisions, creating a closed-loop control system that optimizes resource utilization efficiency. The feedback-driven approach manages system complexity by using automated control loops rather than manual configuration and management.
Data Source
AI summary
A method for processing computationally intensive workloads includes monitoring a storage system to determine what portion of results of computations associated with an application have been received by the storage system. Responsive to the monitoring determining that the portion of results is sufficient to trigger allocation of one of a plurality of event handlers to the application to process the portion of results: an event handler is allocated to the application, the portion of the results is retrieved from the storage system, a specification of a first computation to be performed and the portion of the results are provided to the event handler, the event handler applies the first computation to the portion of results to produce a new result, the new result is stored in the storage system, and the event handler is deallocated from the application.