Gatekeeper-Managed Compute Resource Lanes for Workload Scaling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing compute resource allocation systems struggle to efficiently scale with growing software development teams, leading to idle time and suboptimal utilization due to synchronized pipelines that restrict access to compute resources, causing work and resource starvation.
Innovation Solution
Implementing a system with input constraints, resource lanes, processing rules, and a gatekeeper to manage compute resources, ensuring no work or resource starvation by dynamically distributing work based on availability and priority.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a resource lock is used to restrict access to compute resources, then resource allocation control is improved, but resource utilization deteriorates due to idle time and work starvation
Solution Approach 1:
The system segments the compute resources into multiple independent resource pools (e.g., CPU pool, GPU pool, memory pool) that can be independently allocated and managed. This segmentation allows different workloads to access different resource pools concurrently, eliminating the single-point bottleneck of a unified resource lock while maintaining controlled allocation through pool-specific management mechanisms.
Solution Approach 2:
The patent introduces an intermediary allocation mechanism that sits between the workload and compute resources, managing resource distribution without requiring a single global lock. This intermediary layer enables coordinated access to multiple resource pools simultaneously, preventing work starvation while avoiding the inefficiency of sequential access enforced by traditional resource locks.
2Stability of the object's composition
If synchronized pipelines are used to process builds, then processing order is improved, but throughput deteriorates due to sequential execution constraints
Solution Approach 1:
The system transitions from a single-dimensional sequential pipeline to a multi-dimensional concurrent processing model. Multiple pipelines can execute simultaneously across different resource pools, with each pipeline maintaining its own processing order. This dimensional expansion allows builds to be processed in parallel while preserving the stability and orderliness of individual processing streams through dedicated pipeline management.
3Device complexity
If compute resources are allocated to one build at a time, then resource allocation simplicity is improved, but scalability deteriorates as development teams grow
Solution Approach 1:
The patent creates a universal resource pool architecture where compute resources can serve multiple workloads simultaneously across different pipelines and priority levels. The system maintains allocation simplicity through standardized pool management interfaces while achieving scalability by allowing the same resource pools to be shared and reused across numerous concurrent builds and development teams, eliminating the need for separate dedicated resources for each build.
Data Source
AI summary
Systems and methods that direct items of incoming work to respective resource lanes. A gatekeeper uses processing rules to send items of work in the resource lanes to a resource pool where compute resources are assigned to work on the items. The processing rules allow for distribution of the work from the resource lanes to the processing pool so as to prevent work starvation and compute resources starvation.