Multi-core Processor Dynamic Lane Power Management
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Solution Overview
Problem
Multi-core processors face challenges in efficiently managing power consumption due to stringent power constraints, leading to 'dark silicon' issues where not all transistors can be powered on simultaneously, requiring adaptive power allocation that existing techniques like dynamic voltage and frequency scaling and core-level gating fail to address effectively.
Innovation Solution
The system partitions each core into multiple power regions and lanes, using an online optimization algorithm to determine the combination of powered lanes that optimizes performance under a given power constraint budget, employing techniques like clock gating, power gating, and voltage scaling, and constructs response surface models for rapid adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If all transistors are powered on simultaneously to maximize processing capability, then processing performance is improved, but power consumption exceeds available power budget
Solution Approach 1:
The patent segments each processor core into multiple independently powerable regions (front-end, middle-end, back-end). This segmentation enables selective powering of only the necessary regions based on workload requirements and power budget constraints, resolving the contradiction between maximizing processing performance and minimizing power consumption.
Solution Approach 2:
The patent implements dynamic power region configuration where the system can adaptively enable or disable power regions in real-time based on changing workload characteristics and power budget constraints. This dynamic adjustment allows the processor to optimize the balance between processing performance and power consumption continuously.
2Use of energy by moving object
If existing power management techniques like dynamic voltage and frequency scaling are used, then power consumption is reduced, but they fail to address fine-grained power allocation needs
Solution Approach 1:
The patent divides each core into multiple power regions that can be independently controlled, providing fine-grained power allocation capability that goes beyond traditional whole-core or whole-chip power management approaches. This enables precise control over which parts of the processor consume power based on specific workload requirements.
Solution Approach 2:
The patent enables different power regions within the same core to have different power states simultaneously. For example, the front-end region can be powered on for complex instruction processing while the back-end region remains powered off for simple workloads, achieving local quality differentiation in power allocation.
3Adaptability or versatility
If power regions are partitioned into multiple lanes with independent control, then power allocation precision is improved, but device complexity increases
Solution Approach 1:
The patent segments power control into hierarchical levels (chip-level, core-level, region-level, lane-level), where each level manages specific aspects of power control. This hierarchical segmentation reduces the complexity of controlling individual lanes by organizing control functions at appropriate levels of the hierarchy.
Solution Approach 2:
The patent designs the power region and lane control mechanisms to serve multiple functions: performance optimization, power consumption management, thermal control, and workload adaptation. This multi-functionality reduces the need for separate dedicated control mechanisms for each function.
Data Source
AI summary
The present disclosure provides methods and systems for managing power in a processor having multiple cores. In one implementation, a microarchitecture of a core within a general-purpose processor may include configurable lanes (horizontal slices through the pipeline) which can be powered on and off independently from each other within the core. An online optimization algorithm may determine within a reasonably small fraction of a time slice a combination of lanes within different cores of the processor to be powered on that optimizes performance under a power constraint budget for the workload running on the general-purpose processor. The online optimization algorithm may use an objective function based on response surface models constructed to fit to a set of sampled data obtained by running the workload on the general-purpose processor with multiple cores, without running the full workload. In other implementations, the power supply to lanes can be gated.