Per-Lane Bus Power Management for Burst Traffic
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Solution Overview
Problem
Conventional methods for managing power states of bus lanes in communication systems are suboptimal for burst-y traffic, as they do not account for future workload demands, leading to inefficient power usage and performance penalties.
Innovation Solution
Implementing a Future Bus Load Characterization Unit (FBLCU) to analyze workload operations and predict future bus lane power states based on specific transfer details, such as data size and latency sensitivity, allowing for proactive power management of individual lanes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional demand-responsive power state control is used, then power consumption is reduced when demand is low, but performance degrades during burst-y traffic because lanes are not powered up in time
Solution Approach 1:
The patent applies preliminary action by predicting future bus lane demand using a load predictor before the actual transfer occurs. The system proactively transitions lanes to active state in advance of predicted high-demand periods, ensuring lanes are ready when needed rather than reacting after demand is detected. This resolves the contradiction by preparing the system ahead of time, avoiding both the latency penalty of late activation and the energy waste of continuous activation.
2Loss of energy
If per-lane power management is implemented, then power efficiency improves by placing individual lanes in low power state, but system complexity increases due to per-lane control requirements
Solution Approach 1:
The patent applies universality by implementing a single integrated load predictor that serves multiple functions: it predicts overall bus demand, determines the number of lanes needed, and controls the power state of multiple individual lanes. This multi-functional approach consolidates what would otherwise require separate control mechanisms for each lane, reducing overall system complexity while maintaining per-lane power management capabilities.
Solution Approach 2:
The system applies self-service by using the load predictor to automatically monitor bus lane demand and autonomously transition lanes between active and low-power states without external intervention. The predictor continuously assesses traffic patterns and self-adjusts the power configuration, eliminating the need for complex manual or external control systems while achieving fine-grained per-lane power management.
3Loss of time
If lanes are kept in active state to ensure immediate response, then transfer latency is reduced, but power consumption increases continuously
Solution Approach 1:
The patent applies dynamics by making the lane power state adaptive rather than static. The load predictor continuously monitors bus traffic patterns and dynamically adjusts the number of active lanes in real-time based on predicted demand. During high-demand periods, more lanes are activated to reduce latency; during low-demand periods, lanes are transitioned to low-power state to reduce consumption. This dynamic adaptation resolves the contradiction by allowing the system to optimize both latency and power consumption at different times.
Data Source
AI summary
A method includes receiving a request for a transfer of data on a bus of a computing device; determining a direction for the transfer, at least in part based on the request; determining a quantity of data for the transfer, at least in part based on the request; determining a power state for a lane of the bus, at least in part based on the direction and the quantity of data for the transfer; and setting the power state for the lane of the bus.