Memory Controller Timing for Volatile SRAM Retention and Power-Down
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Solution Overview
Problem
Existing memory systems face high current consumption during low power states due to inefficient management of volatile memory states, leading to unnecessary power usage when data stored in retention SRAM is not referenced.
Innovation Solution
Implementing a memory system with a timer-based control mechanism that transitions volatile memory from a retention state to a power down state based on threshold values calculated from historical wake-up times or data access frequencies, reducing power consumption by cutting off power to the storage circuit when data is unlikely to be referenced.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If volatile memory remains in retention state during low power states, then data can be quickly accessed upon wake-up, but current consumption increases unnecessarily
Solution Approach 1:
The patent implements dynamic state management of volatile memory by transitioning between retention state and power down state based on predicted wake-up timing. The controller calculates predicted wake-up times from historical data and adjusts memory power states accordingly, making the system adaptive rather than static. This resolves the contradiction by dynamically optimizing between speed and energy consumption based on actual usage patterns.
Solution Approach 2:
The patent performs preliminary actions by pre-calculating wake-up times and pre-managing memory power states before actual wake-up occurs. The controller stores historical wake-up time data and uses it to predict future wake-up times, then proactively transitions memory to power down state when early wake-up is predicted, or maintains retention state when late wake-up is expected. This preliminary management resolves the contradiction by preparing the system in advance rather than reacting to actual wake-up events.
2Use of energy by moving object
If volatile memory transitions to power down state early, then current consumption is reduced, but data access may be delayed upon wake-up
Solution Approach 1:
The patent implements feedback mechanisms by continuously monitoring actual wake-up times and comparing them with predicted wake-up times. The controller stores historical wake-up time data and uses this feedback to refine future predictions and adjust memory power state management strategies. This feedback loop resolves the contradiction by learning from past performance and optimizing future energy-time trade-offs based on actual system behavior rather than static assumptions.
Solution Approach 2:
The patent enables the memory system to self-manage its power states by automatically predicting wake-up times and making autonomous decisions about memory power management. The controller independently calculates predicted wake-up times, determines appropriate memory states, and executes power state transitions without external intervention. This self-service capability resolves the contradiction by allowing the system to autonomously optimize its own energy consumption and performance characteristics.
Data Source
AI summary
A memory system includes a nonvolatile memory that stores table data and a memory controller for writing and reading data to and from the nonvolatile memory. The memory controller includes a volatile memory that can be in either a retention state during which power is supplied thereto or a power down state during which the power supplied thereto is cut off, a timer that measures elapsed time starting from when the memory system transitions to the low power state, and a register in which previously measured elapsed times are stored, and in which a current measured elapsed time is stored when the memory system wakes up from the low power state. The controller controls the transitioning of the volatile memory from the retention state to the power down state, if the measured elapsed time is greater than a threshold value, which is calculated based on the previously measured elapsed times.