Memory Controller Dynamic Signal Processing Engine Allocation
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Solution Overview
Problem
Existing memory systems face challenges in efficiently managing power and performance due to the fixed allocation of signal processing engines to channels, limiting adaptability to varying operating conditions and leading to suboptimal error correction and data transfer efficiency.
Innovation Solution
A memory controller with a signal processing block and schedulers that dynamically activate and distribute data across multiple signal processing engines, such as ECC, encryption, or compression engines, based on their states and the operating conditions, allowing for real-time adjustment of bandwidth and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If signal processing engines are fixedly allocated to channels, then device complexity is reduced and ease of operation is improved, but adaptability to varying operating conditions deteriorates and productivity decreases
Solution Approach 1:
The patent implements dynamic allocation of signal processing engines to channels based on operating conditions. The controller dynamically determines which engines to activate and assigns them to specific channels according to current workload, power constraints, and performance requirements, allowing the system to adapt flexibly to varying operating conditions rather than using fixed allocation.
Solution Approach 2:
The patent creates a universal signal processing architecture where engines can serve multiple channels and multiple functions. A single signal processing engine can be allocated to different channels at different times and can perform various signal processing tasks including error correction, encryption, and compression, making the system more versatile without proportionally increasing the number of dedicated engines.
2Productivity
If all signal processing engines are activated, then error correction efficiency and data transfer rates are improved, but power consumption increases
Solution Approach 1:
The patent dynamically adjusts the number and type of signal processing engines activated based on real-time operating conditions. When high data transfer rates are required, more engines are activated; when power savings are prioritized, fewer engines remain active. This dynamic activation strategy allows the system to optimize the trade-off between productivity and power consumption rather than maintaining a fixed activation state.
Solution Approach 2:
The patent changes operational parameters including the activation state of signal processing engines based on power management policies and performance requirements. By adjusting parameters such as engine activation status, allocation mappings, and processing throughput, the system can operate at different power levels while maintaining acceptable performance, effectively managing the power-productivity trade-off.
3Productivity
If signal processing engines are dynamically allocated, then adaptability and performance are improved, but device complexity and control difficulty increase
Solution Approach 1:
The patent incorporates feedback mechanisms where the controller monitors the performance, workload, and status of signal processing engines and channels, then uses this information to make informed allocation decisions. The system continuously adjusts engine assignments based on feedback about current operating conditions, ensuring optimal error correction efficiency while managing complexity through data-driven control rather than arbitrary allocation.
Solution Approach 2:
The patent enables the signal processing system to self-manage resource allocation to some extent. The controller automatically determines optimal engine activation and assignment based on monitored conditions without requiring external intervention, allowing the system to self-optimize its performance and complexity balance. This self-service capability reduces the burden on external controllers while maintaining adaptive efficiency.
Data Source
AI summary
A memory controller connected with a storage medium via a plurality of channels is provided which includes a signal processing block including a plurality of signal processing engines; and a decoding scheduler configured to control a data path such that at least one activated signal processing engine of the plurality of signal processing engines is connected with the plurality of channels, respectively.