Dynamic Memory Controller Transaction Batching
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Solution Overview
Problem
Existing dynamic memory controllers in digital-logic systems face inefficiencies in data transfer due to frequent switching between read and write transactions, leading to processing overhead and reduced throughput, as they typically process requests in the order received, resulting in potential starvation of one direction or master.
Innovation Solution
Implementing a method that takes snapshots of read and write transactions, executing all transactions in one direction before switching to the other, with the ability to repeat snapshots in the same direction, and prioritizing transactions based on master and memory access to optimize data transfer rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If transactions are processed in the order received (first-come, first-served), then simplicity of control is maintained, but data throughput is reduced due to frequent switching between masters and directions
Solution Approach 1:
The patent applies preliminary action by taking snapshots of pending transactions before execution. The snapshot mechanism captures the state of read and write transaction queues in advance, allowing the system to plan and execute batches of transactions in an optimized order rather than processing them immediately as they arrive. This preliminary capture enables out-of-order execution that maximizes throughput while maintaining controlled complexity through the snapshot abstraction.
Solution Approach 2:
The patent segments transactions into distinct batches based on their direction (read vs. write) and master ID. By dividing the transaction stream into manageable segments that can be executed in optimized sequences, the system achieves higher throughput without overwhelming control logic. Each snapshot represents a segmented batch that can be independently optimized and executed.
2Productivity
If all transactions in one direction are executed back-to-back, then turnaround time is reduced and throughput is maximized, but the other direction may be starved indefinitely
Solution Approach 1:
The patent implements periodic action through alternating snapshots between read and write directions. After executing a batch of read transactions, the system takes another snapshot to capture pending write transactions, ensuring that both directions receive periodic service. This periodic alternation prevents starvation while maintaining efficient batched execution within each direction, balancing throughput optimization with fair service distribution.
Solution Approach 2:
The system dynamically adjusts the execution schedule by taking new snapshots after each direction's transactions are completed. The snapshot mechanism is flexible and adaptive, capturing the current state of pending transactions and allowing the system to respond to changing workloads. This dynamic approach ensures that if one direction has no pending transactions, the system can switch to the other direction without rigid scheduling constraints.
3Reliability
If transactions from the same master are executed back-to-back, then master-specific dependencies are satisfied, but other masters may experience delays
Solution Approach 1:
The snapshot mechanism captures all pending transactions from multiple masters before execution begins. By taking a preliminary snapshot of the entire transaction queue, the system can identify and group transactions from the same master that should be executed together, while also seeing the full context of other pending transactions. This allows optimized batching that satisfies master dependencies without indefinitely delaying other masters.
Solution Approach 2:
The patent segments transactions by master ID within each snapshot, allowing transactions from the same master to be grouped and executed back-to-back when appropriate. This segmentation enables the system to respect master-specific dependencies and internal ordering requirements while still interleving transactions from different masters across multiple snapshots, preventing any single master from monopolizing the execution pipeline.
Data Source
AI summary
Data-transfer transactions from multiple masters may be balanced by taking snapshots of the transactions stored in a buffer, and executing transactions from each master back-to-back.