Counter Management Device for Sequential Learning
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Solution Overview
Problem
In distributed environments, concurrent updates to a counter value in a distributed database can result in data being overwritten, leading to a loss of sequentiality and inefficiencies in processing resources.
Innovation Solution
A counter management device employs a locking mechanism to update counter values atomically and streams these values to a FIFO queue, ensuring that each processing unit receives a unique and sequential counter value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If concurrent updates to counter values are allowed in a distributed database, then processing throughput is improved, but data sequentiality is lost and data overwriting occurs
Solution Approach 1:
The patent introduces a counter management device as an intermediary component between processing units and the distributed database. This mediator receives counter update requests from multiple processing units, manages the counter values sequentially, and prevents data overwriting by ensuring each counter value is assigned to only one feedback instance. The intermediary maintains an ordered stream of counter values that are distributed to processing units in sequence, thus preserving data sequentiality while allowing concurrent processing.
2Reliability
If atomic operations are performed for each counter update, then data sequentiality is maintained, but processing overhead increases
Solution Approach 1:
The patent merges multiple counter update operations into a single coordinated process managed by the counter management device. Instead of each processing unit performing separate atomic operations on the distributed database, the counter management device consolidates these requests and generates a single ordered stream of counter values. This combining approach maintains data sequentiality through atomic operations while significantly reducing the total processing overhead by eliminating redundant atomic operations across multiple processing units.
Data Source
AI summary
In some implementations, a device may receive, via a feedback stream, one or more feedback instances associated with a machine learning model. The device may update a counter to obtain counter values for respective feedback instances of the one or more feedback instances based on performing atomic operations for the respective feedback instances. The device may provide, via a data stream, the counter values to a first-in-first-out (FIFO) queue to be written in an order of completion of the atomic operations. The device may store the one or more feedback instances in connection with respective counter values based on obtaining the counter values from the FIFO queue in the order of completion. The device may perform, using the one or more feedback instances, one or more training operations for the machine learning model.