Queue Entry Age Monitoring with Compressed Timestamp Encoding
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Solution Overview
Problem
Existing queue management systems face challenges in efficiently monitoring the age of entries in submission queues, leading to increased memory usage and difficulties in debugging and predicting timeouts due to discrepancies between host and device perspectives on entry ages.
Innovation Solution
Implementing encoding schemes such as delta encoding, entropy encoding, and run length encoding to compress timestamp measurements, along with dynamic parameter adjustment based on queue status and performance, to monitor entry ages from submission, reducing memory usage and enhancing debugging capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If timestamp measurements are stored for each queue entry to track entry age, then debugging capability and timeout detection are improved, but memory usage increases
Solution Approach 1:
The patent applies delta encoding to transform absolute timestamp values into relative time differences, and entropy encoding to compress the encoded data based on probability distributions. These parameter transformations reduce the storage space required for timestamp measurements while preserving the ability to accurately calculate entry ages by accumulating delta values.
Solution Approach 2:
The patent creates compressed representations (encoded copies) of timestamp data that consume less memory. By storing encoded measurements rather than raw timestamps, the system maintains the essential information needed for entry age tracking while significantly reducing the quantity of stored data.
2Quantity of substance
If encoding schemes are applied to compress timestamp measurements, then memory usage is reduced, but system complexity increases
Solution Approach 1:
The patent implements dynamic parameter adjustment where encoding parameters are adapted based on observed queue characteristics such as entry submission patterns and time intervals. This dynamic approach allows the system to optimize compression efficiency for different workload scenarios without requiring manual configuration or complex static analysis.
Solution Approach 2:
The encoding system automatically adapts to the queue's operational characteristics by monitoring entry patterns and adjusting encoding parameters accordingly. The system serves itself by learning from observed data patterns and optimizing its own compression strategy without external intervention.
3Measurement precision
If entry age is tracked from submission time, then timeout detection accuracy is improved, but discrepancies between host and device perspectives persist
Solution Approach 1:
The patent records the submission timestamp at the moment an entry is submitted to the queue, establishing a reference point before any processing occurs. This preliminary timestamp recording ensures that both host and device can independently calculate entry age from the same starting point, eliminating perspective discrepancies.
Solution Approach 2:
The patent enables the device to monitor and report entry age measurements back to the host, creating a feedback loop that allows both parties to verify and align their understanding of entry ages. This feedback mechanism helps resolve perspective differences by providing shared measurement data.
Data Source
AI summary
A method may include receiving, at a device, an indication based on an entry submitted to a queue, obtaining, based on the indication, a measurement for the entry, encoding the measurement to generate an encoded measurement, and storing the encoded measurement. The encoding may include one or more of delta encoding, entropy encoding, or run length encoding. The method may further include modifying the measurement based on a status of the queue. The status of the queue may include an amount of entries in the queue, and the modifying the measurement may include setting the measurement to a value. The status of the queue may include an empty queue, and the modifying the measurement may include resetting the measurement. The encoding may include encoding based on one or more parameters. The method may further include determining at least one of the one or more parameters.