Heap Memory Capacity Tuning Using Full GC Frequency

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Solution Overview

Problem

Existing heap memory management systems face inefficiencies in adapting to diverse big data scenarios, requiring manual expertise and repetitive adjustments, leading to resource waste or performance instability.

Innovation Solution

A memory management method that utilizes log data from garbage collection to construct a memory estimation model, using the frequency of full garbage collection as an independent variable and estimated capacity as a dependent variable, to accurately configure heap memory capacity based on expected full garbage collection frequency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual expertise and repetitive adjustments are used for heap memory management, then memory capacity can be adapted, but resource waste and performance instability occur

Engineering Contradiction:

Improvememory capacity adaptationVSAvoidperformance stability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system performs self-diagnosis and self-configuration of heap memory capacity by automatically collecting GC log data, analyzing old generation memory usage indicators, and adjusting memory parameters without manual intervention. This eliminates the need for expert operators while maintaining adaptive memory management capability.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system continuously monitors garbage collection log data and uses the frequency of full GC as feedback to dynamically adjust heap memory capacity. This closed-loop control ensures performance stability by automatically optimizing memory allocation based on actual runtime conditions.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If manual expertise is used for heap memory management, then memory capacity can be adjusted, but operation complexity increases

Engineering Contradiction:

Improvememory capacity adaptationVSAvoidoperation simplicity

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The memory management system automatically performs all configuration tasks by itself - collecting logs, analyzing indicators, constructing estimation models, and adjusting parameters. This completely eliminates the need for manual operations and expert knowledge, making the system easy to operate while maintaining high adaptability.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-collects garbage collection log data and pre-analyzes old generation memory usage indicators to build an estimation model before actual memory optimization is needed. This preliminary preparation enables rapid, automated decision-making without requiring manual intervention during critical optimization phases.

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If traditional memory management methods are used, then implementation is simple, but measurement precision of memory capacity requirements is insufficient

Engineering Contradiction:

Improvememory capacity estimation accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system introduces an intermediary estimation model that uses garbage collection frequency as a measurable proxy for memory capacity requirements. This model acts as a bridge between observable GC behavior and the underlying memory capacity needs, enabling precise measurement without direct complex analysis of memory allocation patterns.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system replaces manual expert analysis with an automated computational model that processes GC log data and calculates optimal memory capacity. This substitution of mechanical/electronic computation for human expertise achieves high measurement precision while managing system complexity through algorithmic automation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20260050550A1Memory management method, electronic device and storgae medium

Publication Date: 2026.02.19 BEIJING VOLCANO ENGINE TECH CO LTD

AI summary

Embodiments of the present disclosure provide a memory management method, electronic device and storage medium. The method includes: obtaining log data of garbage collection performed on a heap memory; obtaining an indicator related to an old generation memory usage amount according to the log data; constructing a memory estimation model by using a frequency of full garbage collection as an independent variable and an estimated capacity of the heap memory as a dependent variable according to the indicator related to the old generation memory usage amount and an original capacity of the heap memory; obtaining a target capacity of the heap memory according to the memory estimation model and an expected frequency of the full garbage collection; and configuring a capacity of the heap memory according to the target capacity of the heap memory.