Hierarchical Time Tree for Efficient Program Profiling
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Solution Overview
Problem
Conventional profiling techniques require accessing and processing large volumes of call stack samples to generate profile reports, which can be inefficient and time-consuming, especially in multi-threaded applications where sampling occurs for each thread.
Innovation Solution
The construction and use of a hierarchical time tree that represents an execution time of a program, allowing for efficient evaluation and reporting by recursively populating nodes, where each node represents a time interval and includes only the most frequently occurring call stacks, reducing the need to access all call stack samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional profiling techniques access and process large volumes of call stack samples to generate profile reports, then the completeness and accuracy of profiling data is improved, but the time consumption and processing efficiency deteriorate
Solution Approach 1:
The patent segments the call stack data by organizing it into a hierarchical tree structure where the root node represents the main program and child nodes represent called functions. This segmentation allows the system to process and present data in a structured manner, accessing only relevant portions of the call stack rather than processing all samples linearly, thus reducing time consumption while maintaining profiling accuracy.
Solution Approach 2:
The patent performs preliminary action by pre-processing call stack samples and organizing them into a hierarchical tree structure during the profiling execution. This pre-organization allows for rapid query and report generation later, as the data is already structured and indexed, eliminating the need to re-process raw samples when generating reports.
2Measurement precision
If call stacks are sampled at periodic intervals throughout program execution, then the coverage of profiling data is improved, but the volume of recorded data increases linearly
Solution Approach 1:
The patent merges redundant call stack information by identifying common ancestral chains in the call stack tree. When multiple call stacks share common functions in their call chains, the patent represents these shared portions once in the hierarchical structure, merging duplicate data and significantly reducing the overall data volume while preserving complete profiling coverage.
Solution Approach 2:
The patent applies the nested doll principle by creating a hierarchical tree structure where child nodes (representing called functions) are nested within parent nodes (representing calling functions). This nesting allows the system to represent deeply nested call stacks in a compact form, where shared ancestral chains are represented once at higher levels, reducing data volume while maintaining full profiling coverage.
3Measurement precision
If the call stack tree is augmented by adding nodes for each unique call stack encountered, then the completeness of call stack representation is improved, but the complexity of data structure increases
Solution Approach 1:
The patent applies universality by creating a multi-functional hierarchical tree structure that serves multiple purposes: it represents complete call stack information, enables efficient querying for different time periods, supports dynamic re-evaluation when time periods change, and provides a compact representation by merging common ancestral chains. This single structure fulfills multiple functions that would otherwise require separate data structures.
Solution Approach 2:
The patent transitions from a linear one-dimensional representation of call stacks to a hierarchical multi-dimensional tree structure. By organizing call stack data in hierarchical levels (root node representing main program, child nodes representing called functions), the system gains the ability to efficiently query and manipulate data based on different dimensions such as time period, function hierarchy, and call frequency, reducing structural complexity while maintaining completeness.
Data Source
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AI summary
The construction or use of a hierarchical time tree that represents an execution time of a program. To construct the hierarchical time tree, the time frame corresponding to the root node is the execution time during which the plurality of call stack samples were gathered from the program. Beginning at the root node, and proceeding recursively, each node is then populated in a manner that all of the call stacks for a given time period need not be accessed in order to provide a report regarding the given time period.