Source-Level Data Object Profiling for Code Optimization
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Solution Overview
Problem
Conventional profiling tools do not provide detailed information about data objects, which consume the most execution time, nor do they correlate multiple code behavior attributes effectively, leading to inefficient code optimization.
Innovation Solution
A method of profiling code that attributes runtime events to source-level data objects by associating instruction instances with language constructs, allowing for targeted optimization by correlating execution time with data objects, addresses, and other code behavior attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If code instrumentation techniques are used to profile code, then execution characteristics can be sampled, but overhead is imposed on the original program code and program behavior may be altered
Solution Approach 1:
The patent segments the profiling function into separate hardware components (event counters, performance monitoring units) that operate independently from the main code execution path. This allows execution characteristics to be sampled without inserting instrumentation code into the program stream, thereby eliminating the overhead and behavior alteration problems while maintaining measurement precision.
Solution Approach 2:
The patent introduces hardware intermediaries (performance monitoring units, event counters) that mediate between the program execution and the profiling process. These hardware components intercept and count execution events without requiring software instrumentation, thus sampling execution characteristics without imposing overhead or altering program behavior.
2Loss of information
If conventional profiling tools are used, then profile information is provided at image, procedure, or instruction level, but detailed information about data objects is not provided
Solution Approach 1:
The patent adds a new dimension to traditional profiling by introducing data object-level analysis alongside the existing image, procedure, and instruction levels. This is achieved through hardware support for tracking memory addresses and data object identifiers, enabling profiling information to be collected and correlated across multiple dimensions without proportionally increasing system complexity.
Solution Approach 2:
The patent creates a universal profiling system where the same hardware infrastructure (performance monitoring units, event counters) supports multiple profiling dimensions simultaneously - image level, procedure level, instruction level, and data object level. This multi-functional approach provides comprehensive profiling information without requiring separate complex systems for each profiling level.
3Loss of time
If profiling support is patched into exception handler code, then overhead on each execution of sampled instruction is avoided, but hardware assistance is required
Solution Approach 1:
The patent implements self-service profiling where the hardware automatically performs profiling functions without requiring software intervention or exception handling. Performance monitoring units and event counters autonomously track execution characteristics, eliminating the need to patch exception handlers and avoiding per-instruction overhead while reducing reliance on complex hardware-assisted software coordination.
Data Source
AI summary
Including source-level data object information in code profiling data enhances code optimization because it provides new perspectives to view code behavior. A method provides for identifying an operation instance of code that corresponds to a runtime event, which is detected in execution of the code. The detected event is attributed to a source-level data object that corresponds to a source-level representation of a language construct. The attribution is based on a predefined association between the identified operation instance and the language construct of the source-level representation that corresponds to the source-level data object.