Program Energy Analysis Using Control Flow Graph Scoring
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Solution Overview
Problem
Current software development lacks tools for analyzing and comparing the energy consumption of programs executing algorithms, particularly for making informed decisions on algorithm implementations based on energy efficiency, and there is no method for a priori estimation of energy consumption.
Innovation Solution
A method and system that convert source code into an intermediate representation using a control flow graph, map instructions to energy consumption scores, and calculate total energy consumption scores for comparative benchmarking across different implementations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If software optimization focuses on higher performance, then execution speed is improved, but energy consumption increases
Solution Approach 1:
The invention changes the optimization parameter from purely temporal (execution speed) to include energetic (energy consumption). By introducing energy consumption scores as a measurable parameter alongside execution time, the system enables simultaneous optimization of both performance and energy efficiency, allowing developers to make informed trade-off decisions between speed and energy usage.
Solution Approach 2:
The invention implements feedback mechanisms through energy consumption scoring and analysis tools that provide real-time information about energy usage patterns. This feedback enables developers to identify energy-intensive code sections and optimize them, creating a iterative process of improvement that balances performance and energy consumption.
2Measurement precision
If algorithms are measured separately for each input, then measurement accuracy is improved, but analysis time and complexity increase
Solution Approach 1:
The invention performs preliminary analysis by measuring and scoring energy consumption for different algorithms across various input types beforehand. This preliminary action creates a database of energy consumption profiles that can be used for rapid comparison and selection without requiring time-consuming real-time measurements for each specific input case.
Solution Approach 2:
The invention creates abstract representations (copies) of energy consumption characteristics through standardized scoring mechanisms. Instead of measuring every possible input scenario directly, the system creates representative energy consumption models that capture the essential energy behavior patterns, enabling efficient comparison and selection without exhaustive measurement.
3Device complexity
If only system-level energy measurements are performed, then measurement simplicity is improved, but algorithm-level comparison capability is lost
Solution Approach 1:
The invention segments the system-level energy measurement into algorithm-level components by introducing controlled measurement points at the algorithm level. This segmentation allows energy consumption to be attributed to specific algorithms and code sections while maintaining the simplicity of the overall measurement system through standardized interfaces and abstraction layers.
Solution Approach 2:
The invention introduces an intermediary layer of energy scoring and analysis tools that bridge the gap between simple system-level measurements and detailed algorithm-level analysis. This intermediary layer processes and interprets energy data, providing algorithm-specific information without requiring complex direct measurement hardware at the algorithm level.
4Measurement precision
If no a priori estimation tools are available, then measurement accuracy is improved, but development efficiency decreases
Solution Approach 1:
The invention enables preliminary estimation of energy consumption before algorithm selection or optimization. By providing tools that can predict energy consumption based on algorithm characteristics and input data properties, developers can make informed decisions during the design phase without requiring actual execution measurements, thereby improving development efficiency while maintaining accuracy.
Data Source
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AI summary
The present invention relates to a method for performing an energy consumption analysis of a program executing an algorithm, comprising: converting a source code of the program into an intermediate representation formed by control flow graph comprising basic blocks each including a sequence of consecutive instructions; mapping the instructions of the basic blocks of the control flow graph to corresponding instruction energy consumption scores using an energy model; calculating a block energy consumption score for each basic block of the control flow graph based on the instruction energy consumption scores of the instructions of the respective basic block; and calculating a total energy consumption score of the program based on the block energy consumption scores of the basic blocks of the control flow graph. The present invention further relates to a system and a software development tool.