Resource Aware Programming Tools for Computational Efficiency
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Solution Overview
Problem
Existing programming approaches fail to systematically balance resource usage with quantitative metrics, leading to inefficient resource consumption and inability to ensure consistent satisfaction of user expectations, especially in resource-intensive processes like loops and functions.
Innovation Solution
Resource Aware Programming (RAP) tools generate an approximate version of a program that satisfies quantitative metrics while using fewer resources, employing a calibration phase to build a performance loss model and a synthesis phase to create the approximate version, with a runtime recalibration mechanism to ensure continued metric satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the original program processes the task to 100% completion, then the quantitative metrics are satisfied, but the resource consumption increases significantly
Solution Approach 1:
The patent applies partial action by generating an approximate version of the program that performs only the necessary processing to satisfy quantitative metrics. The RAP tool analyzes the original program and creates a simplified version that stops processing once the metrics are met, avoiding unnecessary computational resources spent on achieving 100% completion when 99% already satisfies user expectations.
Solution Approach 2:
The patent changes the execution parameters by transforming the original program into an approximate version with modified processing depth and resource allocation. The RAP tool adjusts key parameters such as processing iterations, computational depth, and resource distribution to achieve metric satisfaction with reduced resource consumption.
2Use of energy by moving object
If the approximate version uses fewer resources, then the resource consumption decreases, but the program complexity increases
Solution Approach 1:
The RAP tool serves as an intermediary between the original program and the approximate version. It analyzes the original program's structure, identifies optimization opportunities, and generates the approximate version automatically. This intermediary approach reduces the burden on developers to manually optimize while maintaining control over the transformation process.
Solution Approach 2:
The patent creates a copy of the original program that is simplified and optimized. The RAP tool generates an approximate version that replicates the essential functionality of the original program but with reduced complexity and lower resource consumption. This copying approach allows the original program to remain unchanged while providing an optimized variant.
3Use of energy by moving object
If the RAP tool generates an approximate version, then the resource consumption decreases, but the measurement precision of task completion decreases
Solution Approach 1:
The RAP tool incorporates feedback mechanisms that monitor quantitative metrics during program execution. It continuously measures whether the approximate version satisfies the specified metrics and adjusts processing depth accordingly. This feedback loop ensures that resource consumption is reduced while maintaining sufficient precision to meet the required quantitative guarantees.
Data Source
AI summary
The described implementations relate to resource aware programming. In one case a program is obtained that is configured to perform a task in accordance with one or more quantitative metrics. An approximate version can be generated from the program. The approximate version is configured to perform the task in a manner that satisfies the one or more quantitative metrics while using fewer computer resources than the program.