Memory Usage Interface for Pinpointing Sub-Optimal Code
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Solution Overview
Problem
Current console development tools lack the necessary granularity to effectively optimize memory usage, particularly in terms of cache hit rates and latency, making it difficult for developers to identify and address inefficiencies in memory resource utilization.
Innovation Solution
A memory usage interface that provides a graphical user interface to analyze memory calls, trace memory access, and present relevant source code portions causing issues, allowing developers to sort and prioritize potential memory problems for optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If developers use traditional memory analysis tools to measure cache hit rates and latency, then they can identify general memory inefficiencies, but they lack the granularity to pinpoint specific sub-optimal code sections
Solution Approach 1:
The patent segments memory analysis into hierarchical levels: aggregate memory statistics, function-level breakdowns, and basic block-level granularity. This segmentation allows developers to drill down from high-level overview to specific code sections causing memory inefficiencies, achieving fine granularity without overwhelming complexity.
Solution Approach 2:
The patent introduces an intermediary analysis layer that correlates memory events (cache misses, latency measurements) with source code locations. This intermediary layer acts as a bridge between raw memory metrics and actionable code optimization, enabling precise identification of problematic code sections without requiring developers to manually trace through complex memory operations.
2Loss of information
If developers manually trace memory calls to identify inefficiencies, then they can obtain detailed memory access information, but the process becomes time-consuming and complex
Solution Approach 1:
The patent performs preliminary automated tracing and analysis of memory calls during application execution. Memory events are captured, correlated with source code, and aggregated into actionable reports before developers need to review them. This preliminary action eliminates the need for developers to manually trace memory calls, providing detailed memory access information instantly.
Solution Approach 2:
The patent implements feedback mechanisms that automatically generate and present memory optimization recommendations to developers. The system continuously monitors memory usage, identifies patterns of inefficiency, and provides actionable feedback correlated with specific code locations, enabling rapid iteration without time-consuming manual analysis.
3Productivity
If developers optimize memory usage by amending source code, then cache utilization improves and CPU idle time decreases, but it becomes difficult to identify which specific code sections need optimization
Solution Approach 1:
The patent employs visual indicators (such as color-coding or highlighting) to mark code sections with memory inefficiencies in the source code view. Problematic areas are visually distinguished from optimized code, making it immediately apparent which sections require attention. This visual feedback directly guides developers to specific optimization targets, enabling focused improvements that increase processing speed.
Data Source
AI summary
Systems and methods for using memory usage to pinpoint sub-optimal code for gaming systems are provided herein. Memory usage characteristics, such as latency, cache misses, load-hit-store, memory address misuse, and wasted cache bandwidth are presented, preferably in a graphical format, to provide the developer with information for optimizing source code. A trace analysis is performed on source code undergoing optimization. Relevant data is extracted from the trace analysis, sorted as necessary, and presented to the user. The user may be presented with multiple results sorting mechanisms as well as ways to change the presentation of the results.