EDA Deep Tracing for Multi-Layer Event Correlation
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Solution Overview
Problem
Existing EDA testing methods face challenges in probing and correlating events across different protocol layers, making it difficult to diagnose issues in emulated electronics designs, particularly under conditions mimicking real-world data center traffic with AI/ML workloads, and manual analysis is time-consuming and labor-intensive.
Innovation Solution
Implementing dynamically instantiated probes in a test system and EDA emulator to capture and correlate events related to emulated data center traffic, using in-band and out-of-band probe control metadata, and leveraging AI for probe configuration, to automatically trace and analyze events across multiple protocol layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of packet capture data is used to diagnose problems, then diagnostic accuracy can be achieved, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system enables self-service automated diagnosis by having the test system automatically correlate probe data across protocol layers and generate diagnostic results without requiring manual analysis, thus reducing both time and labor while maintaining diagnostic accuracy
Solution Approach 2:
The patent replaces the mechanical process of manual packet capture analysis with an automated electronic system that uses probes to capture data and algorithms to correlate events across protocol layers, eliminating manual labor while preserving diagnostic capabilities
2Measurement precision
If probes are instantiated at multiple protocol layers to capture comprehensive event data, then event correlation accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the probing function across multiple protocol layers (application layer, transport layer, network layer, data link layer), with each layer having specialized probes that capture relevant events. This segmentation enables comprehensive event correlation while managing complexity through modular probe design
Solution Approach 2:
The probe system is designed with multi-functionality to operate across different protocol layers simultaneously, with a unified probe management mechanism that handles instantiation, data collection, and correlation across the entire protocol stack, reducing overall system complexity despite the multi-layer approach
3Adaptability or versatility
If dynamic probe instantiation is implemented to adapt to different testing scenarios, then testing versatility improves, but control mechanism complexity increases
Solution Approach 1:
The system implements dynamic probe instantiation where probes are created, configured, and activated based on the specific testing scenario and protocol layer being tested. This dynamic approach enables versatility across different test cases while the system manages control complexity through automated probe lifecycle management
Solution Approach 2:
The system uses feedback mechanisms where the test system monitors testing requirements and automatically adjusts probe instantiation and configuration accordingly. This feedback-driven approach enables adaptive testing versatility while reducing control complexity through automated decision-making
Data Source
AI summary
A method for EDA deep tracing and event correlation includes dynamically instantiating probes in a test system and an EDA emulator to capture data relating to events concerning processing or transmission of emulated data center traffic and/or traffic transmitted by the EDA emulator. The method further includes generating the emulated data center traffic, transmitting the emulated data center traffic to the EDA emulator, and receiving the traffic transmitted by the EDA emulator. The method further includes capturing, by the probes, data relating to the events concerning processing or transmission of the emulated data center traffic and/or the traffic transmitted by the EDA emulator, correlating the data, and outputting results of the correlating of the data.