In-Field Hardware Telemetry Capture for FPGA Testing Throughput
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Solution Overview
Problem
Current hardware testing methods for integrated circuits (ICs) are inefficient and costly due to the complexity of modern FPGA designs, making exhaustive simulation and manual analysis of large data sets impractical, and there is a lack of architectural mechanisms for capturing and interpreting in-field telemetry data from deployed ICs without extensive manual efforts.
Innovation Solution
A framework is provided for configuring ICs to output a telemetry bit stream, using a software device driver to interpret and capture hardware telemetry data, which is then stored and aggregated across multiple devices for statistical analysis, allowing for wide-scale, in-field testing and hardware logic upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exhaustive simulation and manual analysis are used for hardware testing, then measurement precision is improved, but loss of time and productivity deteriorate significantly
Solution Approach 1:
The patent replaces manual analysis methods with automated software drivers that capture and interpret telemetry data from hardware components. This substitution of mechanical/manual processes with automated computational systems resolves the contradiction by maintaining testing accuracy while dramatically reducing the time required for analysis.
Solution Approach 2:
The hardware component is equipped with self-monitoring capabilities through embedded telemetry generators that automatically collect and output performance data. This self-service approach allows the hardware to provide its own testing data without requiring external manual intervention, thus improving efficiency while maintaining measurement precision.
2Manufacturing precision
If exhaustive simulation is performed for hardware testing, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces exhaustive simulation processes with automated in-field telemetry collection using software drivers. This substitution maintains design verification quality by capturing actual hardware performance data while significantly increasing testing throughput through parallel data collection from multiple deployed devices.
Solution Approach 2:
The patent shifts the testing dimension from pre-deployment laboratory simulation to post-deployment in-field observation. This dimensional change allows testing to occur in the actual operational environment, maintaining verification precision while enabling concurrent testing of numerous devices, thus improving productivity.
3Measurement precision
If manual interpretation of telemetry data is performed, then measurement precision is maintained, but ease of operation deteriorates
Solution Approach 1:
The patent replaces manual interpretation of telemetry data with automated software drivers that capture, parse, and aggregate hardware performance data. This automation maintains measurement precision through systematic data collection while dramatically improving ease of operation by eliminating burdensome manual analysis efforts.
4Adaptability or versatility
If in-field telemetry capture is implemented without architectural mechanisms, then adaptability is improved, but device complexity increases due to manual efforts
Solution Approach 1:
The patent implements a universal software driver architecture that can capture and interpret telemetry data from various hardware components through standardized interfaces. This universal approach enables in-field testing adaptability across different device types while reducing overall system complexity by providing a common framework rather than requiring custom manual procedures for each hardware type.
Data Source
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AI summary
A system for capturing hardware telemetry includes a hardware component encoded with hardware logic for emitting a telemetry stream into memory of a computing device. The system further includes a hardware component driver stored in the memory that is configured to parse the telemetry stream, populate telemetry structures defined within a telemetry event schema based on values parsed from the telemetry stream, and generate a telemetry record including the populated telemetry structures.