Instruction Stream Retrograding for Broader Random Test Coverage
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Solution Overview
Problem
Existing random test generation systems for hardware design verification often fail to effectively enhance the robustness of the testing environment, particularly in pre-silicon verification testing, due to limitations in generating instruction streams that adequately cover all potential bug scenarios and microarchitectural features.
Innovation Solution
A system and method for retrograding an instruction stream by inserting placeholder instructions, identifying benefiting instructions, and replacing them with retrograding instructions that influence the benefiting instructions, enhancing the test generation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If random test generation is used to make the testing environment more robust, then the reliability of verification testing is improved, but the ability to adequately cover all potential bug scenarios and microarchitectural features deteriorates
Solution Approach 1:
The system performs preliminary analysis of the instruction stream to identify benefiting instructions before generating the test case. Placeholder instructions are positioned in advance at locations where retrograding instructions will enhance the coverage of specific microarchitectural features or bug scenarios, ensuring that the random test generation is strategically guided rather than purely random.
Solution Approach 2:
The system introduces an intermediary analysis layer between random test generation and execution. This intermediary identifies benefiting instructions and determines optimal placeholder positions, acting as a mediator that guides the random test generation to achieve better coverage of microarchitectural features while maintaining the robustness benefits of randomization.
2Adaptability or versatility
If placeholder instructions are inserted and replaced with retrograding instructions, then the coverage of microarchitectural features is improved, but the complexity of the test generation process increases
Solution Approach 1:
The test generation process is segmented into distinct phases: analyzing the instruction stream to identify benefiting instructions, positioning placeholder instructions at strategic locations, and replacing placeholders with retrograding instructions. This segmentation makes the complex process more manageable and systematic, reducing the perceived complexity while improving microarchitectural feature coverage.
Solution Approach 2:
The system changes the parameters of the test generation process by introducing placeholder instructions as intermediate elements and systematically replacing them with retrograding instructions. This parameter change transforms the approach from direct random generation to a two-stage process that achieves better coverage with controlled complexity.
3Reliability
If retrograding instructions are used to influence benefiting instructions, then the completeness of verification is improved, but the time required for test generation increases
Solution Approach 1:
The system performs preliminary identification of benefiting instructions and strategic positioning of placeholder instructions before the actual test execution. This preliminary action reduces the time required during test generation by pre-planning the retrograding instruction placements, ensuring that completeness of verification is achieved without excessive time overhead.
Data Source
AI summary
A computer system, computer readable storage medium, and computer-implemented method for retrograding an instruction stream to enhance random test generation. The method includes generating a test case for a design-under-test (DUT) comprising positioning one or more placeholder instructions in the test case. The method also includes identifying one or more benefiting instructions. The method further includes executing the test case by replacing the one or more placeholder instructions with one or more respective retrograding instructions. The one or more retrograding instructions influence the one or more benefiting instructions.