CI/CD Infrastructure

Concept

CI/CD Infrastructure, in the cited RISC-V vector accelerator verification work, refers to the automated testing, regression, coverage-collection, and error-reporting infrastructure used to maintain RTL and verification code health. The implementation was built around Jenkins pipelines, RISCV-DV random test generation, regression selection, GitLab-based version control and issue tracking, and nightly/weekly regression runs.

First seen 5/27/2026

Last seen 6/1/2026

Evidence 4 chunks

Wiki v1

WIKI

Overview

In the context of Functional Verification of a RISC-V Vector Accelerator, CI/CD Infrastructure denotes the automation layer used to generate tests, run simulations, classify failures, collect coverage, and gate changes to the device-under-test (DUT) RTL and verification environment. The paper describes it as part of an industrial-grade verification effort for a RISC-V vector accelerator and reports that the overall automated constrained-random generation, simulation, error reporting, and CI/CD infrastructure helped find 3005 errors and reach 95.79% functional coverage. [c1]

Although the paper uses the term CI/CD infrastructure, the detailed implementation described in the evidence focuses primarily on continuous-integration activities: automated test generation, execution, regression selection, coverage collection, and pre-merge/periodic regression execution. [c2]

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NEIGHBORHOOD

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RELATIONSHIPS

8 connections

regression suite uses → 97% 4e

The CI/CD infrastructure uses a regression suite to verify correctness on RTL changes.

Functional Verification of a RISC-V Vector Accelerator ← uses 99% 4e

CI/CD infrastructure is used to automate simulation, test generation, and error reporting.

riscv-dv uses → 98% 3e

The CI/CD infrastructure uses RISCV-DV to generate random tests in its pipelines.

GitLab ← part of 95% 1e

GitLab is part of the CI/CD infrastructure for version control and issue tracking

Jenkins uses → 97% 1e

Jenkins is used as the CI server to implement the CI/CD infrastructure.

Code Coverage uses → 96% 1e

The CI/CD infrastructure collects code coverage metrics from simulations.

GitLab uses → 99% 1e

The CI/CD infrastructure uses GitLab for version control and issue tracking.

Jenkins ← implements 99% 1e

Jenkins is the CI server used to implement the CI/CD infrastructure

LINKED ENTITIES

4 links

Functional Verification of a RISC-V Vector Accelerator USES Extracted graph relationship

Jenkins IMPLEMENTS Extracted graph relationship

GitLab PART_OF Extracted graph relationship

riscv-dv USES Extracted graph relationship

CITATIONS

10 sources

10 citations — click to expand

[1] The paper's verification infrastructure included automated constrained-random test generation, simulation, error reporting, and CI/CD infrastructure, and the overall process found 3005 errors and reached 95.79% functional coverage. Functional Verification of a RISC-V Vector Accelerator

[2] The described CI/CD implementation focuses on CI activities including test generation, execution, regression selection, coverage collection, and regression execution. Functional Verification of a RISC-V Vector Accelerator

[3] The CI infrastructure was built using Jenkins. Functional Verification of a RISC-V Vector Accelerator

[4] GitLab was used for version control, issue tracking, and Wiki-based documentation of guides and tutorials. Functional Verification of a RISC-V Vector Accelerator

[5] The CI infrastructure included New tests, Retry, Selection, and Regressions pipelines; New tests used RISCV-DV, compiled the DUT, executed binaries, and classified passing and failing tests. Functional Verification of a RISC-V Vector Accelerator

[6] The Regressions pipeline executed a small regression set for merge-candidate DUT changes and ran a large regression set weekly. Functional Verification of a RISC-V Vector Accelerator

[7] Continuous integration generated and ran tests and collected coverage metrics, including functional coverage, assertion usage, and code coverage. Functional Verification of a RISC-V Vector Accelerator

[8] When errors were found, reproduction information such as the binary and faulty instruction was provided, active errors were summarized for debugging, and regressions were run before fixes were merged. Functional Verification of a RISC-V Vector Accelerator

[9] Nightly simulations ran 24 tests per night between April and July, then 50 tests per night from August to the end of November; each test contained approximately 500 vector instructions. Functional Verification of a RISC-V Vector Accelerator

[10] The CI infrastructure supported code health, maintainability, coverage closure, and enabled RTL and verification teams to test features and find errors. Functional Verification of a RISC-V Vector Accelerator