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FP-RVVTS: Sail-guided Verification of RISC-V Floating-Point Implementations

A Sail-guided FP-RVVTS flow that uses Sail RISC-V as an executable RISC-V specification for differential verification of RISC-V Floating-Point (FP) implementations, from Instruction Set Simulator s to Register Transfer Level (RTL) designs.

Katharina Ruep, Manfred Schlägl, Daniel Grosse · 0 citations

Automated Generation of RISC-V Extensions with Formal Correctness Guarantees

Janus is presented, an LLM-assisted framework that synthe-sizes custom instructions integrated into the Ibex RISC-V core while keeping correctness outside the agent, demonstrating a practical path for using LLMs to explore ISA specialization without making the agent part of the trusted correctness boundary.

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Preprint Sep 2026

SIMT-Aware Lockstep Verification and Functional-Coverage Closure Methodology for an Open-Source RISC-V GPGPU: A UVM 1.2 Environment

A UVM 1.2 environment and methodology that wraps a bus-master SIMT DUT with role-inverted agents, integrates Vortex's functional simulator (SimX) as a per-configuration golden model over DPI-C, and renders verdicts via two injection-qualified checkers.

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SoK: ARCUS: On the Efficiency and Efficacy of Hardware Fuzzing

This work presents a comprehensive analysis of contemporary hardware fuzzing techniques applied across three major abstraction layers: Instruction Set Architecture (ISA), microarchitecture, and Register-Transfer Level (RTL). Our study examines key factors including input stimulus quality, mutation strategies, feedback...

Alenkruth Krishnan Murali, Raghul Saravanan, D. SaiManojP et al. · 1 citation
Preprint Aug 2026

LACE: Large Language Model Aided Multi-Agent Framework for Agile RISC-V Instruction Extension

LACE is presented, an LLM-aided multi-agent workflow that translates natural-language ISAX intents into a compact two-level IR, performs retrieval-guided localized RTL edits over large repositories, and closes the loop with a compiler-agnostic riscv-formal checking flow.

Pingqing Zheng, Jiayin Qin, Fuqi Zhang et al. · 0 citations
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Automated Estimation of MBIST Area and Test Time in Heterogeneous Memory IPs via Stacked Ensemble Framework

This study proposes a supervised learning framework that predicts MBIST area and test time directly from RTL-level design parameters without synthesis, which enables faster estimation of MBIST costs and supports more efficient design decisions in memory IP development.

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