Parametric Propagators

Concept

Parametric propagators are a generic modeling approach for complex, domain-specific constraint propagators in constraint-based random stimuli generation for hardware verification. The cited evidence describes them as a response to propagators that take months to implement while hardware specifications can change on similar time scales.

First seen 5/26/2026

Last seen 5/26/2026

Evidence 1 chunks

Wiki v1

WIKI

Overview

Parametric propagators are described in the context of generic modeling for domain-specific constraint propagation in hardware-verification constraint satisfaction problems (CSPs). The motivating problem is that some constraint propagators are "extremely complex" and may require months to implement, while the hardware specification they encode can change on the same time scale.^[1]

Purpose

READ FULL ARTICLE →

NEIGHBORHOOD

No graph connections found for this entity yet. It may appear in future ingestion runs.

explore full graph →

RELATIONSHIPS

1 connections

Genesys PE ← uses 100% 1e

Genesys PE uses parametric propagators to generalize complex domain-specific constraints.

LINKED ENTITIES

2 links

Constraint Satisfaction Problem used_in_context_of The evidence places constraint propagators, huge domains, conditional problems, and MAC-style propagation within CSP variables and CSP sub-problems.

Genesys PE application_context The same source section reports application use and payoff for Genesys PE after describing AI features including parametric propagators, though the excerpt does not isolate parametric propagators' individual deployment details.

CITATIONS

5 sources

5 citations — click to expand

[1] Motivation for parametric propagators: some constraint propagators were extremely complex and could require months to implement, while hardware specifications could change on the same time scale. Constraint-Based Random Stimuli Generation for Hardware ... - AAAI

[2] Purpose of parametric propagators: the authors generalized complex domain-specific constraints and developed parametric propagators that were relatively simple to manipulate and change for design changes or next-generation designs. Constraint-Based Random Stimuli Generation for Hardware ... - AAAI

[3] Huge-domain CSP context: the source reports CSP variables such as address and data variables with domains on the order of 2^32 or larger, and says regular propagation methods relying on small domains are inadequate for pruning such spaces. Constraint-Based Random Stimuli Generation for Hardware ... - AAAI

[4] Conditional CSP context: the source describes conditional problems where variable assignments can make extensive parts of a CSP irrelevant, and reports extending MAC with assumption-based pruning to improve pruning under conditionality. Constraint-Based Random Stimuli Generation for Hardware ... - AAAI

[5] Genesys PE application setting: the source describes Genesys PE as a stimuli generator for processor and multi-processor verification and reports its use since 2000 as the major functional verification tool for IBM PowerPC processor designs. Constraint-Based Random Stimuli Generation for Hardware ... - AAAI