Verify Designs for Silicon Success with Conformal AI Studio

The Cadence Conformal AI Studio, which includes logical equivalence checking (LEC), automated functional engineering change order (ECO), and low-power static signoff products, both simplifies and accelerates the verification of complex SoC designs. It achieves this by leveraging re-architected scalable distributed core engines in concert with direct integrations to Cadence’s artificial intelligence (AI) and machine learning (ML) platforms.

For decades, Conformal technology has been a leader in the LEC subset of formal verification and remains the key auditor for ensuring digital implementation tools from both Cadence and third parties perform as intended. As designs have grown 100X in complexity over this timeframe, this task has intensified, and Cadence’s technology has evolved to meet design teams’ growing requirements.

Conformal AI Studio

Unlocking Design Success: Key AI Products for Enhanced Verification and Performance

Conformal AI Equivalence Conformal AI ECO Conformal AI Low Power
Conformal AIEquivalence ConformalAI ECO ConformalAI Low Power

Maximizing Verification Efficiency: Key Benefits of Conformal AI Studio

10X Verification Productivity

Up to 5X runtime improvement from fully distributed engines across LEC, CLP, ECO prove logical, low-power, and ECO equivalence to avoid costly redundant functional simulations

Robust Bug Detection

Leverage independent verification technology for fast and accurate identification of critical bugs throughout the design flow

Functional ECO Implementation

Automate both pre- and post-mask tactical ECO) to minimize manual intervention, ensuring faster tapeouts

Low-Power Signoff and Comparison

Detect low-power implementation errors early in the design cycle, reducing the risk of costly silicon re-spins

ML- Driven Optimizations

Tackle the most difficult formal equivalence tasks of abort resolution and ECO patch optimization by using reinforcement learning to explore and optimize the full proof space

AI- Driven Analysis Insights

Accelerate debug via equivalence-specific AI dashboards focused on identifying both single-run and multi-run cross-project trends

Conformal AI Studio: Enhanced Formal Verification Solutions for Complex Designs

Conformal AI Equivalence

Revolutionizing formal logical equivalence technology for rapid, precise implementation bug detection with AI integration

Cadence Conformal AI Equivalence elevates the verification of multi-million-gate designs by incorporating advanced AI algorithms. Boolean LEC engines allow for verification without the need for test vectors. It offers a comprehensive LEC solution enhanced by AI for validating SoC designs—from RTL to final LVS netlist (SPICE). This cutting-edge tool enables designers to tackle a wider range of circuits, including intricate arithmetic logic, complex datapaths, and custom transistor logic.

Key Benefits:

  • Exhaustively verify multi-million-gate SoC blocks significantly faster than traditional gate-level simulations
  • Reduces the risk of critical bug misses with independent verification of advanced datapath optimizations
  • Automates abort resolution by intelligently applying equivalence proofs using reinforcement learning
  • Supports the latest sequential optimization techniques used during RTL synthesis and place-and-route to ensure optimal design PPA
  • Ensures RTL models perform identically to their corresponding transistor circuits

Conformal AI ECO

Automates ECO generation with new Smart ECO flows and advanced AI for improved patch quality, runtime, and design convergence

Cadence Conformal AI ECO Designer automates the creation of functional ECOs for pre- and post-mask layout using formal LEC engines and integrated AI technologies. This approach replaces the complex and error-prone process of manual ECO implementation with a scalable and efficient solution that shrinks project schedules and ensures on-time tapeouts.

Modern ECOs can involve tens to hundreds of changes, from adding logic to optimizing routing. By leveraging AI and reinforcement-based machine learning, Conformal AI ECO can converge on an optimal patch an order of magnitude faster than a full implementation cycle or manual ECO process.

Key Benefits:

  • Enables fast tactical design changes by minimizing manual intervention and eliminating time-consuming full implementation iterations
  • Generates early estimates on ECO feasibility by quantifying designer intent
  • Generates complex ECOs that are typically not attempted manually
  • Up to 10X runtime speedup for a fully automated ECO process
  • Creates efficient place-and-route scripts to implement either pre- or post- mask ECOs leveraging spare gates, gate arrays, or freed logic
  • Automated Smart flow manages the setup of ECO patch-generation and related LEC runs using RTL-level insights
  • Reduces patch sizes by orders of magnitude for complex datapath ECOs found in leading-edge SoCs
  • Reinforcement learning intelligently applies multiple patch-generation algorithms to reduce patch sizes

Conformal AI Low Power

Fast and accurate validation of power- intent and low- power design structures in complex SoCs

This innovative product combines low-power equivalence checking with static structural and functional low-power verification. A next-generation distributed architecture and flexible hierarchical flow ensures the capacity to scale to multi-billion instance SoCs

Optimizing leading-edge hyperscaler and mobile SoCs for leakage and dynamic power helps designers reduce energy consumption and packaging costs. These advanced low-power design methods also complicate the verification task, introducing risk during synthesis and physical implementation. Conformal AI Low Power allows designers to create power-intent descriptions of their chip-level low-power architectures, then ensure implementation tools at each stage of the flow correctly insert and/or maintain that power intent in the required level shifters, domain shutoff, and isolation logic.

Key Benefits:

  • Low-Power-Aware LEC: Extends Boolean LEC proofs to consider architectural power intent
  • Static Power Signoff: Ensures implementation tools, such as synthesis and place-and-route insert, and maintains proper power structures throughout the design flow
  • Low-Power Compare: Fast, abstracted power-specific compare of two designs in various low-power contexts (PSTs, power intent, power crossings, etc.)
  • Scalable Distributed Signoff Architecture: Multi-threading and distributed processing, together with a hierarchical signoff methodology deliver up to 5X the TAT over prior generation and capacity to multi-billion-instance SoCs
  • Comprehensive Coverage: Reduces silicon respin risk with complete low-power verification coverage of the latest UPF specifications
  • Early Error Detection: Identifies low-power implementation errors early in the design cycle
  • Streamlined Debug: Identification and analysis of low-power design issues through a single unified cockpit for debugging power intent, RTL, logical netlist, and physical netlist power issues
  • Project history insights via AI-enabled dashboards
  • Simplified Power Intent Creation: Facilitates power intent authoring without requiring deep expertise and checks power intent in syntax, semantics, and design specification before implementation

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