Shifting Mindsets: Static Verification Transforms SoC Design at RT Level
Pranav Ashar, CTO, Real Intent Inc.
EETimes (3/6/2015 08:29 AM EST)
Teams 'shift left' to tackle challenges earlier in the design flow, says CTO of Real Intent, an EDA software design tools company.
We are at the dawn of a new age of digital verification for SoCs. A fundamental change is underway. We are moving away from a tool and technology approach — “I have a hammer, where are some nails?” — and toward a verification-objective mindset for design sign-off, such as “Does my design achieve reset in two cycles?”
Objective-driven verification at the RT level now is being accomplished using static-verification technologies. Static verification comprises deep semantic analysis (DSA) and formal methods. DSA is about understanding the purpose and intent of logic, flip-flops, state machines, etc. in a design, in the context of the verification objective being addressed. When this understanding is at the core of an EDA tool set, a major part of the sign-off process happens before the use or need of formal analysis.
To read the full article, click here
Related Semiconductor IP
- USB 4.0 V2 PHY - 4TX/2RX, TSMC N3P , North/South Poly Orientation
- FH-OFDM Modem
- NFC wireless interface supporting ISO14443 A and B with EEPROM on SMIC 180nm
- PQC CRYSTALS core for accelerating NIST FIPS 202 FIPS 203 and FIPS 204
- USB Full Speed Transceiver
Related White Papers
- BIST Verification at SoC level
- Creating IP level test cases which can be reused at SoC level
- Agile Verification for SoC Design
- A Survey on SoC Security Verification Methods at the Pre-silicon Stage
Latest White Papers
- FastPath: A Hybrid Approach for Efficient Hardware Security Verification
- Automotive IP-Cores: Evolution and Future Perspectives
- TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs
- How a Standardized Approach Can Accelerate Development of Safety and Security in Automotive Imaging Systems
- SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models