2024 Outlook with Laura Long of Axiomise
Axiomise pioneered the adoption of formal verification in the semiconductor industry since 2017. Led by visionary CEO, Dr. Ashish Darbari, who has 63 patents in formal verification, and Neil Dunlop an industry veteran with 40 years of experience, Axiomise has helped twenty customers over the last six years by providing them access to bleeding-edge formal verification methodology via its training programs, consulting & services and vendor-neutral formal verification app for end-to-end verification of RISC-V processors.
Tell us a little bit about yourself and your company.
Axiomise provides consulting & services, training and application-specific apps for RISC-V verification such as formalISA for deploying formal methods on complex SoCs. Through our abstraction-driven methodologies and six-dimensional coverage solutions that can be used with any commercial formal verification tool, our experts can tackle the most challenging formal verification problems on a wide variety of designs including RISC-V, Arm, or x86 processors, GPUs or video blocks, networking blocks including Wi-Fi, 5G, and AI/ML.
I am the Business Development Director of the firm and joined the team in February last year.
What was the most exciting high point of 2023 for your company?
To read the full article, click here
Related Semiconductor IP
- Flexible Pixel Processor Video IP
- Bluetooth Low Energy 6.0 Digital IP
- MIPI SWI3S Manager Core IP
- Ultra-low power high dynamic range image sensor
- Neural Video Processor IP
Related Blogs
- 2024 Outlook with Chris Morrison of Agile Analog
- 2024 Outlook with Stephen Fairbanks of Certus Semiconductor
- ST-Ericsson (Part 3): Strategy And Outlook
- How Long Can Intel Stay No.1?
Latest Blogs
- Breaking the Silence: What Is SoundWire‑I3S and Why It Matters
- What It Will Take to Build a Resilient Automotive Compute Ecosystem
- The Blind Spot of Semiconductor IP Sales
- Scalable I/O Virtualization: A Deep Dive into PCIe’s Next Gen Virtualization
- UEC-LLR: The Future of Loss Recovery in Ethernet for AI and HPC