Formal and integrity verification specialist OneSpin will present a poster and deliver a technical workshop during DVCon China, as well as exhibiting at Booth #107. This year’s Chinese edition takes place April 17 at the Crowne Plaza Hotel in Century City Shanghai.
Time flies and the OneSpin’s Holiday Puzzle tradition has reached its third year. In December 2016, OneSpin challenged engineers everywhere to solve the Einstein riddle using assertions and a formal verification tool. In December 2017, the challenge was to model the hardest Sudoku in the world using assertions and find a solution with a formal tool. In addition, participants had to prove that the solution was unique and something impossible to do with simulation.
Will the separation of hardware and software for AI cause problems and how will hardware platforms for AI influence algorithm development?
Semiconductor Engineering sat down to discuss the role that EDA has in automating artificial intelligence and machine learning with Doug Letcher, president and CEO of Metrics; Daniel Hansson, CEO of Verifyter; Harry Foster, chief scientist verification for Mentor, a Siemens Business; Larry Melling, product management director for Cadence; Manish Pandey, Synopsys fellow; and Raik Brinkmann, CEO of OneSpin Solutions. What follows are excerpts of that conversation.
By Ann Steffora Mutschler, Semiconductor Engineering
Different ways of collecting, analyzing and applying that data to improve efficiency and reliability.
Just about every step of the IC tool flow generates some amount of data. But certain steps generate a mind-boggling amount of data, not all of which is of equal value. The challenge is figuring out what’s important for which parts of the design flow. That determines what to extract and loop back to engineers, and when that needs to be done in order to improve the reliability of increasingly complex chips and reduce the overall time to tapeout.
The race to build chips with a multitude of different processing elements and memories is making it more difficult to design, verify and test these devices, particularly when AI and leading-edge manufacturing processes are involved.
RISC-V is hot and stands at the beginning of what may be a major shift in the industry. Even a cursory review of upcoming conferences programs and recent technical articles makes that clear. While it is still early in the evolution of the processor architecture, there is certainly the potential that RISC-V will be a game-changer in the IP and semiconductor industry. As “a free and open ISA enabling a new era of processor innovation through open standard collaboration,” it directly challenges several well-established processor families. This definition comes from the RISC-V Foundation, which assumed support and evolution of RISC-V after the original development in the EECS Department at the University of California, Berkeley.
The open-source RISC-V instruction set architecture (ISA) continues to gain momentum, but the flexibility of RISC-V creates a problem—how do you know if a RISC-V implementation fits basic standards and can play well with other implementations so they all can run the same ecosystem? In addition, how do you ensure that ecosystem development works for all implementations and that all cores that claim to be RISC-V have implemented the specification correctly?
Debug consumes more time than any other aspect of the chip design and verification process, and it adds uncertainty and risk to semiconductor development because there are always lingering questions about whether enough bugs were caught in the allotted amount of time.