#AI and the Evolution of #EDA (OTC: $GTCH) (NASDAQ: $SNPS) (NASDAQ: $GOOG)
(NASDAQ: $CDNS) @gbtt_inc @Synopsys @Google @Cadence
September 26, 2023 - Investorideas.com (www.investorideas.com),
a global investor news source covering tech stocks releases a special news
report on how AI is the future evolution of Electronic Design Automation (EDA) tools,
featuring a tech innovator building a growing IP portfolio in the sector, GBT
Technologies Inc. (OTC PINK:GTCH).
Read this in full at https://www.investorideas.com/news/2023/technology/09261AI-Electronic-Design-Automation.asp
According to allaboutcircuits.com,”For years,
EDA companies have claimed “artificial intelligence” features in their IC
design tools. In the past year, however, generative AI has undergone a dramatic
evolution with platforms like ChatGPT, causing some designers to question
whether previous EDA features still count as AI by today's standards.”
So what is the new standard for AI in EDA?
GBT Technologies Inc. (OTC PINK:GTCH) CTO, Danny Rittman, discussing the issue told Investor Ideas, “Indeed
the dominant EDA companies like Synopsis, Cadence, Siemens invested lots into
AI in the past decade, yet, the solutions that they provide are not sufficient
as the industry struggles to design microchips in an affordable time frames.
Projects are delayed, taking way longer than planned and there is a real need
for an AI breakthrough.”
Rittman recently published a paper on the topic titled,
‘A Qualitative Study that Explores the Implementation of Artificial
Intelligence in Integrated Circuit Design’ https://www.proquest.com/docview/2860456194
Excerpt: “Reports of the early stages of IC chips
designed by artificially intelligent aided by deep neural network learning have
appeared recently (Dinu & Ogrutan, 2019). Over the last decade, there has
been significant growth in the integration of AI technologies within Electronic
Design Automation (EDA) tools. AI has played a pivotal role in enhancing
various aspects of EDA, such as design automation, optimization, verification,
and physical design (Todorov & Dabral, 2020). Typical AI techniques used in
the EDA field include machine learning (ML), deep learning, genetic algorithms,
natural language processing (NLP), and reinforcement learning.”
Regarding its EDA technology, GBT Technologies Inc.
(OTC PINK:GTCH) recently announced it has received
a grant notification for its microchip’s reliability verification and
auto-correction EDA patent application, internal project’s code name, Epsilon.
The patent will be granted as U.S. Patent No. 11,763,062 on September 19, 2023.
GBT’s Epsilon patent application covers the innovative technology to address
advanced semiconductor node physics with the goal of ensuring a high level of
reliability, optimal thermal design, lower power consumption and high
performance. The described technology includes machine learning algorithms to
enable robust design, process optimization, characterization, modeling, and
simulation. The technology underlying the patent identifies reliability flaws,
describes the found issues, and allows an automatic correction of these
reliability issues early during the IC’s design phase. Machine Learning
techniques will be performing data analysis, identification, categorization,
and reasoning about executing the optimal IC layout automatic correction. The
technology aims to allow IC designers to analyze and fix circuits early during
the design phase in real time with the goal of creating higher efficiencies. GBT
plans to continue its R&D efforts in this domain, inventing modern
technologies and enabling reliable, low-power, high-performance,
next-generation microchips.
“We are excited to share that our Epsilon patent
has been granted. This patent aims to perform an early electrical and power
analysis of a microchip during the design phase. The goal is to identify
potential failures and provide solutions as early detection and elimination of
reliability issues can save a significant amount of time in engineering redesign.
The technology is planned to be powered by GBT's machine learning algorithms
for pattern recognition and vast data analysis, especially for advanced
manufacturing nodes like 3nm and below.
"Today's advanced nanometer nodes require
analysis and addressing of reliability parameters to mitigate risks of system
degradation, overheating and possible malfunctions. As IC's manufacturing nodes
are constantly scaling down, layout electrical characteristics analysis is
becoming a much more complex and time-consuming process, addressing challenging
physics phenomenon. Our Epsilon patent is an intelligent design productivity
enhancement EDA software solution that analyzes, detects, and eliminates
electrical reliability issues on-the-fly. Its goal is to enable chip designers
to keep their hands on the pulse of the entire microchip's reliability, power
management, thermal behavior and overall performance.
"Microchip reliability is a complex and
evolving field. As such, we plan to continue our ongoing research and
development efforts to address emerging challenges associated with shrinking
nanometer-scale technologies. Additionally, we plan to file a continuation for
this technology, with the goal of further broadening and protecting our
intellectual "property” stated Danny Rittman, the Company’s CTO.
Synopsys (Nasdaq:SNPS), a global
leader in electronic design automation (EDA) and semiconductor IP announced
earlier this month, the extension of its
Synopsys.ai™ full-stack EDA suite with a comprehensive AI-driven data analytics
continuum for every stage of integrated circuit (IC) chip development. The
Synopsys EDA Data Analytics solution is the first of its kind in the
semiconductor industry to provide AI-driven insight and optimization to drive
improvements across exploration, design, manufacturing, and testing processes.
The solution combines the latest advances in AI to curate and operationalize
magnitudes of heterogenous, multi-domain data to accelerate root-cause analysis
and achieve greater design productivity, manufacturing efficiency, and test
quality.
From the news: The AI-driven
Synopsys EDA Data Analytics (.da) solution includes:
Synopsys Design.da to perform deep analysis of data
from Synopsys.ai design execution, providing chip designers with comprehensive
visibility and actionable design insights to uncover power, performance, and
area (PPA) opportunities.
Synopsys Fab.da to store and analyze large streams
of fab equipment process control data that increase operational efficiencies
and maximize product quality and fab yield.
Synopsys Silicon.da to collect petabytes of silicon
monitor, diagnostic, and production test data from test equipment to improve
chip production metrics, such as quality, yield, and throughput and silicon
operation metrics, such as chip power and performance.
From the news: “As IC
complexity grows and market windows shrink, the semiconductor industry is
increasingly adopting artificial intelligence technologies to enhance the
quality of results (QoR), speed verification and testing, improve fab yield,
and boost productivity across multiple domains spanning the entire IC design
flow,” said Sanjay Bali, Vice President of Strategy and Product Management for
the EDA Group at Synopsys. “With the new data analytics capabilities within the
Synopsys.ai EDA suite, companies can now aggregate and leverage data across
every layer of the EDA stack from architecture exploration, design, test, and
manufacturing to drive improvements in PPA, yield, and engineering
productivity.”
Discussing this, allaboutcircuits.com said, “Synopsys
aims to keep pace with this accelerating field by unveiling a new extension to
its Synopsys.ai EDA suite. This announcement follows the release of Google’s (NASDAQ: GOOG) DeepMind,
which uses AI to accelerate its in-house chip designs. Both of these
announcements indicate how advanced machine learning algorithms are shaping IC
development and how they might be used as a tool for designers in such fields.”
Cadence Design Systems, Inc. (Nasdaq: CDNS), describing
its innovation in AI says, “The Cadence Joint Enterprise Data and AI (JedAI)
Platform is able to harness this rich lode of EDA data in an open, artificial
intelligence (AI)-driven, large-scale data analytics environment, allowing
engineering teams to visualize the data, uncover hidden data trends, and
automatically generate design improvement strategies leading to improved design
performance and engineering productivity.”
“With the Cadence JedAI Platform, Cadence unifies
its computational software innovations in data and AI across Verisium AI-Driven
Verification, Cadence Cerebrus Intelligent Chip Explorer’s AI-driven
implementation, and Optimality Intelligent System Explorer’s AI-driven system
analysis, enabling a generational shift from single-run, single-engine
algorithms in electronic design automation (EDA) to leveraging big data and AI
to optimize multiple runs of multiple engines across an entire SoC design and
verification flow.”
Electronic Design recently reported,
“Skilled engineers remain the driving force for innovation in chips. But it’s
no secret that electronic design automation (EDA) companies are folding AI into
more of their offerings to speed up design and verification.”
“But as industry insiders tell it, these AI-powered
EDA tools don’t have enough intelligence to actually replace human designers
anytime soon. Instead, the biggest difference these tools are having is on the
productivity front, with AI reducing the number of hours that engineers spend
on the more tedious phases of the design and verification process,” said Amit
Gupta, VP and GM of Siemens Digital Industries Software's custom IC
verification division.”
“Specifically, three main types of AI are becoming
prevalent in the world of EDA. The most mature are what he calls “adaptive AI,”
which enhances existing EDA processes to cut down on manual labor, and
“additive AI,” which learns over time to save engineers from repetitive work.
Further along on the roadmap is “assistive” AI. It can pinpoint weak points that
can negatively impact the chip design’s performance and then figure out the
root cause.”
For investors following the sector, the AI implementation
for EDA is still evolving and the next chapter will represent untapped
potential for those willing to bet on the revolution.
Investors following AI stocks can use the free AI
stock directory at Investor Ideas
https://www.investorideas.com/TSS/Stock_List.asp#Robotics
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