#AI and its Role in #EDA Tools – #Stocks to Watch (OTC: $GTCH) (NASDAQ:
$SNPS) (NASDAQ: $GOOG) (NASDAQ: $CDNS) @gbtt_inc @Synopsys @Google @Cadence
September 27, 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/09271AI-in-EDA-Tools.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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