#semiconductor software

[kamalkafir-blog]

US imposes new rules to curb semiconductor design software sales to China

[TECH AND FINANCIAL] It appears the Trump administration has imposed new export controls on chip design software as it seeks to further undermine China’s ability to make and use advanced AI chips. Siemens EDA, Cadence Design Systems and Synopsys all confirmed that they have received notices from the U.S. Commerce Department about new export controls on electronic automation design (EDA) software…

[apieinvestavimapaprastai]

Discover the Synopsys stock price forecast for 2025–2029, with insights into financial performance, AI-driven growth, and investment tips. #Synopsys #SNPS #SNPSstock #stockpriceforecast #EDAsoftware #semiconductorIP #AIchipdesign #stockinvestment #financialperformance #Ansysacquisition #sharebuyback

[impact-newswire]

Siemens Digital Industries Software to acquire Excellicon

Siemens to bring advanced timing constraint capabilities to EDA design flow with Excellicon acquisition Acquisition enables System-on-a-Chip (SoC) designers to accelerate design closure and enhance functional and structural constraint correctness with industry-proven timing constraints management May 19, 2025 – Siemens Digital Industries Software announced today that it has entered into an…

[bratthewurst]

Unforchie AI infringement is going to be impossible to prove. Any patents that relate to AI algorithms are going to be Beauregard claims, which are claims about how software works. Usually the only way to get the evidence of infringement is in discovery because companies dont publish their source code and reverse engineering that is very difficult and niche.

Finding the evidence in software cases is hard and its going to be even harder in AI since it is basically a black box. This is not going to kill AI or the companies sueing. But it will be interesting to see if the plaintiffs can convince the AI companies to take licenses.

[gwydionmisha]

Latest US clampdown on China's chips hits semiconductor toolmakers

[einnosyssecsgem]

SECS/GEM on JEOL JWS-7515 Metrology Equipment: Enhancing Efficiency with EIGEMBox

In the fast-paced world of semiconductor manufacturing, precision and efficiency are paramount. One key aspect of this process is the metrology equipment used to ensure that every component meets stringent quality standards. The JEOL JWS-7515 is a leading tool in this field, particularly when combined with the EIGEMBox, which facilitates the SECS/GEM protocol. In this blog, we’ll explore the significance of SECS/GEM, the features of the JEOL JWS-7515, and how the EIGEMBox enhances metrology processes.

What is SECS/GEM?

SECS/GEM stands for SEMI Equipment Communication Standard/Generic Equipment Model. It is a widely adopted communication protocol in the semiconductor manufacturing industry that allows for seamless data exchange between manufacturing equipment and host systems. This standard is critical for achieving automation and real-time data acquisition, which helps improve production efficiency and reduce errors.

Why SECS/GEM Matters

Standardization: By providing a uniform communication protocol, SECS/GEM simplifies the integration of various equipment and systems, leading to smoother operations.

Real-time Monitoring: With SECS/GEM, manufacturers can monitor equipment performance in real-time, allowing for quick adjustments and better decision-making.

Data Collection: The protocol facilitates extensive data collection, which is essential for analysis, reporting, and continuous improvement initiatives.

Overview of JEOL JWS-7515

The JEOL JWS-7515 is an advanced metrology tool designed for high-resolution imaging and analysis of semiconductor wafers. Here are some of its standout features:

High-Resolution Imaging

The JWS-7515 utilizes cutting-edge electron beam technology to achieve high-resolution imaging. This capability allows for detailed inspections of wafer surfaces, crucial for identifying defects that could compromise performance.

Versatility

This equipment is versatile enough to handle various materials and applications, making it an invaluable asset in a semiconductor fab. Its ability to analyze different substrates and feature sizes helps manufacturers maintain high standards across diverse product lines.

Automated Functionality

Automation is a key feature of the JWS-7515, which enhances throughput and minimizes human error. The system’s ability to integrate with software tools and other equipment makes it a central hub for metrology operations.

The Role of EIGEMBox

The EIGEMBox is a powerful tool that enhances the capabilities of the JEOL JWS-7515 by facilitating SECS/GEM communication. Here’s how it works:

Seamless Integration

The EIGEMBox acts as a bridge between the JEOL JWS-7515 and the host system, enabling seamless data transfer. This integration is crucial for manufacturers who require real-time insights into their metrology processes.

Enhanced Data Management

With the EIGEMBox, data collected by the JWS-7515 can be efficiently managed and analyzed. The ability to centralize data from multiple sources helps manufacturers streamline operations and improve decision-making.

Flexibility and Scalability

The EIGEMBox is designed to be flexible, accommodating a variety of equipment and systems. As manufacturing needs evolve, the EIGEMBox can be scaled to meet increased demands without significant infrastructure changes.

Benefits of Using SECS/GEM with JEOL JWS-7515 and EIGEMBox

Improved Efficiency

By automating data exchange and analysis, the combination of SECS/GEM, the JEOL JWS-7515, and the EIGEMBox significantly improves operational efficiency. Manufacturers can reduce downtime and optimize workflow, leading to faster production cycles.

Enhanced Quality Control

The ability to conduct real-time monitoring and analysis of wafer conditions ensures that quality control measures are always in place. This capability minimizes the risk of defects reaching the production stage, ultimately enhancing product reliability.

Data-Driven Decision Making

Access to comprehensive, real-time data allows manufacturers to make informed decisions quickly. This responsiveness is critical in a competitive landscape where even minor delays can have significant consequences.

Implementation Considerations

While the benefits of integrating SECS/GEM with the JEOL JWS-7515 and EIGEMBox are clear, several implementation considerations should be taken into account:

Training and Support

To fully leverage the capabilities of these technologies, manufacturers should invest in training for their staff. Understanding how to use the equipment and interpret data is essential for maximizing the benefits.

System Compatibility

Ensuring that the EIGEMBox is compatible with existing systems is crucial for a successful integration. Manufacturers should conduct thorough assessments before implementation to identify any potential challenges.

Ongoing Maintenance

Regular maintenance of both the JWS-7515 and the EIGEMBox is essential to maintain optimal performance. A proactive maintenance schedule can help prevent equipment failures and ensure long-term reliability.

Conclusion: Elevate Your Metrology Operations Today

The integration of SECS/GEM with the JEOL JWS-7515 metrology equipment, enhanced by the EIGEMBox, represents a significant advancement in semiconductor manufacturing. By improving efficiency, enhancing quality control, and enabling data-driven decision-making, this combination positions manufacturers for success in a highly competitive market.

If you're looking to elevate your metrology operations and embrace the future of semiconductor manufacturing, now is the time to act! Contact us today to learn more about how SECS/GEM, JEOL JWS-7515, and EIGEMBox can transform your processes. Don’t miss out on the opportunity to enhance your operational efficiency and product quality!

[uniqueeval]

Dell and Palantir to join S&P 500; shares of both jump

Alex Karp, CEO of Palantir Technologies, speaks at the World Economic Forum in Davos, Switzerland, Jan. 18, 2023. Arnd Wiegmann | Reuters Dell and Palantir both jumped about 7% in extended trading Friday after S&P Global announced that the companies would join the S&P 500 index. Software maker Palantir will take the place of American Airlines, and Dell is replacing Etsy, according to a…

[ujusttry]

Shocking 3 Reasons Why Nvidia Lost Its Crown as World's Most Valuable Company

Why Nvidia lost its crown as the world’s most valuable company is a story of rapid stock movement and market volatility. The semiconductor giant’s stock plummeted by 6.7% over two days, resulting in a $200 billion market value loss and positioning Apple and Microsoft ahead in market capitalization. Shocking 3 Reasons Why Nvidia Lost Its Crown1. Nvidia’s Meteoric Rise Made It Vulnerable to…

[jcmarchi]

Here Are The Nintendo Switch's Top 10 Best Selling Games

New Post has been published on https://thedigitalinsider.com/here-are-the-nintendo-switchs-top-10-best-selling-games/

Here Are The Nintendo Switch's Top 10 Best Selling Games

Updated story, 5/07/2024:

Nintendo has released its latest round of financial results, this time for the end of Fiscal Year 2024 (which ended in March). The Switch has surpassed 140 million units sold, further securing its place as the second-best-selling console in the company’s history, and Nintendo has also revealed it will announce the Switch successor by March 2025. 

Despite great numbers in this round of financial results, Switch software is down roughly 5% compared to the same time frame for Fiscal Year 2023. Nonetheless, its games are still selling well comparatively in the wider market. With the latest numbers on Switch software, here’s Nintendo’s most up-to-date list of its best-selling Switch games: 

Mario Kart 8 Deluxe: 61.97 million units

Animal Crossing: New Horizons: 45.36 million units

Super Smash Bros. Ultimate: 34.22 million units

The Legend of Zelda: Breath of the Wild: 31.85 million units

Super Mario Odyssey: 27.96 million units

Pokemon Sword and Shield: 26.27million units

Pokemon Scarlet and Violet: 24.92 million units 

Super Mario Party: 20.66 million units

The Legend of Zelda: Tears of the Kingdom: 20.61 million units

New Super Mario Bros. U Deluxe: 17.45 million units

The original story continues below…

Updated story, 5/09/23:

Nintendo has released its latest round of financial results, this time for the end of Fiscal Year 2023 (which ended in March). While the Switch has surpassed 125 million units sold, both hardware and software sales for the platform are down. 

Overall, hardware sales are down 22.1% while software sales are down 9%. 

With recent releases like Pokemon Scarlet and Violet, Splatoon 3, and more, here’s Nintendo most up-to-date list of its best-selling Switch games: 

Mario Kart 8 Deluxe: 53.79 million units

Animal Crossing: New Horizons: 42.21 million units

Super Smash Bros. Ultimate: 31.09 million units

The Legend of Zelda: Breath of the Wild: 29.81 million units

Pokemon Sword and Shield: 25.82 million units

Super Mario Odyssey: 25.76 million units

Pokemon Scarlet and Violet: 22.10 million units 

Super Mario Party: 19.14 million units

New Super Mario Bros. U Deluxe: 15.41 million units

Ring Fit Adventure: 15.38 million units

The original story continues below…

Original story, 8/03/22: 

Nintendo released its latest round of financial results, this time for Quarter 1 of the 2023 Fiscal Year, which accounts for April, May, and June of 2022. In it, the company revealed that the Switch surpassed 111 million units sold but, despite that, overall sales are down. 

In terms of hardware, sales are down 22.9%, with Nintendo citing the ongoing semiconductor shortage as why. Software sales are down too, declining 8.6% this quarter. However, while 8.6% is a sizeable drop, Nintendo still moved 41.41 million units in Q1 FY23. It also revealed its top 10 best-selling Switch games, with many having seen increases since the last round of financial results earlier this year. 

Here are the top 10 best-selling Nintendo Switch games as of June 2022: 

Mario Kart 8 Deluxe: 46.82 million 

Animal Crossing: New Horizons: 39.38 million

Super Smash Bros. Ultimate: 28.82 million

The Legend of Zelda: Breath of the Wild: 27.14 million

Pokemon Sword/Pokemon Shield: 24.50 million

Super Mario Odyssey: 23.93 million

Super Mario Party: 18.06 million

Pokemon Brilliant Diamond/Pokemon Shining Pearl: 14.79 million

Pokemon: Let’s Go, Pikachu!/Pokemon: Let’s Go, Eevee!: 14.66 million

Ring Fit Adventure: 14.54 million

Mario Kart 8 Deluxe had the biggest jump in this list, selling 1.48 million units this quarter. According to Nintendo, new 2022 releases are also selling well. Nintendo Switch Sports sold 4.84 million units, Mario Strikers: Battle League sold 1.91 million, and Kirby and the Forgotten Land sold 1.88 million units, making it the second-best selling Kirby game of all-time. 

For more, read about Nintendo’s latest financial results released earlier today and then check out this list of every NES, SNES, N64, and Sega Genesis game available on Nintendo Switch Online. After that, feast your eyes upon all the new Pokemon from Scarlet and Violet revealed in today’s Pokemon Presents showcase. 

Are there any Switch games on this list you haven’t played yet? Let us know which ones and why!

[govindhtech]

Electronic design automation (EDA) workloads: using IBM Cloud

A market sector known as Electronic design automation(EDA) is made up of hardware, software, and services that are used to help define, plan, design, implement, verify, and then manufacture semiconductor devices (or chips). Foundries or fabs that produce semiconductors are the main suppliers of this service.

EDA solutions are essential in three aspects even if they are not directly engaged in the production of chips:

To make sure the semiconductor manufacturing process produces the necessary performance and density, EDA tools are employed in its design and validation.

EDA tools are used to confirm that a design satisfies every criterion related to the manufacturing process. We call this area of study “design for manufacturability” (DFM).

The need to track the chip’s performance from the point of manufacture to field deployment is becoming more and more pressing. The term “silicon lifecycle management” (SLM) describes this third use.

EDA HPC environments are constantly expanding in size because to increased competition, the need to get products to market more quickly, and the growing demands for computers to handle the more fidelity simulations and modeling workloads. Businesses are trying to figure out how to effectively leverage technologies like hybrid cloud, accelerators, and containerization to obtain a competitive computing advantage.

The integrated circuit design and Electronic design automation software

In order to shape and validate state-of-the-art semiconductor chips, optimize their manufacturing processes, and guarantee that improvements in performance and density are reliably and consistently realized, Electronic design automation (EDA) software is essential.

For startups and small enterprises looking to enter this industry, the costs of purchasing and maintaining the computer environments, tools, and IT know-how required to use Electronic design automation tools pose a substantial obstacle. In addition, these expenses continue to be a major worry for well-established companies that use EDA designs. A key component of success is meeting deadlines, and chip designers and manufacturers are under tremendous pressure to introduce new chip generations with improved density, dependability, and efficiency.

Read more on Govindhtech.com

[phonemantra-blog]

Changes will be noticeable in the long term As Seekingalpha writes, new US rules on chip exports to China are unlikely to have much of a short-term impact on companies like Nvidia and AMD, but the long-term picture could be very different. Nvidia and ASML said the rules would have a minimal near-term impact on their results of operations. However, China accounts for up to 25% of Nvidia's data center sales, and its chips intended for the market, particularly the A800 and H800, are now on the banned list. Analysts believe AMD and Intel could also feel the impact. In the long term, some companies may experience a decline in revenue, which could limit investment. At the same time, the United States is trying to find a balance between allowing sales and protecting its interests. “The US government doesn't want to just say no to everything, but it does want to be able to control every transaction that it can,” said IDC Vice President Mario Morales. [caption id="attachment_72995" align="aligncenter" width="780"] Nvidia, AMD, and ASML[/caption] US sanctions against China threaten Nvidia, AMD and ASML Nvidia said it does not expect a significant impact in the short term: “We comply with all applicable regulations as we work to build products that support thousands of applications. Given global demand for our products, we do not expect a material impact on our financial results shortly.” ASML said it would need to carefully assess the implications: “It is our understanding that the new rules will apply to a limited number of facilities in China associated with advanced semiconductor manufacturing. These export control measures are likely to have an impact on the regional distribution of sales of our systems in the medium to long term.” UBS noted that China receives between 20% and 25% of its data center revenues: “All other things being equal, these new rules represent 7% to 10% of data center revenues (or ~6% to 8% of total revenues this year). year). The effect will be small in the short term, but it will have an impact in the long term.” US measures to limit the export of advanced chips with artificial intelligence (AI) technologies to China could open up huge opportunities for Huawei to import substitution in the domestic market, as we previously reported.

[apieinvestavimapaprastai]

Broadcom Inc.: The Ultimate Investment Opportunity in 2025

Explore Broadcom Inc.'s impressive financial performance, strategic market position, and consistent dividend policy. Learn why this tech #Stockpriceforecasting #Investmentinsights #Dividendpolicy #Marketanalysis #Techinvestments #Semiconductorsolutions

Broadcom Inc. is a global technology leader that designs, develops, and supplies semiconductor and infrastructure software solutions. The company’s operations are divided into two main segments: Continue reading Broadcom Inc.: The Ultimate Investment Opportunity in 2025

[impact-newswire]

Cadence to Acquire Secure-IC, a Leader in Embedded Security IP

Leading embedded security offerings will complement Cadence’s expanding IP portfolio, unlocking a growing multi-hundred-million incremental TAM opportunity Press Release – January 21, 2025 – SAN JOSE, Calif. – Cadence (Nasdaq: CDNS) today announced it has entered into a definitive agreement to acquire Secure-IC, a leading embedded security IP platform provider. The addition of Secure-IC’s talent…

[machine-saint]

licensing all my posts under the GPL from now on

GNU GENERAL PUBLIC LICENSE

Version 3, 29 June 2007

Copyright © 2007 Free Software Foundation, Inc. <https://fsf.org/>

Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.

Preamble

The GNU General Public License is a free, copyleft license for software and other kinds of works.

The licenses for most software and other practical works are designed to take away your freedom to share and change the works. By contrast, the GNU General Public License is intended to guarantee your freedom to share and change all versions of a program--to make sure it remains free software for all its users. We, the Free Software Foundation, use the GNU General Public License for most of our software; it applies also to any other work released this way by its authors. You can apply it to your programs, too.

When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for them if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs, and that you know you can do these things.

To protect your rights, we need to prevent others from denying you these rights or asking you to surrender the rights. Therefore, you have certain responsibilities if you distribute copies of the software, or if you modify it: responsibilities to respect the freedom of others.

For example, if you distribute copies of such a program, whether gratis or for a fee, you must pass on to the recipients the same freedoms that you received. You must make sure that they, too, receive or can get the source code. And you must show them these terms so they know their rights.

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Finally, every program is threatened constantly by software patents. States should not allow patents to restrict development and use of software on general-purpose computers, but in those that do, we wish to avoid the special danger that patents applied to a free program could make it effectively proprietary. To prevent this, the GPL assures that patents cannot be used to render the program non-free.

The precise terms and conditions for copying, distribution and modification follow.

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[mariacallous]

AI’s energy use already represents as much as 20 percent of global data-center power demand, research published Thursday in the journal Joule shows. That demand from AI, the research states, could double by the end of this year, comprising nearly half of all total data-center electricity consumption worldwide, excluding the electricity used for bitcoin mining.

The new research is published in a commentary by Alex de Vries-Gao, the founder of Digiconomist, a research company that evaluates the environmental impact of technology. De Vries-Gao started Digiconomist in the late 2010s to explore the impact of bitcoin mining, another extremely energy-intensive activity, would have on the environment. Looking at AI, he says, has grown more urgent over the past few years because of the widespread adoption of ChatGPT and other large language models that use massive amounts of energy. According to his research, worldwide AI energy demand is now set to surpass demand from bitcoin mining by the end of this year.

“The money that bitcoin miners had to get to where they are today is peanuts compared to the money that Google and Microsoft and all these big tech companies are pouring in [to AI],” he says. “This is just escalating a lot faster, and it’s a much bigger threat.”

The development of AI is already having an impact on Big Tech’s climate goals. Tech giants have acknowledged in recent sustainability reports that AI is largely responsible for driving up their energy use. Google’s greenhouse gas emissions, for instance, have increased 48 percent since 2019, complicating the company’s goals of reaching net zero by 2030.

“As we further integrate AI into our products, reducing emissions may be challenging due to increasing energy demands from the greater intensity of AI compute,” Google’s 2024 sustainability report reads.

Last month, the International Energy Agency released a report finding that data centers made up 1.5 percent of global energy use in 2024—around 415 terrawatt-hours, a little less than the yearly energy demand of Saudi Arabia. This number is only set to get bigger: Data centers’ electricity consumption has grown four times faster than overall consumption in recent years, while the amount of investment in data centers has nearly doubled since 2022, driven largely by massive expansions to account for new AI capacity. Overall, the IEA predicted that data center electricity consumption will grow to more than 900 TWh by the end of the decade.

But there’s still a lot of unknowns about the share that AI, specifically, takes up in that current configuration of electricity use by data centers. Data centers power a variety of services—like hosting cloud services and providing online infrastructure—that aren’t necessarily linked to the energy-intensive activities of AI. Tech companies, meanwhile, largely keep the energy expenditure of their software and hardware private.

Some attempts to quantify AI’s energy consumption have started from the user side: calculating the amount of electricity that goes into a single ChatGPT search, for instance. De Vries-Gao decided to look, instead, at the supply chain, starting from the production side to get a more global picture.

The high computing demands of AI, De Vries-Gao says, creates a natural “bottleneck” in the current global supply chain around AI hardware, particularly around the Taiwan Semiconductor Manufacturing Company (TSMC), the undisputed leader in producing key hardware that can handle these needs. Companies like Nvidia outsource the production of their chips to TSMC, which also produces chips for other companies like Google and AMD. (Both TSMC and Nvidia declined to comment for this article.)

De Vries-Gao used analyst estimates, earnings call transcripts, and device details to put together an approximate estimate of TSMC’s production capacity. He then looked at publicly available electricity consumption profiles of AI hardware and estimates on utilization rates of that hardware—which can vary based on what it’s being used for—to arrive at a rough figure of just how much of global data-center demand is taken up by AI. De Vries-Gao calculates that without increased production, AI will consume up to 82 terrawatt-hours of electricity this year—roughly around the same as the annual electricity consumption of a country like Switzerland. If production capacity for AI hardware doubles this year, as analysts have projected it will, demand could increase at a similar rate, representing almost half of all data center demand by the end of the year.

Despite the amount of publicly available information used in the paper, a lot of what De Vries-Gao is doing is peering into a black box: We simply don’t know certain factors that affect AI’s energy consumption, like the utilization rates of every piece of AI hardware in the world or what machine learning activities they’re being used for, let alone how the industry might develop in the future.

Sasha Luccioni, an AI and energy researcher and the climate lead at open-source machine-learning platform Hugging Face, cautioned about leaning too hard on some of the conclusions of the new paper, given the amount of unknowns at play. Luccioni, who was not involved in this research, says that when it comes to truly calculating AI’s energy use, disclosure from tech giants is crucial.

“It’s because we don’t have the information that [researchers] have to do this,” she says. “That’s why the error bar is so huge.”

And tech companies do keep this information. In 2022, Google published a paper on machine learning and electricity use, noting that machine learning was “10%–15% of Google’s total energy use” from 2019 to 2021, and predicted that with best practices, “by 2030 total carbon emissions from training will reduce.” However, since that paper—which was released before Google Gemini’s debut in 2023—Google has not provided any more detailed information about how much electricity ML uses. (Google declined to comment for this story.)

“You really have to deep-dive into the semiconductor supply chain to be able to make any sensible statement about the energy demand of AI,” De Vries-Gao says. “If these big tech companies were just publishing the same information that Google was publishing three years ago, we would have a pretty good indicator” of AI’s energy use.

[einnosyssecsgem]

What is SECS/GEM? Understanding the SEMI Equipment Communications Standard/Generic Equipment Model