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Introducing XSim: Achieving high-quality Photonic IC tape-outs

Introducing XSim: Achieving high-quality Photonic IC tape-outs
by jrobcary on 08-21-2024 at 10:00 am

txcorp XSim Example Photonics

Similar to analog circuits, which use EM waves at communications frequencies, components in photonics integrated circuits (PICs), which use EM waves at optical frequencies, are sensitive to layout and manufacturing variations—arguably more so.  Similar to their semiconductor counterparts, which transmit information using electrons, PICs transmit information using photons, and they also have to resolve signal integrity and parasitic losses. Designers of PIC components, therefore, have had to pioneer new design workflows. These workflows typically rely on FDTD EM engines that are computationally demanding, even for smaller components.

Currently, component designers have limited awareness of physical effects since they are limited to simulating extruded (as-drawn) GDS geometries, which under-represent important details of the as-manufactured PIC. As a result, they learn of the impact of physical effects like backscattering and parasitic interaction with other components much later, after prototype fabrication and during testing. This results in excessive design-of-experiments iterations and long loops of prototyping shuttle runs with their foundry partner, resulting in unpredictable timelines to market and a lack of flexibility to react to evolving requirements.

The solution to the problem requires industry cooperation and improvements in both computational hardware and software features and algorithms.  For computational hardware, Nvidia’s GPU and CUDATM programming language provide powerful new capabilities for solving large, difficult problems. On the simulation side, Tech-X has been doing very large physical simulations for national labs and large commercial customers on supercomputers for over two decades. But we also have recognized that most photonics IC design groups don’t have access to these resources, and modeling large manufacturing-realistic photonic component designs requires distributed computing across 100’s of CPU cores or 10s of CUDA GPUs, now accessible at larger companies or through Amazon Web Services.  In addition, we have been working with customers to understand the problems they face in achieving more accurate simulations and have built those capabilities into XSim, designed specifically to tackle computationally challenging manufacturing-aware photonic component design.

To highlight XSim capabilities:

  • STL or STEP input files or extruded GDS with optional roughness modeling to accurately describe 3D manufacturing features and sidewall roughness. The built-in Composer™ tool can also create 3D geometry.
  • User-defined or built-in materials properties, constant or variable-grid meshing, highly accurate dielectric algorithms,  mode solver/launcher, accurate S parameter calculations.
  • Efficient distributed computing across a large number of CPU cored or GPUs to resolve the critical dimension required for the simulation volume.
  • Efficient cloud hardware configuration set-up and access to AWS’s wide range of x86 and GPU cluster instances for those design groups who do not have access to on-premises workstations or clusters.

Come see how XSim can reduce prototyping cycles at our webinar on September 5th.  More information and webinar sign-up can be found at www.txcorp.com/xsimwebinar.

John Cary
Founder, CTO
Tech-X Corporation

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Podcast EP242: A View of the Dynamics and Future of the Memory Market with Jim Handy

Podcast EP242: A View of the Dynamics and Future of the Memory Market with Jim Handy
by Daniel Nenni on 08-21-2024 at 8:00 am

Dan is joined by Jim Handy of Objective Analysis. Jim is a 35-year semiconductor industry executive and like Dan, a leading industry analyst, speaker, and blogger. Following marketing and design positions at Intel, National Semiconductor, and Infineon, Jim became highly respected as an analyst for his technical depth, accurate forecasts, industry presence, and numerous market reports, articles, white papers, and quotes.

In this far-reaching and informative discussion, Jim explores the memory market with Dan. He explains the forces that define how new memory technologies displace existing approaches. Volume availability and cost drive a lot of those decisions. He points out that better technical approaches will see low adoption if the cost is much higher than existing technology for high volume applications such as cell phones.

Regarding new memory technologies, MRAM and ReRAM are discussed. Jim explains why he believes there will be room for only one new memory technology, He also discusses the challenges of using new materials and explores the specific reasons why embedded flash doesn’t scale,

Jim also discusses specific challenges in some markets, such as automotive, military and space.

The views, thoughts, and opinions expressed in these podcasts belong solely to the speaker, and not to the speaker’s employer, organization, committee or any other group or individual.


Synopsys IP Processor Summit 2024

Synopsys IP Processor Summit 2024
by Daniel Nenni on 08-21-2024 at 6:00 am

Synopsys Processor Summit

Now that live events are filling up there are even more live events especially here in Silicon Valley. Synopsys, the #1 full IP provider, will host a processor summit here in Santa Clara next month. Given the popularity of anything RISC-V, I would expect this event to be very well attended so be sure and register in advance.

The networking opportunities are always worth the time spent at live events but looking at the agenda I would say the content will be the big draw. Not to mention the excellent food provided by the Marriot, Synopsys events are very well catered, absolutely.

The keynote sets the tone for the summit which is a full day event. The speaker is Alexander Kocher, a 30+ year semiconductor professional with deep experience in the automotive industry. Currently, Alexander is the CEO of new comer Quantauris which has an impressive list of investors: Robert Bosch GmbH, Infineon Technologies AG, Nordic Semiconductor ASA, NXP® Semiconductors, and Qualcomm Technologies, Inc.

Keynote:

Enabling RISC-V Solutions for IoT & Automotive Applications
RISC-V is generating a high interest across multiple industries. In the software-defined era, system integrators are intrigued by the prospects of increased innovation, agility and customization, while cutting cost and reducing supply chain risks.Those opportunities led to the creation of Quintauris, founded to accelerate the adoption of RISC-V globally by enabling solutions for the Automotive and IoT industries. Quintauris will describe the benefits RISC-V offers to the automotive and IoT market segments, and how the organization will overcome perceived challenges around open standard semiconductor design by nurturing the broad RISC-V ecosystem and facilitating commercial adoption.

Synopsys IP Processor Summit 2024 Registration
September 5, 2024 9:00 a.m. – 6:30 p.m @ the Santa Clara Marriott

Conference Introduction:

As electronic systems continue to become more complex and integrate greater functionality, SoC developers are faced with the challenge of developing more powerful, yet more energy-efficient devices. The processors used in these applications must be efficient to deliver high levels of performance within limited power and silicon area budgets.

Why attend?

Join us for the Processor IP Summit to get in-depth information from industry leaders on the latest in ARC-V™ RISC-V processor IP, ARC® VPX DSP IP and ARC NPX NPU IP along with related hardware/software technologies that enable you to achieve PPA differentiation in your chip or system design. Synopsys experts, partners, and our processor IP user community will discuss electronic market trends and present on a range of topics including artificial intelligence, automotive safety, software development and more. Sessions will be followed by a networking reception where you can see live demos.

Who Should Attend?

Whether you are a developer of chips, systems or software, the Synopsys Processor IP Summit will give you practical information to help you create more differentiated products in the shortest amount of time.

Synopsys IP Processor Summit 2024 Registration
September 5, 2024 9:00 a.m. – 6:30 p.m @ the Santa Clara Marriott

About Synopsys

Catalyzing the era of pervasive intelligence, Synopsys, Inc. (Nasdaq: SNPS) delivers trusted and comprehensive silicon to systems design solutions, from electronic design automation to silicon IP and system verification and validation. We partner closely with semiconductor and systems customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow. Learn more at www.synopsys.com.

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The State of The Foundry Market Insights from the Q2-24 Results

The State of The Foundry Market Insights from the Q2-24 Results
by admin on 08-20-2024 at 10:00 am

TSMC Leads but Challengers Follow 2024

If you work in the Semiconductor or related industry, you know that industry cycles can profoundly impact your business. It is crucial for strategic development to invest at the appropriate time and to rope the sails when necessary.

As a semiconductor investor, you’re accustomed to the ebb and flow of industry cycles. It’s a reality that even the most stable long-term growth stocks must adapt to. But with the right understanding and preparation, you can predict and make informed investment decisions during these cycles.

My work aims to extract insights from the analysis of public data, insights that can be used to predict where the Semiconductor business is heading. While Semiconductor companies are different, these are the waters all semiconductor companies are navigating. Predicting a company’s business is different from predicting the stock price. The stock market has its logic, but eventually, it will align with the company’s underlying business.

One of the pivotal areas of the Semiconductor industry is the foundry market, which is dominated by TSMC. Born out of frustration with the American ability to compete effectively with the Japanese, the Taiwanese giant is unrivalled from an advanced logic perspective. TSMC always deserves a particular analysis in my research, but researching the entire foundry industry for insights is often valuable.

The development of the Foundry market impacts many companies. A survey from last week confirmed this:

Q2-24 Status of the foundry market.

It was another growth quarter for the foundry companies. Collectively, the industry grew by 10.2% QoQ and 19.6% YoY to $33.5B, which is still some distance from the last peak of $35.4B

TSMC’s dominance is undeniable, and as the current market situation is driven by AI’s need for leading-edge GPUs, it is no surprise that TSMC gained additional market share in Q2-24 although only marginal. The rest led by the Chinese foundries are matching the pace.

After some wobbling quarters, TSMC is now consistently increasing market share. TSMC’s market share has passed 62%, up from the latest low of 52% 10 quarters ago. This is likely to continue for the next few quarters as Intel and Samsung struggle to challenge TSMC’s leading-edge leadership.

The operating profit took a significant jump upwards and is completely dominated by TSMC. The AI leading edge boom is likely to benefit TSMC even more and it is obvious why TSMC is content even though Nvidia captures most of the value.

The increasing operating profit could indicate that we are entering shortage territory again soon, as it is only a couple of billion short of the record.

However, the collective inventory position of the Foundries shows that, in all likelihood, the industry is in balance and is not near the capacity maximum. A deeper dive into the numbers can uncover more insights

The deeper insights

The revenue from a technology perspective is moving at a rapid pace. More than half (SMIC excluded from this analysis) of the top 5 foundry revenue is at 7nm-3nm. That is up from just over a third, 2.5 years ago.

While not a problem yet, we are not far from a situation where it will become challenging to get mature technologies from Western companies.

The wafer fab capacity has increased significantly over the last cycle. For top 6 the combined capacity has grown by 11% CAGR, with SMIC leading the pack. With CapEx investments higher than revenue, the Chinese foundry was able to grow capacity by 29% CAGR since beginning of 2022.

The utilisation of capacity is on the rise for all major foundries, first and foremost the Chinese operations, while TSMCs have a more modest increase at the 80% range. In all likelihood TSMC have quite different loading of the different factories according to technology with pressure on 3nm.

Brick owners of the Semiconductor Industry

It is no secret that semiconductor manufacturing is expensive, which is why most semiconductor companies have chosen the fabless model, leaving the investments to the foundries.

While capacity levels give a good idea of the online capacity at a given time, they do not indicate future capacity. It is valuable to look at the companies’ balance sheets and the financial value of the manufacturing assets. Property, Plant, and Equipment are almost all manufacturing assets for semiconductor companies.

It is worth noting that manufacturing assets are allocated to the country of incorporation, so all of Intel’s PPE will register as US. Of course, reality is more complex so this cannot be used to evaluate the impact of the US chips act.

The PPE view shows that the financial value of the manufacturing assets is closing in on $550B. This is not only ready facturing but also land and construction in progress.

We divide the PPE into three categories to get a feel for the strength of the different manufacturing models:

IDM – Integrated Device Manufacturers manufacturing their own Chips

Foundry – Manufacturing for other IDMs and fabless companies

Mixed Manufacturing – Speciality fab owners that buy advanced logic from Foundries

The chart shows healthy growth, indicating more capacity will come online in the near term, but also a decline in growth in the last quarter. This signals that the investments from the last peak are coming to an end, and PPE growth will be slower.

The CapEx spend can be analysed to gain insight into the longer term future capacity.

It may seem a little bit counterintuitive, given all of the noise about the Chips Act, but CapEx investments are actually declining. It could be easy to interpret this as the Chips Act not working. However, a more likely answer is that the Chips Act changed the investment strategy of most of the large manufacturers to align with it, and investments will accelerate later.

The investment levels in each of the manufacturing types are well above the replacement capex, which represents the capex needed to maintain the same level of capacity.

Conclusion

It was a good quarter for the Foundry companies, particularly TSMC and the Chinese foundries. TSMC’s strong profitability shows that the company does not have to make concessions to keep and win business and is still miles ahead of Samsung.

While TSMC is still far from full capacity, the Chinese foundries are getting closer. As they have lost a significant proportion of their Western business, this is a sign that the Chinese electronics manufacturers are increasing their purchases.

The short-term capacity increase is likely to tail off, as indicated in the PPE development for both IDMs and foundries. This is a result of the last investment peak and the following CapEx pause.

The large gap between current CapEx and replacement CapEx will benefit the longer-term capacity. This has been somewhat delayed but will accelerate once TSMC starts filling its new factories. There will be sufficient capacity, but maybe not the right kind.

The dominance of TSMC will continue, but the Chinese Foundries are punching above their weight and will soon own a significant part of the mature technologies. TSMC will only make limited investments into these technologies and Western fabless companies will have to find a way back to the Chinese foundries without alienating the US government.

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Weebit Nano is at the Epicenter of the ReRAM Revolution

Weebit Nano is at the Epicenter of the ReRAM Revolution
by Mike Gianfagna on 08-20-2024 at 6:00 am

Weebit Nano is at the Epicenter of the ReRAM Revolution

It’s well known that flash is the embedded non-volatile memory (NVM) incumbent technology. As with many technologies, flash is bumping into limits such as power consumption, speed, endurance and cost. It is also not scalable below 28nm. This presents problems for applications such as AI inference engines that require embedded NVM, typically on a single SoC below 28nm. Resistive random-access memory, referred to as ReRAM or RRAM, is emerging as the preferred alternative to address these shortcomings. Weebit Nano is paving the way for this change. Dan Nenni provides a good overview of the company’s ReRAM technology in this DAC report.  The movement is gaining speed. In this post, I’ll review how things are coming together and how Weebit Nano is at the epicenter of the ReRAM revolution.

The Times Are Changing

At the recent TSMC Technology Symposium, there was a lot of discussion about ReRAM.  Indeed, the foundry market leader (who refers to it as RRAM) talked up the technology in its presentation on embedded NVM. The company shared that RRAM, non-volatile memory well formed between backend metal layers, is an excellent Flash replacement with good scalability.

According to the TSMC website, TSMC continues to explore novel RRAM material stacks and their density-driven integration, along with variability-aware circuit design and programing constructs to realize high-density embedded RRAM-based solution options for AIoT applications.

Tech Insights recently reported that Nordic Semi’s new Bluetooth 5.4 SoC has 12 Mb embedded ReRAM on board. The piece went on to say that with multiple resistive states, which can correspond to multiple memory states, ReRAM is a leading contender for machine learning designs. Nordic’s chip is fabricated in TSMC 22 nm ultra-low leakage (22ULL) with an embedded resistive random-access memory (eReRAM) process.

According to the Yole Group by 2028, the total embedded emerging non-volatile memory  market is expected to be worth ~$2.7 billion. Yole cited the first microcontroller product for automotive applications employing embedded RRAM from Infineon as an example of RRAM momentum. The Infineon AURIX TC4 MCU includes 20 MB of non-volatile resistive memory and is manufactured by TSMC in a 28nm process.

Another market research firm, Objective Analysis in its EMERGING MEMORIES BRANCH OUT report, states that over time, the NOR embedded in most SoCs will be almost entirely replaced by either MRAM, ReRAM, FRAM, or PCM.

This momentum isn’t limited to TSMC. On July 31 of this year, it was announced that Weebit Nano and DB HiTek tape-out ReRAM module in DB HiTek’s 130nm BCD process. It was reported that the demo chips will be used for testing and qualification ahead of customer production and demonstrate the performance and robustness of Weebit Nano’s ReRAM technology. And there’s more. Read on…

More From a Recent Memory Conference

Amir Regev

Embedded non-volatile memory technology isn’t the only thing experiencing change. Conference names are evolving as well. The Design Automation Conference is now DAC: The Chips to Systems Conference.  The Flash Memory Summit is now FMS: the Future of Memory and Storage. At that conference, which was held in Santa Clara from August 6-8, 2024, Weebit Nano’s VP of Quality and Reliability Amir Regev gave a presentation on emerging memories. During that presentation, Amir presented more evidence of the ReRAM revolution.

Amir presented test results for Weebit’s ReRAM technology implemented on GlobalFoundries 22FDX wafers. This is significant as this is the first time any public data has been shared about NVM performance at nodes such as 22nm.You can read the press release announcing this milestone here. In that release, it was reported that, Mr. Regev will also highlight the performance of Weebit ReRAM on GlobalFoundries 22FDX® wafers including endurance and retention data – the first such ReRAM results.

Here are some details that Amir presented:

  • Earlier this year Weebit received GF 22FDX wafers incorporating our ReRAM module prototype
    • 8Mb, 128-bit wide, targeting 10K cycles and 10yr retention at 105°C (automotive to follow)
    • Characterization and qualification activities are ongoing
  • Pre-qualification results show:
    • Weebit’s ReRAM stack is stable at 105°C cycling endurance up to 10K cycling
    • Very good data retention pre- and post-cycling is maintained for a long time at high temperatures (150°C), as shown in the figure below.
Hi Temp Cycling Results

Amir also provided a broad summary of Weebit’s qualification work:

  • Qualified modules at 85°C and 125°C
    • Temperatures specified for industrial and automotive grade 1 ICs
    • Qualified for endurance and 10yr retention per JEDEC industry standards
  • AEC-Q100 qualification (150°C and 100K cycles) in progress
    • Good results achieved, collecting statistical data for full qualification
  • Technology demonstrated on multiple process nodes
    • From 130nm to 22nm, Al / Cu, 200mm / 300mm
    • Successfully simulated on FinFET nodes

Amir also described the work underway to qualify Weebit’s ReRAM under extended automotive conditions. He mentioned the excellent results so far on temperature cycling provide a strong foundation for automotive qualification.

Weebit Nano’s ReRAM is finding application in a wide range of processes, foundries and applications. Beyond those mentioned so far, the company also recently announced work with Efabless on SkyWater’s 130nm CMOS (S130) process. This work enables fast and easy prototyping of intelligent devices using Weebit’s technology. Weebit Nano is creating a wide footprint in the market.

To Learn More

ReRAM technology is poised to change the game for many applications.  If your next project includes embedded non-volatile memory, you should see how Weebit Nano can help. You can learn more about the company’s technology here.  If you want to chat with the Weebit team, you can start here.  Weebit Nano is at the epicenter of the ReRAM revolution, join in.


What are Cloud Flight Plans? Cost-effective use of cloud resources for leading-edge semiconductor design

What are Cloud Flight Plans? Cost-effective use of cloud resources for leading-edge semiconductor design
by Christopher Clee on 08-19-2024 at 10:00 am

fig1 vpc

Embracing cloud computing is highly attractive for users of electronic design automation (EDA) tools and flows because of the productivity gains and time to market advantages that it can offer. For Siemens EDA customers engaged in designing large, cutting-edge chips at advanced nanometer scales, running Calibre® design stage and signoff verification in the cloud proves advantageous, as evidenced by the benchmark results discussed in this article. Calibre flows not only facilitate swift design iterations with modest compute resources but also consistently improve with each release. Cloud deployment offers a dual benefit: design teams avoid waiting for local resources and gain the flexibility to scale up during peak demand and leverage Calibre’s scalability for increased design throughput.

But to be cost-effective, cloud resources and infrastructure must be tailored to meet the individual and diverse demands of the many tools that constitute the semiconductor design flow. So what is the optimal configuration for running Calibre applications in the cloud? Which of the dozens of classes of virtual machines are best for running Calibre applications? How do cloud users know they are spending their money wisely and getting the best results? We set out to answer all these questions with a collaboration between Amazon Web Services (AWS), Amazon Annapurna Labs (Annapurna) and Siemens EDA to evaluate results from a series of Calibre flow benchmarks run inside Annapurna’s production virtual private cloud (VPC), which is hosted on AWS. After this evaluation, we developed a set of best known methods (BKMs) based on our experiences and the results.

Environment setup

The cloud experience works best when it is configured to be seamless from an end-user’s perspective. The setup that is probably most familiar to semiconductor designers in their on-premises systems is one where user has an exclusive small head node assigned that is used to submit all their jobs to other machines using some kind of queue manager. The head node is also useful for housekeeping purposes, like editing files, moving data, capturing metrics, etc.

The Calibre nmDRC benchmarks detailed in this paper took advantage of the Calibre MTFlex distributed processing mode running on a primary machine with a series of attached remote machines. In these cases, we used the same machine type for both the remote hosts and the primary. Other tests simply used multithreading on a single machine. A virtual private cloud setup is illustrated in figure 1.

Figure 1: VPN access from a VNC client to a dedicated head node, and then to primary and remote machines inside the cloud environment

Calibre nmDRC benchmark results

Figure 2 shows results for Calibre nmDRC runtime and peak remote memory usage for an Annapurna 7nm design when using an increasing number of remote cores. Runtime is shown in hours, and peak remote memory usage in GB. All runs used the Calibre MTflex distributed processing mode and a homogeneous cluster of machine types for the primary and remote nodes (AWS r6i.32xlarge instances). The horizontal axis shows the number of remote cores, which were doubled with each subsequent run. Each run used a consistent 64-core primary machine.

Figure 2. Calibre nmDRC runtime and peak remote memory with an increasing number of remote cores for the 7nm Annapurna design

The dark blue line is the baseline run using the same Calibre nmDRC version that Annapurna originally used in production on these designs with stock rules from their foundry partner. The light green line shows results using a more recent Calibre nmDRC version with optimized rules and instead of reading the data in from an OASIS file, the design data was restored from a previously saved reusable hierarchical database (RHDB) which in this case saved about 20 minutes per run. The light blue dotted line shows the percentage time saving between these two sets of runs. The purple line is the Calibre nmDRC Recon run, which automatically selects a subset of the foundry rules to run to find and resolve early design iteration systematic errors. Siemens EDA always recommends that customers run the Calibre nmDRC Recon tool on dirty designs before committing to a full Calibre run. This helps find the gross errors in the design very quickly, so they can be eliminated with short cycle times.

Determining how many remote cores to use in the cloud is dependent on the size and complexity of the design, the process technology, and the complexity of the rule deck. The optimal spot is found around the “knee” in the curve on these charts (for the design in figure 2, around 500 remote cores). The peak memory plots show that there was plenty of headroom for physical memory – each remote had 1TB RAM. The cost of these runs is typically in the range of a couple hundred dollars. Calibre customers typically use 500 remote cores as a minimum for full-chip Calibre nmDRC runs at advanced nodes. The data supports the Calibre value proposition of maintaining fast turnaround based on a modest amount of compute resource. However, the data also shows that scalability continues to even greater numbers of cores, giving Calibre users headroom to further compress cycle time if needed.

Figure 3 shows similar results for a Calibre nmDRC run on a 5nm Annapurna design. Here again, the optimal spot is around 500 remote cores, with fewer than 5 hours of runtime.

Figure 3. Calibre nmDRC runtime and peak remote memory with an increasing number of remote cores for a 5nm Annapurna design

Here again, the data demonstrates that the Calibre nmDRC tool is very resource-efficient, so it is not necessary to use thousands of remote CPUs to get reasonable design cycle times. Design teams can readily perform multiple turns per day using a modest number of cores, with a correspondingly modest associated cost. If it is helpful or necessary to squeeze in one or two more design turns per day, they can increase the number to 1,000 remote cores. The advantage of operating in the cloud is that more machines are always available, and it is highly likely that they will spin up very quickly.

Calibre interactive run management results

Both Annapurna designs were opened in the Calibre DESIGNrev interface, and the Calibre Interactive invocation GUI was used to initiate Calibre nmDRC and Calibre nmLVS runs. In addition, the Calibre Interactive integration with the Altair Accelerator (NC) queue manager was assessed, and Calibre RVE invocation and cross-probing to the design in the Calibre DESIGNrev interface was evaluated. All Calibre Interactive operations were fast and responsive.

Best known methods for EDA cloud computing

Following the benchmarks, we evaluated the results to encapsulate learnings and observations into suggested BKMs for running Calibre applications in the cloud. We generated general BKMs for optimizing spend in the cloud, improving cloud performance, and optimizing the general experience when using cloud-based resources, as well a specific BKMs for running Calibre flows in the cloud. These BKMs are encapsulated as Cloud Flight Plans, which are instructions for flow-specific optimizations that will allow Siemens EDA customers to leverage the availability, scalability and flexibility of cloud compute in a way that is very cost effective. Many of these resources are available through cloud landing pages on our Siemens EDA website. Our Cloud Reference Environment and other flow-specific assets and resources are available to our customers through our SupportCenter resource site.

Download our newest technical paper that describes BKMs for Amazon Web Services (AWS), using Annapurna Labs’ experience as a benchmark. Running Calibre solutions in the cloud: Best known methods.

Conclusion

In the realm of electronic design automation (EDA), cloud computing offers a compelling solution to the problem of constantly burgeoning design size and complexity. Design teams, armed with cloud-tuned machines, can work at an accelerated pace—launching jobs when needed, utilizing resources efficiently, and even running multiple tasks in parallel. Whether it’s accelerating design cycles or optimizing costs, the cloud provides flexibility. To navigate this celestial landscape effectively, understanding and optimizing cloud resources and configurations is key. Siemens EDA, in collaboration with major cloud providers like AWS, has crafted Cloud Flight Plans to guide design mutual customers on their cloud journey. With Cloud Flight Plans as their compass, semiconductor designers can chart a steady course toward efficient, cloud-powered success.

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AMAT Underwhelms- China & GM & ICAP Headwinds- AI is only Driver- Slow Recovery

AMAT Underwhelms- China & GM & ICAP Headwinds- AI is only Driver- Slow Recovery
by Robert Maire on 08-19-2024 at 6:00 am

One Trick Pony
  • AMAT reports good but underwhelming quarter
  • China slowing creates revenue & GM headwinds- ICAPs weak
  • AI remains the one and only bright spot in both foundry & memory
  • Cyclical recovery remains slow – Single digit Y/Y growth
OK quarter – still slow growing, revs up only 5% Y/Y

AMAT came in at revenues of $6.78B , up 5% Y/Y with EPS of $2.12. Guidance is for $6.93B+- $400M and EPS in a range of $2.00 to $2.36. Guidance was only slightly better than current estimates.

Given the standard “beat” versus true expected “whisper” numbers we would view the results as somewhat underwhelming and the after hours trading reflected that.

The recovery from the down cycle remains both slow and elusive

With revenues up only 5% year over year we are certainly not experiencing a “V” shaped recovery or a quick bounce back from the long downturn.

We have suggested many times that the recovery would be slow and arduous and the numbers we see underscore that view. As compared to previous downcycles that bounced back very quickly there are more headwinds and fewer tailwinds to drive the recovery.

AI is the “one trick pony” of the semiconductor recovery

The one and only bright spot of a luke warm recovery is clearly AI. Both in leading edge foundry (read that as TSMC as they are the sole makers of NVIDIA chips) and HBM memory which is the only bright spot in the overall lackluster memory market.

Although we are super bullish on all things AI, it will be difficult for semiconductor equipment makers to have a full scale cyclical recovery without other sectors improving as well.

NAND is still in the dumps and DRAM is really primarily HBM. In foundry logic its really just the leading edge and again primarily TSMC given Intel’s recent cut of capex spend

Running on two cylinders of TSMC & HBM , although strong, is not great for acceleration.

China slows significantly which also creates headwinds for gross margins

China is slowing from the mid 40’s percent to the mid thirties percent of business. This obviously creates a revenue challenge but more importantly creates a gross margin challenge as China customers have been paying significantly higher pricing (we pointed this out in our previous note about Chinese “sucker” customers).

This roughly 10% hit to equipment revenues and higher hit on gross margins adds to recovery headwinds.

Is ICAPs and trailing edge permanently slower?

Management also talked about some weakness in the ICAPs, trailing edge business and projections of mid single digit growth rates (not lighting things on fire)

Our view is that the industry went through a number of years of hyper growth in trailing edge equipment sales driven in large part by new and expanding trailing edge fabs in China and Asia to serve this significant market and now we are in an overcapacity situation such that there is clearly not enough need to buy new trailing edge tools.

The days of “unusual” hyper growth in trailing edge are over and will likely return to more modest numbers over the long run.

This trailing edge of the market has been especially good to Applied and without it being strong will be another significant headwind for the companies recovery.

The Stocks

Management demurred from making any projections about 2025 likely with good reason as things may not be quite as strong as some analysts were thinking/hoping.

Although Applied management used the word “strong” many times there were no numbers or projections to back that up so estimates of future growth may be getting toned down a bit.

As we saw with Lam when they reported last month we experienced numbers that were good but not “good enough” and the stock traded off.

Applied was up $10 during the day but gave back $5 in the aftermarket on what we viewed as a less than stellar quarter, guide and lack of long term projections.

In summary, AI is a great but only a singular driver while NAND, China, gross margins, ICAPs, the rest of DRAM, Intel capex all have headwinds.

We would consider taking some money off the table after the recent recovery in the semi sector from a negative overreaction that caused an overall market correction that we have more or less recovered from.

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About Semiconductor Advisors LLC

Semiconductor Advisors is an RIA (a Registered Investment Advisor),
specializing in technology companies with particular emphasis on semiconductor and semiconductor equipment companies. We have been covering the space longer and been involved with more transactions than any other financial professional in the space. We provide research, consulting and advisory services on strategic and financial matters to both industry participants as well as investors. We offer expert, intelligent, balanced research and advice. Our opinions are very direct and honest and offer an unbiased view as compared to other sources.

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Podcast EP241: A Look at Agile Analog IP with Chris Morrison

Podcast EP241: A Look at Agile Analog IP with Chris Morrison
by Daniel Nenni on 08-16-2024 at 10:00 am

Dan is joined by Chris Morrison, who has over 15 years of experience in delivering innovative analog, digital, power management and audio solutions for International electronics companies, and developing strong relationships with key partners across the semiconductor industry. Currently he is the Director of Product Marketing at Agile Analog, the customizable analog IP company. Previously he held engineering positions, including 10 years at Dialog Semiconductor.

Chris reviews the fist half of the year for Agile Analog with Dan. The conferences the company attended and the product traction achieved are discussed. Agile Analog enjoys strong market interest across a broad range of applications. The company is working with many of the leading foundries and attends those foundry events to connect with current and new customers.

Chris also discusses what’s in store at Agile Analog for the second half of the year. Collaboration with Globalfoundries becomes a key new addition for the second half. From a product perspective, Chris sees significant interest in the company’s reconfigurable data converters and power management IP.

There is also keen interest in analog IP at leading edge nodes, so this will also be a focus for the second half of the year.

The views, thoughts, and opinions expressed in these podcasts belong solely to the speaker, and not to the speaker’s employer, organization, committee or any other group or individual.


CEO Interview: Anders Storm of Sivers Semiconductors

CEO Interview: Anders Storm of Sivers Semiconductors
by Daniel Nenni on 08-16-2024 at 6:00 am

Anders Storm Sivers

Anders Storm is the CEO of Sivers Semiconductors. Under his almost decade-long leadership, the company has experienced significant growth, solidifying its position as a key player in the global semiconductor industry. With expertise in wifi communications, 5G, and photonics, he drives the company’s corporate strategy, product innovation, organisational excellence, and shareholder engagement.

Tell us about your company
Sivers is at the forefront of SATCOM, 5G, 6G, Photonics, and Silicon Photonics, pushing the boundaries of global communications and sensor technology. We have two business units – Photonics and Wireless – which provide advanced chips and modules essential for best in class gigabit wireless and optical networks. We serve a wide range of industries, from data and telecommunications, aerospace to defense, meeting the growing need for faster computation and better AI performance. By switching from electric to optical connections, we’re also helping to create a more sustainable future.

What problems are you solving?
We address several critical issues across various industries. Sivers enhances global connectivity and communication by advancing SATCOM, 5G, and 6G technologies, ensuring faster and more reliable networks. Our chips and modules for gigabit wireless and optical networks tackle the need for high-speed data transmission, crucial for applications such as video streaming and cloud computing. Additionally, Sivers supports the growing demand for high-performance computing and AI applications, enabling faster data processing and efficient machine learning models. Serving industries from telecommunications to aerospace, Sivers facilitates innovation and improvement in products and services, while helping companies future-proof their infrastructure and scale with technological advancements.

What application areas are your strongest?
Our newest Radio Frequency Module is a high-performance, high-power, wide bandwidth component designed for gigabit communication for example Fixed Wireless Access applications. It enables the creation of internet and data connections without the need for physical cables, making it ideal for providing wireless broadband to homes and businesses.

What keeps your customers up at night?
We find that our customers are most anxious about keeping up with the rapid pace of technological advancements in communications and sensor technologies, fearing that their current infrastructure might become obsolete and not sustainable long term. Similarly, the need to maintain a competitive edge in their respective industries by continuously innovating and integrating the latest technologies is a source of stress for our customers. In addition, the growing demand for higher data transmission speeds and computational power to support emerging applications like AI and machine learning may also weigh heavily on their minds.

What does the competitive landscape look like and how do you differentiate?
The growing demand for high-speed, reliable, and sustainable communication solutions across various industries puts pressure on companies to continuously innovate. Strategic partnerships and collaborations with tech companies, research institutions, and industry organizations are essential for staying competitive and expanding market reach in this rapidly evolving sector. Of course, the integration of AI into communication networks is increasingly crucial, as competitors use AI to optimize performance and enhance analytics.

What new features/technology are you working on?
Under a new contract with Blu Wireless, we are designing and developing advanced 5G long range antenna modules that operate within the 57-71 GHz license exempt band, providing high-speed broadband communication links for track-to-train applications. This is a new and exciting area for us as we seek to transform the way passengers and operators experience connectivity on the move. Another area is for AI clusters to connect GPUs with 16 terabit per second using photons rather than electrons, reducing power consumption by up to 90 percent.

How do customers normally engage with your company?
For customers requiring tailored solutions, Sivers engages in custom development contracts. These agreements outline the specific requirements and specifications for the custom product or solution, including performance metrics, timelines, and milestones. Such contracts often involve close collaboration between Sivers’ engineering teams and the customer’s technical staff, after that we deliver the chips or modules in volumes entering into long-term supply agreements to ensure a steady and reliable source of integrated chips, modules, and other critical components. It’s in this phase we are now transitioning into where we will go from 39% in second quarter 2024 in product sales, to over 80% in 2026. This is where we really will leverage our custom development contracts into the next phase of high growth.

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Emerging Memories Overview

Emerging Memories Overview
by Daniel Nenni on 08-15-2024 at 10:00 am

ReRAM History 2024

This year’s Future of Memory and Storage Conference (formerly the Flash Memory Summit) was again very well attended. The Santa Clara Convention Center is definitely the place to be for a Silicon Valley Conference.

This post is about the Emerging Memories session organized by Dave Eggleston. We will be covering other sessions but this was my #1. Having been in the embedded memory space for a good part of my career I know there is a serious Moore’s Law scaling problem and it will be interesting to see what new technology comes out on top.

Here is the session abstract:

In this session, we discuss emerging memories. Ultra-High Speed Photonic NAND FLASH technology revolutionizes memory operations by achieving ultra-high speeds with lower voltages and power consumption. This technology combines vertical NAND FLASH transistors with lasers/LEDs and photon sensors for efficient READ operations. ReRAM is now mainstream in applications such as automotive and edge AI due to its low power, scalability, and resilience to environmental conditions. We will explore the technology enhancements needed for wider adoption and the latest developments in advanced processes. ULTRARAM boasts exceptional properties like energy efficiency and extreme temperature tolerance, making it ideal for space and high-performance computing applications. We will highlight progress in fabrication processes and potential applications. Finally, we will discuss life beyond flash and the future of memory technologies like MRAM, ReRAM, PCM, and FRAM. Analysts will explore the impact on computer architectures, AI, and the memory market in the next 20 years, emphasizing the inevitability of transitioning to emerging memory types.

For me ReRAM is a top contender. Amir Regev, VP of Quality and Reliability at Weebit Nano presented:  ReRAM: Emerging Memory Goes Mainstream which was very interesting. Here is the abstract. Weebit also has a lot of information and instructional videos on their website which is quite good.

ReRAM today is being integrated as an embedded non-volatile memory (NVM) in a growing range of processes from 130nm down to 22nm and below for a range of applications: automotive, edge AI, MCUs, PMICs and others. It is low-power, low-cost, byte-addressable, scales to advanced nodes, and is highly resilient to a range of environmental conditions including extreme temperatures, ionizing radiation and electromagnetic fields. In this session, Weebit will discuss what technology enhancements are needed to proliferate ReRAM even further into applications with extended requirements. We will discuss the latest technical and commercial developments including data in advanced processes.

For those of you who don’t know Resistive Random Access Memory (RRAM or ReRAM) is a type of non-volatile memory that stores data by changing the resistance of a material. Unlike traditional memory technologies like DRAM or flash memory, which store data using charge. Amir reminded us that RERAM is not new and I do remember past RRAM discussions at some of the top semiconductor companies and certainly at TSMC.

Jim Handy also presented. Jim is one of the most respected embedded memory analysts and a blogger like myself. You can find him at https://thememoryguy.com/.

Here is Jim’s presentation abstract:

Flash memory has scaled beyond what was thought possible 20 years ago. Can this continue, or will an emerging memory technology like MRAM, ReRAM, PCM, or FRAM move in to replace it? Are there other memory technologies threatened with similar fates? What will the memory market look like in another 20 years? This talk will explain emerging memory technologies, the applications that have already adopted them in the marketplace, their impact on computer architectures and AI, the outlook for important near-term changes, and how economics dictate success or failure. Noted Analyst Jim Handy, and IEEE President Tom Coughlin will present the findings of their latest report as they discuss where emerging memories complement CXL, Chiplets, Processing In Memory, Endpoint AI, and wearables, and they explain the inevitability of a conversion from established technologies to new memory types.

I invited Jim to be a guest on our Semiconductor Insiders podcast to talk to him in more detail so stay tuned.

Bottom line: If you are currently researching embedded memory my advice is to look to the foundries. Foundry silicon reports do not lie.

Also Read:

Weebit Nano at the 2024 Design Automation Conference

Weebit Nano Brings ReRAM Benefits to the Automotive Market

ReRAM Integration in BCD Process Revolutionizes Power Management Semiconductor Design