semiconductor design

Azeez Bhavnagarwala, Metis’ founder and CEO, speaks about advanced CMOS Memory and Arithmetic component intellectual property (IP) to improve energy efficiency and performance of processors.

Anna Fontanelli, Monozukuri’s founder and CEO, is an expert in deep-submicron silicon technology and design tools shares her view on the state of Moore’s Law and challenges surrounding 2.5D integration, 3D chip stacking & advanced packaging, as well as the chip design industry’s startup environment.

As a leading analyst covering the electronic system design segment, Laurie Balch is well steeped in identifying and analyzing technology trends and forecasting new market opportunities. Laurie is now President and Research Director at Pedestal Research.

“Virtual platform environments that combine the verification capabilities of emulation with the pre-silicon functionality insights available through verification intellectual property (VIP) are an increasingly popular way to get designs verified ahead of the curve of new standards,” Browy says.

Machine learning (ML) and artificial intelligence (AI) have ushered in tremendous opportunities for faster growth, problem-solving and technological development in the electronic system design ecosystem. Cadence Design Systems, Inc., a member of the ESD Alliance, a SEMI Technology Community, is at the technological forefront in incorporating ML techniques in its chip design products. I spoke with Chin-Chi Teng, Senior Vice President and General Manager of Cadence’s Digital Signoff Group, about how ML is reshaping EDA and the semiconductor industry, the cloud’s role in the evolution of ML in design and its impact on Moore’s Law. Teng also offers advice on how engineering students can calibrate their education to prepare to work with this transformative technology and urges them to have fun in the process. Smith: How is ML changing the EDA industry? Teng: ML is changing EDA for the better in many ways. It’s more difficult than ever to design chips, and ML is helping by overcoming the complexity, size and technology interdependencies. At the same time, ML is helping our own engineers solve certain classes of EDA algorithm, tool, and flow/solution challenges so that we can deliver even better EDA tools to our user base. The benefits can include reducing runtime, increasing quality of results, and being better equipped to manage vast complexity and data. Also, and maybe even more significant, is the potential boost to user and team productivity, where engineers have more time to focus on high-value problems because they no longer need to spend time on managing overwhelming volumes of data and details that can be easily automated. Smith: What is the potential impact ML can have on semiconductor design? Teng: ML technology can be leveraged in several ways to improve EDA tool performance and engineering team productivity. For example, we initially applied ML to applications such as formal verification, simulation regressions, analog circuit design, and PCB design. We targeted ML toward specific algorithms that processed lots of data to sharpen and speed decision-making. Then we started to look at digital implementation flows that combine multiple steps with multiple decisions in a recipe, especially for chip implementation where the more efficient use of engineering knowledge can make a substantial difference in the chip’s resulting power, performance and area (PPA). These flows present more challenges and require different ML and optimization techniques since the data points are expensive to create and the volume of data is huge. But flow optimization offers the largest rewards for companies investing in data collection and analysis to improve their operations and product quality. By using ML to improve the implementation flow, our users are seeing up to 20% better PPA and 10x improved productivity in developing data center CPUs and AI engines, automotive sensor processing SoCs, and mobile devices. Smith: What is the cloud’s role in the evolution of ML in EDA? Teng: More ML usage means there will be an inevitable surge in compute demand resources, and engineers need the ability to scale in parallel. The cloud provides engineers with the best opportunity to scale computing resources without facing procurement limitations. The cloud also allows engineers to use task-specific compute and ML accelerators and capitalize on distributed computing innovations that leverage the cloud for greater design flexibility and availability. Smith: You have written that you see Moore’s Law accelerating. How does ML fit into this? Teng: We see the rapid adoption of new process technologies as the biggest trend surrounding Moore’s Law right now. ML technology in EDA will help speed tool certification processes, process design kit (PDK) development and other deliverables aimed at creating and improving customer support through all stages of the process lifecycle. This is a virtuous circle, and it’s expanding beyond hardware design and optimization to also include software. Today’s ML functionality works on the abstraction of register transfer level (RTL), optimizing the implementation and verification flows. ML will soon enable use of a higher abstraction of describing the target systems, exploring architectural options and optimizing across hardware and software partitioning. Smith: What advice would you give engineering students who are studying ML with the goal of becoming an electrical engineer? Teng: With the rapid pace of technology development, things are changing constantly. I’d absolutely encourage students to look at ML because ML isn’t going away — its growth is only going to accelerate from here. I’d also suggest that students look more broadly at computational mathematics because that’s foundational for ML. There are many, many opportunities to apply ML to real-world applications that will make a significant impact when it comes to optimizing computational software. Most important, students should explore and have fun while doing it. About Chin-Chi Teng Chin-Chi Teng has served as Senior Vice President and General Manager of the Digital and Signoff Group (DSG) since 2018. Prior to this role, Teng held senior leadership positions in research and development in digital implementation. Teng joined Cadence in 2002 via the acquisition of Silicon Perspective Corporation and subsequently led various research and development groups. He brought deep technical knowledge and more than 20 years of industry and academic experience to his role as leader of the IC Digital group. Teng holds a BS in electrical engineering from the National Taiwan University and an MS and Ph.D. in electrical and computer engineering from the University of Illinois at Urbana-Champaign. He holds seven patents and has written many EDA papers, several deep learning papers, and the book Electrothermal Analysis of VLSI Systems. Robert (Bob) Smith is executive director of the ESD Alliance, a SEMI Technology Community.

Three-dimensional integrated circuits (3D-ICs) are revolutionizing the semiconductor industry. Manufactured by stacking and interconnecting dies so they perform as a single device, 3D-ICs deliver more capabilities by offering higher performance and bandwidth — while also reducing power consumption, package size and costs. However, 3D-ICs present tough design challenges to engineers. Significantly larger than a single-chip system on a chip (SoC), these assemblies have more components, more integration points and longer interconnects, that translate to new risks for high-frequency signal failure, reliability, and other performance issues such as thermal buildup. As the lines between silicon and system continue to blur, engineers must conduct concurrent, multivariate analysis to assess every possible failure mode ― not only at the component level, but also across the entire 3D-IC assembly ― a technical obstacle for many development teams accustomed to applying a series of single-physics engineering simulation tools in a sequential approach. 3D-ICs are assembled in a complex package using a serial analysis approach that doesn’t take into account system-level interactions, as well as the many thousands of bump connection points where something can go wrong. By contrast, concurrent, multivariate simulation and analysis takes into account all physics simultaneously from the earliest prototyping stages of design. Most semiconductor development teams not only lack the technical tools to perform this complex simulation and analysis, but they also face cultural obstacles as they undertake system-level analysis. Diverse teams working with disparate tools simply aren’t equipped to perform seamless handoffs and collaborate effectively on a complex 3D IC design from an early stage. Instead, they scramble to address system-level issues later when launch delays are likely, the cost of rework is high and their positive contributions to the design are diminished. The Value of a True Multiphysics, Multivariate Approach As market demand for 3D-ICs increases, semiconductor development teams need a single simulation platform that enables simultaneous multiphysics analysis — including power integrity, reliability, electromagnetics (EM), thermal, computational fluid dynamics (CFD) and mechanical studies ― across the entire assembly. A unified simulation platform that brings together best-in-class solutions for every physics enables semiconductor engineers to collaborate across functions, seamlessly hand off analysis tasks between engines, and partner to optimize 3D-IC designs across every performance parameter. Costly surprises from signal integrity to thermal conductivity and structural strength are far less likely when the team reaches physical assembly to help ensure on-time, cost-effective product launches. An example of simultaneous multivariate analysis of a chip stack showing both thermal gradients and mechanical stress/warpage of the package at an early prototyping stage. By contrast, applying multiple physics sequentially can lead to ongoing and expensive setbacks. For example, as one team resolves signal integrity issues, another team could discover that timing failures or thermal risks have arisen. It’s not only back to the drawing board, but back to a series of time- and resource-intensive handoffs across disconnected simulation and analysis tools, as well as across functional boundaries. The Importance of Considering Novel Physics Because the pressure is on to launch innovative 3D-IC designs rapidly, development teams might be tempted to focus on existing signoff metrics ― which are complicated enough, across today’s multi-die assemblies — but overlook the application of more novel physics. This is a mistake that can result in failures in the field, product recalls, warranty expenses and lasting damage to the brand reputation. To achieve full product confidence across the entire 3D-IC system, semi engineering teams need a solution set and associated best practices that make it fast and intuitive to not only optimize performance and cost, but to concurrently analyze novel physics that will impact electrical reliability, mechanical stability and thermal failure modes. The number of physical effects that need careful simulation has risen in lockstep with Moore’s Law and has increased even more for 3D-IC design. The use of a single, connected platform enables this kind of true multiphysics analysis. A multiphysics platform should interface with popular design systems, and be extensible by Python API's to the user and to other vendors. For example, engineers can check the thermal behavior and the likelihood of melting and local failures of each solder bump based on the electrical current it carries. The engineers can apply computational fluid dynamics to evaluate how well airflows generated by fans and heat sinks work to cool down the assembly. They can maximize system reliability by examining unfamiliar effects like low-frequency power oscillations on the distributed power supply network. Best of all, a unified and purpose-built simulation platform enables semiconductor development teams to conduct all these studies simultaneously to rapidly reveal design trade-offs that arise when many elements are brought together in a complex assembly. Only this type of multiphysics, multivariate, concurrent approach enables engineering teams to reach all their goals for speed, confidence, innovation and product performance as 3D-IC designs take over the global market. Supporting a Culture of Vertical Integration Global leaders in the semiconductor and electronics industries benefit from a culture and organizational model based on vertical integration, which supports high levels of design collaboration. It can be tough for horizontally integrated, smaller companies to establish this depth of collaboration. Customers require open and extensible platforms that support a broad range of analysis tools across many different abstraction levels – from device to chip to board to system. The right simulation technology platform can significantly help. A shared platform that brings cross-functional engineering teams together for simultaneous, not sequential, multiphysics design can make it easy and seamless to collaborate across functional boundaries and support excellence in every aspect of power, performance, reliability and cost. By balancing these foundational performance aspects with simultaneous optimizations of temperature, mechanical stress and other subtle effects, semiconductor engineering teams can position themselves as leaders, not followers, in the 3D-IC revolution. Learn More at the Ansys IDEAS Digital Forum Register for Ansys IDEAS Digital Forum on demand to learn more about 3D-IC best practices from leading industry experts (www.ansys.com/ideas). John Lee is General Manager of the Electronics and Semiconductor Business Unit at Ansys.

In the early 1990s, engineers of varying degrees of skill with a powerful PC set up shop designing and selling blocks or libraries of reusable components with a defined interface and behavior. These blocks, known as intellectual property, or IP, were then (and still are) integrated into a larger design. While the new market segment created excitement and new opportunities, it also was untested and created uncertainty. Many fledgling companies failed. It’s a different story today. Arm, as well as Cadence and Synopsys, are silicon IP suppliers and the segment’s yearly revenue tops $4 billion, a long way from those early garage startup days. ESD Alliance member CAST, a silicon IP provider since 1993, participated in the remarkable growth and impact on the semiconductor industry. Nikos Zervas, CAST’s CEO, and I discuss those early days of the IP business and what’s ahead. Smith: What were the early days of silicon IP like? Zervas: In those early Wild West days of IP, vendors and customers both wanted to benefit from IP, but nothing was standardized, and people just tried things to see if they worked. The perceived barrier to entry was low: hundreds of IP companies sprang up thinking they only needed RTL coding skills and tools, an FPGA to prototype, and a few thousand dollars to invest. IP deliverables, quality standards, and business practices varied from vendor to vendor and over time. Risk was high, and there are many horror stories of re-spins or market failures due to faulty IP cores. Smith: How has the silicon IP market changed from its early days? Zervas: Firms delivering high-quality IP and providing outstanding customer support survived. Others disappeared. Eventually the industry centered around a reasonably common sense of IP requirements and quality and a consistent set of business practices. IP product complexity has driven upwards as SoCs have grown. The largest ASICs used to approach a few million gates; today they’re hundreds of millions, and the granularity of IP has evolved from small functions to pre-integrated subsystems. Early on, a designer doing image processing might license individual functions like a Finite Impulse Response (FIR) filter or a Discrete Cosine Transfer (DCT) block. Today, instead they would license a complete JPEG compression core containing those functions and more, or even a complete black box subsystem streaming processed, stabilized, compressed video over Ethernet. IP selection criteria have also changed. Early IP was handcrafted to eliminate every extra gate, as being a few thousand gates smaller was a killer advantage in the era of 180nm ASIC processes. Today, at 7nm or 5nm process, tens of thousands gate differences are just noise, and it’s usually the reliability, functionality, and performance of an IP core that matter most. Smith: When did the silicon IP market start to take off? What was the driving force? Zervas: By the early to mid 2000s, uncertainty about what IP was and how best to use it – and the early wave of less-than-great providers – were being replaced by increasing acceptance and emerging best practices. The introduction of smartphones, the wild growth of Internet of Things applications, growing automotive system sophistication, and other advances fueled the explosion of the IP market in the late 2000s. In fact, according to the ESD Alliance Electronic Design Market Data Report, revenue from IP licensing today has surpassed the license revenue from front-end EDA tools. This would have been unimaginable in the late 1990s. Smith: How has silicon IP changed chip design? Zervas: Designers today must develop massive, complex systems with an even tighter time to market. Only the higher level of design abstraction and the distributed expertise that silicon IP provides make this possible. But IP also increases the challenge of differentiation: With the same IP available to everyone, how do you design a product that stands out in its market? The answer to differentiation today lies mainly in clever SoC architecture. Delivering better features with superior performance, lower power consumption, or other winning characteristics now depends not so much on perfecting each separate IP block but rather from selecting the best IP for the system’s requirements, integrating those IP cores for clean communication and efficient resource sharing, and other smart system-level decisions. It’s similar to modern building design: Every firm has access to the same materials and tools – concrete, glass, etc. – but only a few produce exceptional buildings. Smith: It seems that are several different business models for IP licensing, such as up-front license fees, subscriptions, royalties, or a combination of these. Do you think the IP market will gradually align around one basic model, or will it continue as is with a variety? Zervas: Different models serve different needs. For example, commodity IP like a SPI interface can’t demand royalties, but unique, leading-edge IP – like a 112Gbps SERDES – still can. I believe the market will continue with different business models, though the number of different models may shrink and their terms begin to align. About Nikos Zervas Dr. Nikos Zervas is the chief executive officer of CAST, Inc. He co-founded image and video compression IP developer Alma Technologies in 2001, and led the bootstrapped firm as chairman and CEO for nine years before joining CAST. He was a founding member of the Hellenic Semiconductor Industry Association and served on its board for several years with responsibility for strategic planning. He is a senior IEEE member and member of the Technical Chambers of Greece, had contributed to the GSIA's IP Working Group, and has published multiple technical papers on data compression design and related topics. Robert (Bob) Smith is executive director of the ESD Alliance, a SEMI Technology Community.

Alameda, Calif.-based Verific Design Automation, a member of the ESD Alliance, made its name in the electronic system design and semiconductor industry supporting companies ranging from startups to billion-dollar industry leaders such as Synopsys, Cadence, Siemens EDA, Xilinx, Microchip, NVidia, Infineon, Qualcomm, Renesas and Samsung. Its software is used as the front end to design automation tools such as synthesis, simulation, debug, and formal verification. I spoke with Verific president and COO Michiel Ligthart about homegrown and open-source EDA tools and other recent trends in chip design. Smith: What trends are you seeing in chip design? Ligthart: Semiconductor companies are starting to build a portfolio of intellectual property, including homegrown electronic design automation (EDA) tools, that they want to keep secure and differentiated from their competitors. The increased interest in internally developed and supported EDA tools is a trend we started to see about two years ago. It’s not simulation, synthesis or place and route (P R). Instead, it’s pieces of a chip design flow optimized for a company’s specific needs. In the past, a semiconductor company would either standardize on one EDA company’s chip design flow or mix and match best-in-class tools from different vendors. The common denominator was that they used off-the-shelf products. If they had a specific requirement, they went to the EDA provider for assistance. In today’s competitive landscape, semiconductor companies are figuring out ways to diversify themselves and their design flow became a way to do so. They may not build their own P R tool, but they will look at building their own power domain approach, for example. Is this a widespread trend? It could be. We hear about it within end-user applications ranging from 5G and AI to data center processors and there are probably others we don’t hear about. Power optimization is an example of the kind of specific internal need being addressed. Smith: What are your thoughts about open-source EDA tools? Ligthart: Our industry supports open source already with language reference manuals (LRMs) for VHDL, SystemVerilog, Unified Power Format (UPF) and the RISC-V Instruction Set. The LRMs and the instruction set are free. Moving to the development of actual tools becomes a question of who will implement, support and maintain the tools. Implementation is expensive. The Big Three (Cadence, Siemens EDA and Synopsys) invest about 35 to 40% of top-line revenue into R D. For smaller EDA companies, this number is even higher. The industry may come up with a business model that will have open-source components as well as a way to fairly reimburse companies that make these tools freely available. I have not seen it yet. Smith: Business Insider reports that Verilog HDL is among the top 10 tech skills that companies are desperate for their employees to learn right. Does Verific get asked about Verilog training? Ligthart: No. Our customers are experienced users. Nonetheless, it was great to read that article and it suggests the semiconductor industry is healthy, growing and hiring talented engineers. Smith: If an entrepreneur asked you for advice about starting an EDA or IP company, what advice would you provide? Ligthart: I would tell the entrepreneur to focus on the problem the startup is solving. Stick to the company’s core competency and try not to build in-house what can be purchased from a reputable supplier. In the end, it will save time and jump-start the development effort, and the engineering budget can be allocated to the startup’s core competency. The external supplier presumably has years of product validation, which brings a major QA gain. About Michiel Ligthart Michiel Ligthart, president and COO of Verific Design Automation, has an extensive background in engineering, product marketing and general management. Prior to joining Verific, Ligthart was vice president and general manager of West Coast operations for Theseus Logic, a startup in asynchronous logic. Before that, he spent eight years with Exemplar Logic in engineering and marketing roles. Ligthart started his career with Philips Research Labs in California and was a visiting scholar at the Center for Integrated Systems at Stanford University. He has a Master of Science degree in Electrical Engineering from Delft University of Technology, the Netherlands. Robert (Bob) Smith is executive director of the ESD Alliance, a SEMI Technology Community.

Throughout the current millennium, System-on-Chip (SoC) has been the gold standard for optimizing performance and cost of complete electronic systems. By incorporating practically all the phone’s digital plus analog capabilities onto a single, giant chip, the mobile phone processor serves as a near-perfect exemplar of SoC. But today’s leading integrated circuits (IC) are pushing up against the upper limit of a chip’s size which is limited by the manufacturing equipment’s optical reticle size. This has proven difficult to increase and has grown only slowly over the years. Yet market pressure continues unabated for bigger, more capable electronic systems with more integrated memory, more digital logic, and more analog/mixed signal circuitry. An emerging solution to this tension is 3D and 2.5D multi-die chip assemblies – often referred to as 3D-IC. The key technology breakthrough of 3D-IC is that it makes it possible to spread a system out over multiple, smaller chips that are then assembled close together and interconnected with high-speed, low-power interconnect technologies. By abandoning the need to integrate an entire system on a single SoC and instead allowing it to be disaggregated over multiple chips, 3D-IC enables Moore’s Law to break through the reticle size barrier, improves yield by shrinking the size of individual chips, and makes it possible to mix different process technologies optimized for each function. The Four Engines Driving Semiconductor Design The road forward is not without its challenges, however, and we are seeing design companies making significant efforts to adapt and come to grips with the following four technology and market drivers: The requirement for concurrent multiphysics analysis to ensure reliable and efficient electronic systems The blurring of the lines between silicon and system The need for open and inclusive multiphysics platforms that interoperate with the multitude of design platforms The need for, and value of, bespoke silicon for hyperscalers and system companies Blurring of Silicon and System Design The advent of 3D-IC opens up new horizons for solutions that can be implemented in silicon. But it also forces a closer integration between two distinct technology markets that have co-existed symbiotically for many decades: IC design and printed circuit board (PCB) design. These markets use different tools, different data formats, different manufacturing back-ends, operate at different computational and geometric scales, and focus on different physical concerns. Yet, 3D-ICs share many aspects of both markets: They include monolithic chips but also board-like substrates to stitch the chips together. And in between the two disciplines is packaging, a completely different domain that is requiring companies to re-imagine their design capabilities and flows, as well as their organizational structure. Open, Extensible Multiphysics Platforms The siloed isolation of chip design from PCB design and package design means that each of these markets has developed insular data structures that are ill-suited to deal with the breadth of multiphysics analysis for 3D-IC design. Many different physical disciplines, including computational fluid dynamics, mechanical stress, and electromagnetic radiation, all need to work together based on open and extensible multiphysics platforms. These platforms must embrace the modern cloud compute paradigm and enable an ecosystem by allowing individual design platforms to connect for comprehensive multiphysics analysis. Bespoke Chips Today’s market-leading companies are heavily dependent on technology for their continued success and market differentiation. Everybody from online retailers to telecommunications to social networking companies and hyperscalers are moving away from off-the-shelf solutions and turning to custom-built silicon to give them an edge. Many of these companies are seeking to gain market share by leveraging proprietary AI/ML algorithms trained on their extensive troves of market data – but this requires huge amounts of compute power and specialized chips. Access to high-quality silicon solutions is vital in today’s world and the demand is for continually more complex and powerful electronics. 3D-IC an Inflection Point in Electronic Design To be sure, 3D-IC design is at an inflection point in electronic design and presents major challenges that are realigning the electronic design industry around this new reality. For more insights on this topic from a semiconductor industry leader, please view the Keynote Address 2.5D and 3D – The Road Ahead by Vicki Mitchell, VP Engineering, Arm Central Engineering Systems Group presented at the latest Ansys IDEAS Forum. And for an EDA perspective, please view Successful 2.5D and 3D Multi-die Silicon System Design Using Synopsys’ 3DIC Compiler and Ansys’ Multiphysics Analysis from Synopsys SNUG World 2021. About John Lee John Lee is general manager and vice president of the Ansys Electronics and Semiconductor Business Unit. Lee co-founded and served as CEO of Gear Design Solutions (now Ansys), developer of the first purpose-built big data platform for integrated circuit design. He cofounded two other startups (Mojave Design and Performance Signal Integrity), which successfully exited into companies now part of Synopsys. He holds undergraduate and graduate degrees from Carnegie Mellon University.

Spend any time with Ansys’ John Lee, Rich Goldman or Marc Swinnen and you’ll hear plenty of optimism about the semiconductor industry even though they tick off a long list of looming design challenges. The need for reliable and effective electronic systems, they emphasize, is great and runs through high tech, aerospace and defense, automotive, IoT and 5G with communications being a common denominator. The three are especially bullish these days on changing market dynamics brought on by systems companies building company-specific bespoke, or custom, silicon. These systems companies are building chips with a different perspective and a fresh look at silicon design, a move away from the more traditional segment-specific silicon due to much more complexity. Ansys, a member of the ESD Alliance, a SEMI Technology Community, is a 4,100-employee company with a comprehensive portfolio of multiphysics engineering simulation software for product design, testing and operation products and services. John, Rich, Marc and I focused on Ansys’ semiconductor and electronics segment for our conversation. Smith: When did you notice the move by systems companies to build their own chips? What drives this trend? Lee: The inflection point was about three years ago when hyperscale data center and system companies recognized they needed an enterprise system design platform. They are designing bespoke silicon, driven to do this for cost efficiencies and to avoid relying on outside suppliers. They also want differentiation based on their specific platform needs so they can optimize compute power to their specific needs. Smith: What is driving the trend for multiphysics experience to ensure effective and reliable electronic systems? Lee: The increasing need for multiphysics analysis is acute. The physics of 3D IC, for example, brings in mechanical engineering with the convergence of mechanical and electrical as 3D emerges at the intersection of IC and System. As a result, physics becomes a necessity to analyze the stability of the chip in the package. Goldman: As well, the move to stacked chips, 3D IC and wafer-on-wafer requires thermal, electromagnetic and mechanical analysis in addition to the traditional analysis for function, performance and power. They all need to be analyzed together, not serially. It becomes multiphysics, not multiple physics. Smith: Two distinctly different disciplines – multiple physics and multiphysics – are needed for semiconductor design. How are they different? Why the need now? Swinnen: Multiple physics refers to the sheer breadth of physics that is now needed to analyze from the IC up to the largest system whereas multiphysics refers to the capability to analyze several physical effects concurrently, accounting for their impact on the design and interactions between various physics. Multiphysics are necessary to analyze the full context of the system environment – from nanometers to kilometers – for multi-chip packaging, chip-to-package-to-silicon and systems with multi-domain guidance. Goldman: A self-driving car, as an illustration, includes AI systems-on-chip, solid-state sensors, infotainment systems and radar/lidar detectors that must all work in the rain, the heat and the bitter cold. Smith: Why are design groups being reorganized to include expertise in mechanical and electromagnetic issues? Swinnen: Complexity has exploded, driven by a long list of technical requirements and, perhaps, mischaracterization. Goldman: Just consider the system on chip, mischaracterized by the semiconductor industry. The chip is never a system by itself. Rather, it is a complex component in a larger system and must be analyzed in that context. 3D IC is where this comes together and forces a recognition of physics outside the traditional scope of SoC design. 3D IC chips are much closer together on the board and it takes multiphysics embedded into the workflow of semiconductor design, packaging, system design and 3D IC to ensure they work reliably and efficiently. Smith: What is the solution? Goldman: It’s clear a specialized digital thread is necessary to move disparate groups with expertise in systems, physics and silicon together. Today, these groups or disciplines might not exist in the same company, whether it be a foundry, fabless or outsourced semiconductor assembly and test (OSAT) company. Lee: In order to unify the entire system design environment, a cloud-based, open and extensible heterogenous enterprise compute platform is required. It is similar to the SaaS-based business model and known as Simulation-as-a-Service (also SaaS). While vertical integration of design groups is already taking place at leading system design houses, there have also been advances in electronic design tools. These are starting to offer more comprehensive multiphysics capabilities including thermal, fluid dynamics (CFD), mechanical stress and reliability analysis in a single analysis cockpit. Today’s system designers face two platform challenges: First, they need an environment that is open enough to accept analysis results from multiple sources so that they can be overlapped and cross-analyzed. Second, the design platform must have the capacity to handle the enormous amounts of data generated by the latest 3-nanometer chips and 3D IC systems, and this implies an intimate coupling to elastic cloud computing. The days of an engineer writing Perl scripts and handing it off to someone else are gone. We believe that the industry is responding to this challenge with a new generation of design platforms that a cloud-native, open and extensible to allow heterogenous enterprise design. We are definitely at an inflection point in electronic design today, but the electronic industry has faced these before an we are confident it will master these challenges as well. About Rich Goldman Rich Goldman is director of marketing for the Electronics and Semiconductor Business Unit of Ansys. He holds a Bachelor of Science degree from Syracuse University and an MBA and Master of Science degree in Engineering Management. Moscow Institute of Electronic Technology (MIET)’s first honorary professor, he is also the recipient of honorary PhD degrees from Russian-Armenian (Slavnoic) University and State Engineering University of Armenia for contributions to the advancement of Armenia’s high-tech education and economic ecosystem. Rich served on EDAC’s board of directors. About John Lee John Lee is general manager and vice president of the Ansys Electronics and Semiconductor Business Unit. Lee co-founded and served as CEO of Gear Design Solutions (now Ansys), developer of the first purpose-built big data platform for integrated circuit design. He cofounded two other startups (Mojave Design and Performance Signal Integrity), which successfully exited into companies now part of Synopsys. He holds undergraduate and graduate degrees from Carnegie Mellon University. About Marc Swinnen Marc Swinnen is director of product marketing for the Electronics and Semiconductor Division of Ansys. He holds Master degrees in Electronic Engineering and Industrial Management from KU Leuven, Belgium, as well as an MBA from San Jose State University. About Bob Smith Robert (Bob) Smith is executive director of the ESD Alliance, a SEMI Technology Community. He is responsible for the management and operations of the ESD Alliance, an international association of companies providing goods and services throughout the semiconductor design ecosystem.