Synopsys Debuts Industry's First Broad-Scale Cloud Saas Solution To Revolutionize Chip Development

Semiconductor Review | Thursday, March 31, 2022

Fremont, CA: Synopsys unveiled a new cloud-optimized electronic design automation (EDA) deployment model that delivers unparalleled chip and system design flexibility via a single-source, pay-as-you-go approach to drive significantly greater productivity and efficiency for increasingly complex chip designs. In addition, Synopsys Cloud gives customers access to the company's cloud-optimized design and verification tools and the pre-optimized infrastructure on Microsoft Azure to address higher degrees of chip development interdependencies.

"Semiconductor businesses are increasingly pushed to deliver both complicated functionality and energy efficiency in order to meet growing demands for more compute," said Mark Papermaster, AMD's senior vice president and chief technology officer. "AMD produces high-performance CPUs for a variety of tasks. In addition, Synopsys Cloud, which is built on the Microsoft Azure HBv3 cloud platform and is now powered by the latest 3rd Gen AMD EPYCTM Processors with 3D V-CacheTM technology, can enable cloud-based access to optimised compute and EDA tools, further enhancing our revolutionary chip design capabilities."

Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

Flexible Design and Verification Workloads for Dynamic Chips

Chip creation in the cloud is viable for an industry contending with rising computational needs and tighter time-to-market constraints. More chipmakers are shifting workloads to the cloud, from innovative design houses to huge systems firms to small startups, to take advantage of the faster time-to-results, improved quality of results, and lower cost-of-results that cloud-based design and verification technologies enable. However, forecasting computing needs has gotten more difficult, causing engineers to underestimate the computation and EDA resources they require while dealing with increasing systemic complexity.

Collaboration with Microsoft Azure to Improve Chip Development Using a Software-as-a-Service Approach

In recent years, chip development teams have begun to use Synopsys and other EDA vendors' "bring your own cloud" (BYOC) approach, in which chip development teams are required to source compute infrastructure from public cloud service providers and are frequently constrained by the pre-defined design and verification capacity. Synopsys collaborates with Microsoft, its preferred cloud partner, to redefine the landscape with a software-as-a-service (SaaS) chip development solution running on the Microsoft Azure cloud computing platform. Customers can immediately access and pay for cloud computing resources and any Synopsys cloud-enabled design and verification product using the SaaS model.

Customers who already have cloud resources through a BYOC approach can use Synopsys Cloud and its cloud-enabled EDA products on a pay-per-use basis. In addition, design teams will benefit from the flexibility and speedier time-to-market due to the cooperation with Microsoft Azure, which will solve today's systemic challenges in chip design and verification. Learn more about this relationship and its benefits from Microsoft

More in News

Executives acquiring quartzware fabrication systems face a purchasing decision that reaches beyond component replacement. In semiconductor and adjacent manufacturing environments, quartzware sits close to process performance, equipment uptime and yield protection. A tank, carrier, tube, chamber or heat exchanger that appears minor on a procurement list can become a constraint when purity, tolerance control or lead time fails to match production needs. The right fabrication partner must therefore be assessed not only by what it can build, but by how consistently it can support continuity when demand shifts, equipment ages or legacy parts become difficult to source. Current pressure on manufacturing teams has made this decision more exacting. Many facilities are trying to extend asset life while maintaining process discipline, controlling cost and avoiding downtime. New builds remain necessary, but replacement alone is not always the rational answer. When a damaged quartz component can be restored to specification, repair capability becomes a strategic purchasing advantage. It helps teams preserve scarce capital, shorten recovery windows and reduce dependence on fresh fabrication when production schedules are exposed to raw material and capacity delays. Precision is still the baseline. Quartzware used in semiconductor equipment must be fabricated from appropriate high-purity material and held to tight dimensional requirements because contamination and variation can travel quickly into yield loss. Buyers should look for evidence that the supplier treats quality control as a release discipline rather than a final formality. That means documented inspection, tolerance verification, equipment upkeep and a workforce trained to repeat complex work without relying only on individual memory. A supplier’s ability to keep machinery calibrated, maintain fixtures and invest in the people doing the work often determines whether quality holds steady beyond one successful order. Flexibility is equally important. Many manufacturers inherit tools, assemblies and parts without current drawings, especially when equipment has been modified, transferred or supported by older OEM documentation. A capable quartzware fabrication system should be able to reverse engineer unfamiliar parts, translate samples into workable drawings and support both one-off and recurring needs. This is where the distinction between a parts vendor and a true fabrication resource becomes clear. The stronger partner can handle unusual geometries, repairs, production pieces and urgent requests while preserving inspection discipline and delivery reliability. Delivery performance should be treated as a technical requirement, not a customer service promise. In fabricationdependent manufacturing, lateness does not merely inconvenience purchasing. It can idle equipment, delay qualification or force teams into lower-quality substitutes. Strong suppliers build reliability through planned maintenance, trained labor, transparent quoting and realistic commitments. The best choice is the partner that can combine purity, repair judgment, engineering adaptability and delivery consistency into one dependable source. Desert Glass Works stands out for buyers needing this balance. Its relevant work spans quartzware repair, custom machining and precision fabrication for tanks, carriers, process chambers, diffusion tubes, bell jars, heat exchangers and related semiconductor components. The company’s model is well matched to buyers managing new requirements and legacy equipment, since it can repair or restore parts, reverse engineer components without drawings and fabricate custom quartzware from high-purity stock. Its emphasis on full inspection, maintained equipment, apprenticeship-based skill development and on-time delivery makes it a strong recommendation for organizations that need quartzware support tied directly to yield, uptime and disciplined execution. ...Read more
Longer validation cycles are forcing semiconductor factories to examine a cost that rarely appears cleanly on a procurement sheet: the time lost among test readiness, tool availability, engineering bandwidth and material movement. Advanced packaging, AI processors, automotive electronics and mixed-signal devices have widened the range of qualification work inside the same facility. A test cell may be technically capable, yet throughput still suffers when device programs shift faster than handlers and factory logistics can adjust. That pressure often shows up as idle equipment rather than an obvious planning failure. The buying question is no longer confined to tester performance. Executives responsible for semiconductor test and robotics systems need to understand how a platform behaves when product mix changes and validation data expands while factory movement becomes a constraint on output. Hardware flexibility matters because qualification programs cannot wait for major reconfiguration every time a device family changes. The test environment should support wafer sort, final test, system-level validation and diagnostic review while allowing engineering teams to move between device requirements with limited disruption.  Diagnostic visibility carries equal weight. AI accelerators and dense system-on-chip designs produce large volumes of validation data under demanding electrical conditions. Engineers need earlier anomaly detection, clearer failure analysis, yield-behavior context  and a practical way to connect test results to process variation. A system that only records pass-fail results leaves too much interpretation for later review. Better infrastructure helps teams identify variation while the qualification window is still open. Factory movement has become part of the same purchase logic. Semiconductor facilities often lose time in the handoff between test stages, especially when materials or qualified components depend on manual transport. Robotics should reduce that drag without forcing the factory into a redesign. Collaborative robots must be practical for inspection and machine tending, while autonomous mobile robots should coordinate transport across existing floor layouts, adjust to changing routes, respond to obstacles and reduce waiting time around qualification flow. Integration is where many automation programs lose momentum. Test equipment, robotics systems, factory software and data tools frequently come from different vendors, making communication gaps a real production issue. Buyers should press for open integration and clear status data. Deployment paths also matter, especially when custom work stretches past the point of early value. Reliability remains nonnegotiable, since a robot or tester that adds downtime during a qualification push creates the problem it was purchased to solve. Teradyne fits this buying logic because it brings semiconductor test equipment and intelligent robotics into one portfolio relevant to validation and factory flow. Its test systems support wafer sort, final test, system-level validation and broader device qualification for memory, analog, mixed-signal and system-onchip applications. Universal Robots gives it collaborative robots suited to machine tending and inspection work. Mobile Industrial Robots supports autonomous transport inside manufacturing environments. Teradyne’s emphasis on analytics, adaptable test platforms, collaborative automation and mobile robotics gives semiconductor executives a practical route to connect validation accuracy with steadier factory coordination. For buyers trying to reduce qualification delays without separating test decisions from movement constraints, it deserves close evaluation. ...Read more
The PCB design industry has consistently prioritized innovation, enabling electronic device manufacturers to develop increasingly advanced products. As demand grows for smaller, faster, and more efficient electronics, effective PCB design has emerged as a crucial element in meeting these requirements. Advanced software solutions now extend beyond mere circuit drawing; they enhance every phase of the design process, from initial concept to final production. As technological advancements continue to evolve, new trends within the PCB design domain are emerging, influencing how engineers address design challenges and facilitating the transition of products from the conceptual stage to practical implementation. Integration with AI and Machine Learning The industry is transforming significantly by integrating artificial intelligence (AI) and machine learning into printed circuit board (PCB) design software. AI-driven tools can automate essential tasks, including component placement, routing, and error detection, enhancing performance and manufacturability. Furthermore, AI can identify potential issues during the design phase, enabling engineers to rectify such problems before the fabrication of physical prototypes. These machine learning models facilitate informed decision-making regarding component placement and routing by analyzing historical data and established best practices, ultimately saving designers time while improving the quality of PCBs. Shortly, a broader acceptance of AI is anticipated, which is expected to lead to fully automated design processes that enhance the efficiency of the PCB design cycle. Cloud-Based Collaboration and Remote Design Cloud-based PCB design platforms are fundamentally transforming the design landscape by facilitating real-time collaboration and providing access to design files from any location globally. These platforms enable engineers, designers, and manufacturers to work concurrently on the same PCB design, enhancing communication and accelerating decision-making processes across global supply chains. They offer significant advantages such as version control, data backup, and the capability to share large design files without the limitations commonly associated with traditional file transfer methods. In an increasingly remote or hybrid work environment, these cloud-based PCB design tools will continue to be indispensable for bridging geographically distributed design teams. 3D PCB Design and Simulation The emphasis in PCB design is increasingly placed on three-dimensional (3D) design and simulation within the design environment. Historically, most software solutions provided limited two-dimensional (2D) views, which constrained the ability to visualize performance under real-world conditions. Integrating a third dimension in PCB design significantly enhances engineers' understanding of how circuits interact with mechanical enclosures, adjacent components, and entire device systems. Engineers can conduct more precise analyses by evaluating critical metrics such as thermal performance, signal integrity, and component placement in a realistic context, thereby identifying potential challenges at an early stage. Comprehensive simulations of all physical interactions between the PCB and the associated components can mitigate the risk of incurring substantial errors during the revision and prototyping phases. As the complexity of PCB designs continues to escalate, the necessity for advanced 3D design capabilities is expected to rise correspondingly. ...Read more
PCB design software has long been treated as a discrete step within a broader engineering workflow, focused on schematic capture, layout precision and manufacturability. That framing no longer holds under the weight of modern embedded systems, where software-defined functionality, connectivity requirements and component diversity introduce a level of interdependence that traditional tools were not built to manage. Engineering teams are no longer constrained by layout complexity alone; they are constrained by fragmentation across tools, domains and decision points that sit upstream and downstream of PCB design itself.  The most significant and ongoing problem is not necessarily the capability of the tools, but the lack of connectivity between the tools. Hardware designers, software engineers and system architects typically work in parallel domains that don't share a consistent model of design intention. Requirements are interpreted differently among domains, documentation is out of date and validation only occurs late, often during integration when corrections are costly.   This fragmentation is compounded by the diversity of applications in embedded systems. Each use case brings its own set of tools, workflows and dependencies, forcing teams to reconstruct their environment repeatedly. The result is a design process where value creation is delayed, iteration cycles are prolonged and decision-making is constrained by the effort required to evaluate alternatives. This prevents a "what if" exploration of possibilities and restricts system-level optimization opportunities.  A better model results when the PCB design is not treated as an independent task but rather as a step within the overall system model. In this model, design intent is captured early and expressed in a way that can be interpreted across domains. Component choices, system performance and requirements are explicitly described as data structure inputs to the subsequent design steps automatically. Instead of manually reconciling datasheets, tool outputs and design assumptions, engineers operate within an environment where context is shared and continuously updated.  This shift changes how teams assess PCB design software. The question is no longer whether a tool can perform layout tasks efficiently, but whether it can support a connected design process that spans concept development, component selection and system validation. The ability to take high-level design objectives and turn them into practical design configurations is becoming increasingly important. Just as important is maintaining alignment between hardware and software, ensuring that configuration states, dependencies and constraints remain consistent throughout the development process.  Time-to-market improvements come from this continuity rather than isolated efficiency gains. When design decisions are evaluated earlier and updated dynamically, the need for late-stage corrections is reduced. Iteration times shorten and become more reliable, allowing the team to progress confidently from idea to deliverable.  Renesas Electronics Corporation positions its Renesas 365 platform within this emerging model. It goes beyond traditional PCB design by bringing requirements, component data and design workflows into a single environment. By evaluating design requirements alongside available components, the platform helps engineers identify viable options more quickly and reduces the manual effort involved in assessing feasibility. Its approach links hardware and software through shared models, keeping configurations aligned and allowing teams to quickly adapt as requirements evolve.  The result is a design experience where engineers spend less time assembling tools and more time refining system behavior. Through continuity and the built-in context of the Renesas 365 workflow, PCB design is aligned more closely with the system-level requirements imposed on current embedded systems, making it a strong choice for organizations aiming to move from fragmented processes to coordinated system-level engineering.  ...Read more