Leveraging a Cloud-Native Environment for EDA | Synopsys Cloud
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Introducing Synopsys Cloud

Cloud native EDA tools and pre-optimized hardware platforms. Experience unlimited EDA licenses with true pay-per-use on an hourly or per-minute basis.

By leveraging a cloud-native environment, you can design, build, and manage workloads in the cloud. A cloud-native approach utilizes containers, service meshes, microservices, immutable infrastructure, and application programming interfaces (APIs). 

Because cloud-native architecture depends on microservices that perform unique and specific functions, advantages in implementation, communication, and execution are available.


Advantages of a Cloud-Native Environment

Cost-effective 

Computing resources can be scaled as needed in a cloud-native environment, and load balancing is unnecessary because overprovisioned hardware is eliminated. Virtual servers are easy to add for testing, and cloud-native applications can be up and running quickly. Containers can also run additional microservices on a single host to save time, resources, and money.

Because cloud-native applications function on the cloud and offer compatibility with cloud-native infrastructure, costs for backup, maintenance, development, and resource usage decrease. Open-source tools that follow a pay-per-use model can further drive down costs.

 

Independently Scalable 

Microservices are logically isolated and scalable. With microservices, you can scale out only the services that need more processing power to meet desired performance levels and service-level agreements. Fine-grained scaling provides enhanced system control and reduces overall costs.

Cloud-native applications adapt to business requirements and allow frequent software updates and modifications based on customer feedback. They enable horizontal scalability, eliminating the need for hardware solutions and software-dependent infrastructure as the business grows.

 

Flexible

Cloud-native apps use containers to port microservices across cloud vendor infrastructures, preventing vendor lock-in. Because cloud-native services can run on any cloud platform, you can move to a better cloud pricing and benefit plan anytime

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Manageable

In cloud-native environments, app updates and features are deployed automatically. All microservices and components can be tracked during the update process. Cloud-native allows engineers to focus on specific microservices without worrying about how they interact with each other.

 

Observable

A microservice architecture isolates services, making it easier for engineering teams to study and learn how applications interact. Cloud-native environments allow real-time analysis and use of data to detect performance issues and analyze customer behavior. 

 

Cutting Edge

The cloud-native environment is designed to handle the influx of modern data volumes. Cloud-native application development makes it possible to conduct data analysis in real time. Once data is analyzed, it can be assigned a particular lifespan then discarded or redirected to a storage medium. 

 

Automated

Automation is a crucial component of DevOps. Modern cloud-native apps support DevOps processes, enabling automation and collaboration. Automated processes can repair, scale, and deploy your system faster than people.

 

Resilient

A cloud-native architecture lets you build self-healing, resilient systems. Even if downtime occurs, you can run your apps by spinning up other systems while isolating the faulty ones. The result is higher availability, better customer service, and better uptime.

 

Secure

A cloud-native environment originates in internet-facing services. A defense-in-depth approach applies authentication between each component and implements a zero trust security model. Consequently, there is no “inside” and “outside” in terms of security, which is well-suited to a cloud-native environment.


Cloud-Native Environment and EDA

What are the benefits of a cloud-native environment for chip makers who use electronic design automation (EDA) software? While most EDA tools run on-premises, EDA vendors and customers can gain significant value from using cloud-native EDA tools. 

Chip design teams can use cloud-native software tools to work simultaneously on multiple steps. By eliminating storage and compute constraints, cloud-native tools help organizations break down silos between chip research, development, and design.

With Synopsys, you can access cloud-native EDA tools, pre-optimized hardware platforms, and a flexible business model. Additionally, our cloud-based chip design will not disrupt your workflow. Using unlimited computing power and flexible deployment options, you’ll design and verify chips faster.


Synopsys, EDA, and the Cloud

Synopsys is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With Synopsys Cloud, we’re taking EDA to new heights, combining the availability of advanced compute and storage infrastructure with unlimited access to EDA software licenses on-demand so you can focus on what you do best – designing chips, faster. Delivering cloud-native EDA tools and pre-optimized hardware platforms, an extremely flexible business model, and a modern customer experience, Synopsys has reimagined the future of chip design on the cloud, without disrupting proven workflows.

 

Take a Test Drive!

Synopsys technology drives innovations that change how people work and play using high-performance silicon chips. Let Synopsys power your innovation journey with cloud-based EDA tools. Sign up to try Synopsys Cloud for free!

About The Author

Gurbir Singh is group director, Cloud Engineering, at Synopsys. He has a demonstrated history of leadership in the software industry. In his current role, he leads the development of the Synopsys Cloud product, which enables customers to do chip design on the cloud using EDA-as-a-Service (SaaS) as well as flexible pay-per-use models. Gurbir has run organizations to develop cloud SaaS products, machine learning applications, AI/ML platforms, enterprise web applications, and high-end customer applications. He is experienced in building world- class technology teams. Gurbir has a master’s degree in computer science, along with patents and contributions to publications. 

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