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Multi-Cloud Architecture: Design, Benefits, and Role in Chip Design

Gurbir Singh

Sep 19, 2022 / 3 min read

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Are you thinking of leveraging more than one cloud provider to help you with your chip design and verification project? This blog examines the best practices for multi-cloud architecture and discusses how you can employ multi-cloud to your advantage.

What is a Multi-Cloud Architecture?

With a multi-cloud architecture, you can boost innovation, access specialized hardware unavailable on-premises, and scale computing and data storage as your business grows. A multi-cloud architecture can include public and private clouds or multiple public clouds.

Multi-cloud architectures allow for resilience. By combining clouds and services and tailoring applications to their strengths, multi-clouds increase efficiency and produce better results. For example, you might leverage one cloud provider¡¯s GPUs for specific workloads and a second cloud provider¡¯s analytics engine.

 

To better understand multi-cloud, it is useful to answer a few questions:

  • Why should I use more than one cloud provider?
  • How do I design a multi-cloud architecture?
  • How can multi-cloud architecture help with chip design and verification?

Examining these questions in greater detail can help determine how multi-cloud architecture can help you design better chips.

Reasons to Opt for Multiple Cloud Providers

Close to 90% of enterprises already use more than one cloud provider, according to a  by Flexera.

Enterprises rely on multiple cloud providers to find the best price for cloud services, reduce latency, avoid vendor lock-in, ensure flexibility, increase redundancy, and comply with data sovereignty regulations. 

But to gain those benefits, you need to manage cloud services efficiently. Otherwise, the complexity of a multi-cloud environment might overwhelm your IT team.

Designing an Effective Multi-Cloud Architecture

To take full advantage of a multi-cloud environment, you need a consistent multi-cloud architecture design. Let¡¯s examine the most prominent multi-cloud architecture designs.

 

1. Cloudification

Cloudification enables an on-premises app to use cloud services from multiple cloud providers. Cloudification provides the application with increased scalability. It also avoids vendor lock-in, improves availability, and boosts reliability. Additionally, the application can still work even if one cloud service goes down.

 

2. Multi-Cloud Relocation

In multi-cloud relocation, you can rehost a previously on-premises application on a cloud platform. You can then configure it to use another cloud platform. For instance, you might relocate the application to one cloud provider but secure the data storage from another.

 

3. Multi-Cloud Refactoring

The multi-cloud refactoring process involves re-architecting an application. It is therefore compatible with multiple clouds. You can re-architect an on-premises application into two components and run them on separate cloud platforms. In contrast to relocation, refactoring involves re-designing the original application, which necessitates changing the code.

 

4. Multi-Cloud Rebinding

Multi-cloud rebinding involves re-architecting an application for migration to a multi-cloud environment. With the re-architected application, you can deploy some components over multiple cloud environments to ensure continuity of service in case a failure occurs on the main platform. 

Multi-cloud rebinding can also use a cloud brokerage service, integrating various components of multi-cloud infrastructure. This process ensures all components function optimally and securely.

 

5. Multi-Application Modernization

In multi-application modernization, you can re-architect several applications as a portfolio and deploy them in a multi-cloud infrastructure. Individual applications, even when re-architected for the cloud, can still experience shortcomings. These shortcomings can include data inconsistencies, duplicate functionality, and higher maintenance costs. By analyzing applications before re-architecting them, you may uncover opportunities to consolidate and integrate. Doing so can ensure your applications work together proficiently in multi-cloud environments.

Multi-Cloud Architecture's Impact on Chip Design and Verification

With a multi-cloud architecture, a chip designer can connect on-premises workflows to various clouds.

A multi-cloud architecture allows for the seamless migration of electronic design automation (EDA) workloads from one cloud provider to another. Utilizing EDA in the multi-cloud enables you to create iterations faster, producing a competitive advantage in time-to-market. 

A multi-cloud architecture also allows you to negotiate better prices with cloud providers. Alternatively, you can change providers if necessary, as the architecture enables easy switching to avoid vendor lock-in.

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 ¨C 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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