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One way to ease the complexity and cost of chip design is to leverage cloud elasticity. But what is elasticity in cloud computing, and how can it help with your next chip project?

This article answers the following questions in detail:

• What is elasticity in cloud computing?
• How does cloud elasticity differ from cloud scalability?
• Why does cloud elasticity matter to EDA?

What is Elasticity in Cloud Computing?

Put simply, elasticity is the ability to increase or decrease the resources a cloud-based application uses. Elasticity in cloud computing allows you to scale computer processing, memory, and storage capacity to meet changing demands. Scalability will prevent you from having to worry about capacity planning and peak engineering. 

Cloud elasticity also prevents you from having to pay for unused capacity or idle resources, meaning you won¡¯t have to buy or maintain extra equipment.

As an alternative to on-premises infrastructure, elastic computing offers greater efficiency. It is also typically automated and keeps services running reliably by avoiding slowdowns and interruptions.

You can automatically trigger and execute cloud elasticity based on workload trends, or else you can manually initiate it. With cloud elasticity, it's easy to remove capacity if and when demand eases. By doing so, you pay only for the resources you consume at any particular time. As a result, you won¡¯t need to invest in or retire on-premises infrastructure to meet demand spikes.

What Makes Cloud Elasticity Different from Cloud Scalability?

Cloud elasticity allows you to match the number of resources allocated with the number of resources needed at any given time. With cloud scalability, you can add and remove resources to meet the changing needs of an application within the confines of existing infrastructure. You can do this by adding or removing resources to existing instances¨Cscaling up or down, or vertical scaling¨Cor by adding or removing resources of existing instances¨Cscaling out or in, or horizontal scaling. 

Scaling up or out keeps the application or chip design project from slowing down due to a lack of resources. Scaling down the infrastructure statically supports a smaller environment when you don't need the resources. 

Why is Cloud Elasticity Important for EDA?

With cloud-based systems, you can scale up your EDA infrastructure in minutes. When you need to, you can quickly expand your infrastructure as much as you¡¯d like. If you no longer need it, you can easily shrink it back down. Simply notify the orchestrator in the cloud environment that you require more or less capacity, and they will change it for you in minutes. 

In contrast, expanding your on-premises network's EDA capacity will require you to borrow existing capacity from someone else on the network. Otherwise, you must order more servers, wait for the vendor to ship them, set them up in your server room, and activate them. 

Cloud computing is also more redundant than on-premises networks. Cloud systems are redundant inside the data center, with redundant data centers worldwide. These systems keep your data safe from both natural disasters and human error.