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Chip designers often face the challenge of accurately predicting the amount of compute resources their business will need as it grows and evolves. This is where scalability in cloud computing steps in, offering the flexibility to adapt your systems in line with changing objectives. More than just flexibility, scalability can be a powerful tool to optimize costs and enhance overall efficiency.
Benefits of Scalability in Cloud Computing
Cloud computing refers to a network of remote servers over the internet that store, manage, and process data. One of the key benefits of cloud computing is the ability to easily scale up or down IT resources depending on your needs.
Scalability in cloud computing allows for the expansion or reduction of infrastructure to meet an organization¡¯s current requirements. Since compute demands vary over time, predicting your organization¡¯s needs can be tricky. With the cloud, you can adjust your servers, data storage, or software to match your current demands.
Some prime benefits of scalability in cloud computing include:
- Enhanced productivity. Since cloud providers have the infrastructure already in place, you can decrease or increase your resources as needed without the wait for on-premises scaling faces. You can also keep track of your usage patterns to better predict your varying needs.
- Reduced turnaround times. Rather than having to buy or rent more resources, your growing business can request servers on short notice to accelerate the chip design process.
- Lower costs. With cloud computing, you only purchase the resources you need. When you no longer need them, you can scale back to meet your demand and avoid paying for what you aren¡¯t using.
Scalability in cloud computing provides a convenient alternative to on-premises equipment. Rather than purchasing more physical hardware, you can simply add virtual machines. Scalability in cloud computing increases the speed and ease of chip design and can help your business stay competitive by adapting to changing resource needs.
The various cloud models, specifically the hybrid cloud¡ªa model that provides benefits of both public and private cloud models¡ªallow you to access a multitude of compute and storage resources.
Types of Scalability in Cloud Computing
Vertical Scaling
Vertical scaling in cloud computing allows you to scale your existing servers up or down. You can vertically scale these resources without making changes to your code. Rather than having to purchase new equipment to meet the increasing needs of your business, you can simply increase the resources or memory of your virtual server.
Horizontal Scaling
Horizontal scaling in cloud computing allows you to increase the number of virtual servers to meet demand. In cloud computing, you can add additional instances instead of moving to a larger instance size as you would with on-premises. Horizontal scaling allows you to deal with increased traffic, yet it can be more complex to implement than vertical scaling.
Diagonal Scaling
Diagonal scaling in cloud computing is a combination of vertical and horizontal scaling. Here, your business would vertically add components to a single server before replicating the server and expanding horizontally.
Strategies for Scalability in Cloud Computing
Chip designers are confronting growing computational demands and time-to-market pressure. It is essential to correctly manage resources from the start to ensure you are using the cloud to its fullest potential. Similarly, you want to ensure you aren¡¯t lacking the appropriate resources for your chip design projects.
Synopsys cloud-based design solutions allow you to securely scale your infrastructure as needed to increase productivity and fuel innovation. Our EDA deployment model provides unparalleled levels of chip and system design flexibility via a single-source, pay-as-you-go approach called FlexEDA.
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.
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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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