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Preparing for the Future of Cloud Computing

By Sridhar Panchapakesan, Senior Director, Cloud Engagements

Table of Contents

Major Trends for Cloud Computing
Developing Chips in the Cloud
Synopsys, EDA, and the Cloud

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Gartner forecasts that end-user spending on public cloud services worldwide will reach $600 billion in 2023, up from $495 billion this year. By 2026, Gartner estimates that public cloud spending will surpass 45% of all enterprise IT spending, up from 17% in 2021.

With the rise of the cloud, business technology has changed profoundly. Are you ready for what the future of cloud computing can offer?

Below are some of the major trends to look out for if you want to stay ahead of cloud computing developments.

Future of Cloud Computing: Major Trends

Artificial Intelligence

Businesses are steadily turning to artificial intelligence (AI) for their cloud computing needs. With AI, cloud computing is more efficient, strategic, and insight-driven. Companies can automate complex and repetitive tasks and analyze data without human intervention.

The future of cloud computing will see AI become increasingly relevant as companies hope to streamline processes and eliminate manual work. AI/ML innovations in high-performance computing (HPC) products require the generation and management of massive amounts of data for training, analyzing, and building models. Cloud-scale infrastructure has become a must-have for swiftly gathering data and building intelligent models in such innovative products.

As data analysis continues to rely upon AI, companies will also have better insight into their products and services.

Quantum Computing

Cloud-based quantum computing provides direct access to quantum emulators, simulators, and processors over the internet. Quantum computing uses the laws of quantum mechanics to solve problems that are too complex for classical computers.

Quantum algorithms take a new approach to complex problems, creating multidimensional spaces where the patterns linking individual data points emerge. Classical computers can't create these computational spaces, therefore they cannot deduce these patterns. Linking the cloud and quantum computing can overcome these limitations.

Edge Computing

Decentralization is popularizing edge computing, where everything is done locally instead of at the central cloud network. Storing and calculating data close to where it is generated and consumed reduces latency, provides faster real-time response times and optimizes bandwidth.

Businesses are looking to bridge the gap between a centralized cloud and the end-user at the network edge. Spurring innovation requires integrating a distributed edge strategy into a larger cloud computing effort.

Serverless

Serverless is a cloud-native development platform that allows developers to build apps without managing servers. Servers still exist in serverless, but they are abstracted from app development. Cloud providers handle provisioning, scaling, and maintaining the server infrastructure. Deploying code is as easy as packaging it up in a container.

The main difference between serverless and other cloud computing models is that the cloud provider manages both the cloud infrastructure and the scaling of applications. In serverless applications, containers automatically launch when you need them.

SASE

Organizations will continue to adopt security access service edge (SASE) technology as they graduate from the quick response measures implemented for unexpected surges in remote workers.

With SASE, software-defined wide area network (WAN) capabilities combine with cloud-native security services, including zero-trust network access, secure web gateways, cloud access security brokers, and firewall as a service.

Regional Ecosystems

The future of cloud computing will see the emergence of regional and vertical cloud ecosystems. Growing regulatory fragmentation, protectionism, and industry compliance all drive this trend.

Many companies are looking for ways to reduce lock-in and single points of failure for their cloud services. Regions that cannot create or sustain their own cloud platform ecosystems will have to rely upon those established in other regions. Concerns among politicians, academics, and tech providers have increased within these regions, leading to regional data infrastructure initiatives such as GAIA-X in Europe.

Developing Chips in the Cloud

A trend affecting the semiconductor industry and chip designers, in particular, is the growing use of chip design and verification tools in the cloud.

Cloud computing works best for chip design in areas where computing resources are limited. For example, brute force computation may take precedence over human design expertise and skills in large-scale verification projects.

Increasing computational demands and the need for shorter design and verification cycles have created a need for new methodologies and tools. To keep up with chip and system design innovation, chip companies and designers will increasingly employ cloud-based tools and techniques.

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.

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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

Sridhar Panchapakesan is the Senior Director, Cloud Engagements at Synopsys, responsible for enabling customers to successfully adopt cloud solutions for their EDA workflows. He drives cloud-centric initiatives, marketing, and collaboration efforts with foundry partners, cloud vendors and strategic customers at Synopsys. He has 25+ years’ experience in the EDA industry and is especially skilled in managing and driving business-critical engagements at top-tier customers. He has a MBA degree from the Haas School of Business, UC Berkeley and a MSEE from the University of Houston.