The use of cloud computing for EDA work may still be out of reach, but within three to five years, cloud computing will account for up to 20% of design transactions between major EDA vendors and customers.
This conclusion was set by the vice president of IBM's Innovation Design at the Design Automation Conference for cloud computing. Bernie Meyerson predicted in his recent keynote speech that in the next 5 to 10 years, cloud computing will be the main medium used by chip designers. "This is due to the unsustainable rate of increase in IT spending."
"All along, the demand for IT resources has accelerated and seems to never be met, driven by the emergence of "net things," Meyerson said. This is forcing even EDA to explore emerging computing models such as cloud computing.
The panel discussion on this issue, with the SaaS (as a service software) model, came from the computer enterprise space gradually infiltrating the design automation community in order to transfer certain parts of its design to remote server farms.
In fact, IC design has taken a lap: From the previous design, mainframes were used to calculate design parameters and design the corresponding chips. Nowadays, it is a large number of servers where the company's electricity bills are used—an old-fashioned scenario. The next step is to bring the design to remote IT server farms and share server farms with others, just like the mainframe era, but it is now being used remotely.
Raul Camposano, a former Synopsys employee and now a consultant, said that cloud computing is driven by cost-effective on-demand provision of a large number of scalable computing resources. "Cloud computing has set the standard for many enterprise and consumer applications. However, there is a limited chance of success in IC design."
John Chilton, senior vice president of marketing/strategy development at Synopsys, said, "Obviously, the EDA industry must determine how best to use the potential advantages of this resource."
Chilton said that Synopsys sees cloud computing as a way to manage and control the total cost of its design, given the complexity of relentless growth and the constant review and reduction of budgets. "Achieving real-time availability and flexible computing resources is the key to solving this challenge. Like all optimization issues, it is critical to carefully and completely limit costs."
Professor Rean Griffith of the University of California, Berkeley stated that in the cloud computing, certain categories of applications have become more compelling: "Parallel batch jobs can benefit from computational costs. For example, it will use 1,000 machines per machine. Hours and use of 1,000 machines at the same time in one hour cost the same, but results are faster.â€
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