Singapore based Plunify claims that chip design companies can design faster and better using cloud computing. Stressing on the company’s go-to-market strategy, Plunify’s founder, Harn Hua Ng, said the Plunify partners with tool vendors, their distributors and complementary sales representatives.
Since pay-as-you-go business models are rare in the semiconductor industry, we went through several steps, of which the first was to better understand the market, the available tools and stake-holders:
* How is the market reacting to cloud computing and licensing schemes?
* What are current tool capabilities with regards to multiple CPUs/servers? Which parts of the chip design workflow can best take advantage of scalable, parallel features?
* What tools are more suitable for a cloud environment?
With these in mind, the next step was to build the cloud platform and the application clients to address immediate concerns – security, accessibility and cost.
“Then, we partner with tool vendors, their distributors and sales reps to bring our solutions to end-users. Companies of different sizes
view the advantages of cloud computing differently, so solutions need to be customized accordingly. Some see Plunify as solving longer term IT problems of scaling and provisioning; while others use us as an immediate way to speed up their design workflows. We are still in the process of learning about the market.”
How can the on-demand cloud computing platform dramatically accelerate chip design workflows? According to Harn Hua Ng, one immediate benefit is an almost instantaneous fulfillment of peak demand IT requirements, for example, a urgent request to do 100 synthesis builds to fix a problem due yesterday. Or if the problem cannot be fixed, at least the design team will find out in a day rather than potentially in three months’ worth of runtime without a cloud solution. The longer term acceleration is a gradual parallelization of the design workflow.
Currently, chip designers tend to visualize the design workflow as a chain of mostly serial steps with many dependencies, just because many steps can be time-consuming (both in terms of runtime and time taken to analyze intermediate results).
With an on-demand compute platform, designers can have more room to experiment and to optimize, more readily incorporating agile practices in hardware development.