Companies in the semiconductor ecosystem have started seriously considering the cloud for computing and storage at an increasing pace. Some have already migrated. Others are evaluating their cloud technology choices and sizing the business impact and benefits to make the leap. According to adoption reports such as this, the cloud environment is proving to be beneficial for System-on-Chip (SoC) designers. It provides access to unlimited compute capacity, flexibility, on-demand tailored virtual machines, advanced computing services, and enabling multi-site collaboration.
Various semiconductor companies will have different cloud solution requirements. Their business goals and chip design workflows will likely dictate their cloud migration paths and their choices of compute environment – whether, for example to move to the cloud, or opt for an on-premises data center, or a combination with adoption considerations.
Like the industries serving healthcare and finance, chip design companies have stringent requirements for cloud solutions. These will include security, just-in-time monitoring and compliance with regulations. In addition, the type of cloud environment and model will differ based on a company’s size and business goals as well as its chip design and verification methodologies. It is not one size fits all.
So, a successful migration and journey to the cloud requires a performance-cost-based assessment and identifying which chip design and verification workflows to move to the cloud. This includes decisions on a single or multi-CSPs (Cloud Services Providers) environment, the type of cloud model (“all in the cloud” or hybrid), and the types of automation and license models.
What should you move to the cloud?
Chip design complexity is growing, and the verification workflow continues to make up a significant portion of the chip design development cycle. Looking closely at IC design projects, the time spent on verification – both analog and digital circuit simulations – is a higher percentage (Figure 1) of the overall design project cycle.
The highly iterative circuit simulation tasks involved span the entire IP design and verification cycle. Then, each process node migration to the next smaller process geometry results in more simulations because there are more packed blocks and sub-systems to verify to realize the intended performance boost. These parallelizable simulation tasks comprise a suitable workflow to move to the cloud, where users can reduce runtimes from weeks to days.
Advanced node library characterization is another highly parallelizable workflow. Characterizing an entire standard-cell library requires hundreds of millions to billions of SPICE simulations, taking days to weeks to complete. With cloud computing, library characterization teams can accelerate their library characterization workflows and complete to within 24 hours.
The availability of compute resources limits the number of simulations each designer can run during the entire design cycle. Typically, design teams run as many simulations as they can on what is available. This limits the extent to which they can perform design space exploration to ensure the most optimal PPA (Performance, Power, and Area) and deliver competitive products on schedule. Furthermore, the compute resource constraint forces design teams to prioritize their various simulation-plan tasks to meet the development deadline, which often leads to cutting corners based on the best historical judgement that may not necessarily translate to thorough verification – hence, putting the design at risk. Cloud computing is a viable option to provide scaling compute resources and meet the demand during peak times of the chip design cycle.
The decisions around the type of cloud solutions, the migration path to the cloud and the workflows to employ there must all be made thoughtfully with minimal disruption to the existing chip design environment. To that end, Siemens EDA, as a trusted supplier and advisor, provides cloud-ready AMS verification solutions to help accelerate SoC verification and library characterization on the Amazon Web Services cloud. This enables chip design teams to boost productivity and shorten their time-to-market schedules.
Selecting the migration path and adoption
A customer’s choice of cloud environment and migration depends on several factors, including the company’s size and the type of EDA workflows. There are generally three categories of companies: large, mid-size and small/startup.
Enterprise (or large) companies will have an established IT, support team, on-premises compute infrastructure and a central CAD team. They typically have transitioned to the cloud with a do-it-yourself (DIY) approach. These companies adopt the hybrid cloud model to augment their on-premises compute clusters with cloud computing to meet peak compute capacity demand and customize the cloud application to their needs.
Mid-size companies will probably have some compute infrastructure and a CAD team. They typically require automation assistance to implement and support their choice of a cloud model, whether for an “all in the cloud” or a hybrid cloud flow.
Small and startup companies may have minimal-to-no computing infrastructure and/or existing technical expertise in the cloud. Building a compute infrastructure is costly and has probably not yet become a feasible option for them. The trend for these companies has been to outsource their compute capacity requirement to a third party, such as a managed cloud environment service, removing the overhead of internal maintenance.
Cloud-ready and cloud-certified EDA technology tools are essential for companies to successfully migrate their chip design and verification workflows to the cloud. Collaboration within the semiconductor ecosystem, including the end customer and CSPs, is paramount to providing tried and tested optimal cloud reference environment templates, architectures, and best-known methods.
Siemens EDA’s collaboration with CSPs offers customers various cloud solutions to make the cloud journey and adoption easier within these three categories. Let’s look at some of the options available.
The hybrid cloud model
Cloud-ready EDA tools must be optimized and flexible enough to handle a hybrid cloud environment and enable an appropriate portion of the chip design and verification workflows to run efficiently on the company’s on-premises compute clusters and on the cloud.
One reason why some large companies migrate to a hybrid cloud model is that they can still keep sensitive data in local compute cluster environments, eliminating the potential for security breaches of company IP or licensed third-party technology. Another is that the model allows them to capitalize on existing compute infrastructure and gain the flexibility to support custom flows.
Integration of the workflows for a hybrid environment must support interaction between the data retained on-premises and the data placed in the cloud. For example of a GUI-driven interactive circuit design and simulation workflow shown in Figure 2, considerations must include key building blocks – such as the simulation job scheduler and job management – to allow the designer to augment their on-premises work seamlessly with cloud resources during peak simulation workloads.
Moreover, an optimal data transfer latency during downloading and viewing of simulation results is a crucial metric for acceptance of a hybrid cloud workflow. Most companies prefer to build a custom hybrid cloud flow that meets their specific requirements with automation provided by the EDA vendor. Siemens EDA’s cloud solution portfolio provides a Siemens-managed cloud service for a turnkey design environment and scalable computing.
Flexible access to EDA licenses
A company’s requirement for which EDA license access to use in the cloud will vary based on business and operational goals and the services and products that the company delivers to their end customer. A common theme is a flexible and granular access based on existing EDA license configurations to specifically address peak demand at various stages in the chip design cycle – with minimal disruption. Ultimately, the license models should be flexible enough to seamlessly allow chip design teams to use on-premises and peak-demand licenses in congruence.
It is imperative that chip design companies, EDA solution providers and CSPs collaborate to make any cloud migration successful. An upfront assessment to determine the cloud environment and model that best fits a semiconductor company’s requirements is crucial. As a trusted advisor, Siemens EDA has collaborated with chip design and verification companies and with CSPs to provide cloud-ready products and solutions to help deliver scalable performance for peak capacity needs, ease cloud adoption, and maximize productivity. Click the link to learn more about the Siemens EDA Cloud solution portfolio.