Introduction:
In the dynamic world of electronic design, engineers and designers are continually seeking innovative solutions to streamline their workflows and enhance collaboration. A notable trend in recent years is the increasing adoption of cloud-based Electronic Design Automation (EDA) tools among designers.
These cloud-based platforms offer a range of benefits that traditional on-premises software struggles to match. From improved accessibility and scalability to enhanced collaboration and cost-effectiveness, designers are finding compelling reasons to embrace cloud-based EDA tools. In this article, we explore four key reasons driving this shift and how it is reshaping the landscape of electronic design.
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How Cloud-Native EDA Tools Propel Semiconductor Innovation
In recent years, many semiconductor companies have successfully shifted chip design from on-premises data centers to the cloud. With monolithic Systems on chips (SoCs) and multi-die systems becoming ever more complex, chip designers increasingly rely on “unlimited” cloud resources and new cloud-native, AI-driven EDA tools to rapidly optimize power, performance, and area (PPA).
Industry experts identified the following four trends driving the rapid migration of EDA tools and chip design workloads to the cloud:
- Ever-increasing compute demands
- Accelerated time-to-market requirements
- Evolving cyber threats and stringent security protocols
- A growing need for more flexible, cost-effective storage options
Read on to get an in-depth look at how cloud-native EDA tools are empowering semiconductor companies to accelerate their chip design cycles.
Meeting EDA Compute Demands in the Cloud
In the semiconductor industry, scaling up in the cloud offers significant benefits for chip design workloads. Ansys, a leading player in this space, harnesses high-performance computing (HPC) to run complex simulations that enable semiconductor companies to analyze electrical and thermal interactions for billions of instances in SoCs and multi-die systems. However, these simulations require massive parallel processing power, typically provided by GPU clusters and large shared memory pools. Accessing this infrastructure in the cloud allows customers to pay for resources as needed and benefit from the latest hardware upgrades.
Similarly, Arm, a major player in chip design, highlights the immense compute power required for designing and verifying new chips. The cloud provides a practical solution for obtaining this compute capacity while reducing the global data centre footprint. Over 50% of Arm’s electronic design automation (EDA) workloads now take place in the cloud, enabling engineers to scale up and efficiently run hundreds of thousands of concurrent jobs.
Additionally, EDA vendors are using sophisticated machine learning models to optimize cloud-based chip design, aiding semiconductor companies in achieving their performance, power, and area (PPA) targets efficiently.
There are several reasons why chip designers are increasingly turning to cloud-based Electronic Design Automation (EDA) tools:
On-demand scalability: Cloud computing offers vast pools of computing resources that can be accessed and scaled up or down as needed. This is crucial for chip design, which can involve running complex simulations that require significant processing power. In contrast, traditional on-premise EDA tools can be limited by the physical hardware available, making it difficult to scale up for large projects. https://www.synopsys.com/blogs/chip-design/eda-cloud-predictions-2024.html
Faster time-to-market: Cloud-based EDA tools can help designers get their chips to market faster by enabling them to run simulations and other design tasks concurrently. This is because cloud platforms can provide access to a much larger number of compute resources than what is typically available on-premise.
Reduced costs: The cost of EDA tools and the underlying hardware can be significant. Cloud-based EDA tools can help to reduce these costs by eliminating the need for upfront capital expenditures on hardware and software licenses. Additionally, cloud providers typically offer pay-as-you-go pricing models, which allow companies to only pay for the resources they use.
Enhanced security: Cloud providers invest heavily in security measures to protect their infrastructure. This can give chip designers peace of mind knowing that their intellectual property is safe. Additionally, cloud platforms can offer features such as version control and disaster recovery that can help to protect design data.
Access to the latest tools: Cloud-based EDA tools are typically delivered as a service (SaaS), which means that the software is always up-to-date. This ensures that designers have access to the latest features and bug fixes.
Read More: 5 Jobs That Will Be Majorly Affected by AI in The Next 5 Years – techovedas
1. Accelerating Chip Design and Time to Market
Time to market refers to the duration it takes (for a company) from conceptualizing a product and to finally launching it in the market. Moreover,Using cloud EDA tools accelerates time to market for semiconductor companies by leveraging high-performance computing resources and optimized software environments.
Additionally,Cloud-based solutions offer scalability and flexibility, allowing companies to efficiently manage compute-intensive workloads without the constraints of traditional on-premises infrastructure.
In a bid to accelerate chip design and verification, improve time-to-market for next-gen silicon, and harness high-performance computing (HPC) workloads, AMD integrates its EPYC processors into cloud-driven EDA processes, notably in Microsoft Azure HBv4-series virtual machines. Additionally, this includes diverse tasks like rendering, computational geoscience, and financial risk analysis. Leveraging Microsoft Azure optimizes and streamlines AMD’s chip development software environment, thereby enhancing operational efficiency.
Read more 3 Key Trends for Electronic Design Automation (EDA) in the Cloud in 2024 – techovedas
2. Addressing Cybersecurity Concerns
Semiconductor companies once viewed security as a major barrier to adopting cloud-based workflows. However, with substantial investments from cloud providers like Microsoft in building advanced cybersecurity centres, the perception of cloud-based security has shifted.
Cloud vendors, including Microsoft Azure, maintain robust security protocols. These measures include meticulous documentation and implementation of stringent security processes to safeguard sensitive data and intellectual property. Additionally, cloud providers offer compliance with strict international security protocols, ensuring the protection of sensitive information even for highly regulated industries like semiconductor manufacturing.
TSMC’s Open Innovation Platform® Virtual Design Environment (OIP VDE), which enables customers to securely design silicon on Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform. Moreover, it works closely with its EDA partners like Synopsys to ensure its OIP VDE-based EDA tools and customer data—such as process technology files, process design kits (PDKs), foundation IP, and reference flows—are stored and protected in highly secure environments.
3. Accessing Secure, Flexible, and Cost-Effective Storage
Ronen Schwartz, SVP and GM of Cloud Storage at NetApp, affirmed that security concerns are no longer a hindrance to cloud adoption, as the cloud offers secure and flexible storage options. Such as, the opposite is now true, as companies choose the secure capabilities of the cloud to store and archive sensitive data that must remain immutable. Many organizations are implementing a hybrid cloud models i.e. certain applications and workloads moving to the cloud while other tools and workflows remain on-premises.
As new process nodes lead to an explosion of chip design data (3nm processes require four times the storage capacity and computation capabilities of 5nm) the cloud is helping semiconductor companies efficiently meet demands for more secure, flexible, and cost-effective storage options.
Cloud-based storage will continue to evolve as new AI/ML tools further optimize data retrieval and help customers manage costs in real time. Ultimately, storage will be as easy to navigate as driving with a GPS.
Conclusion
The transition to cloud-based EDA tools marks a significant paradigm shift in the semiconductor industry. By leveraging cloud resources, companies can address compute demands, accelerate chip design cycles, mitigate cybersecurity risks, and efficiently manage data storage. Such as technology continues to advance, cloud-based solutions are expected to play an increasingly vital role in driving innovation and shaping the future of semiconductor design.
