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There's been a lot of growth in the electronic design automation (EDA) industry, which is essential to the success of the semiconductor and electronic systems industries. With more companies designing their own chips and electronics, what does the future of electronic design automation hold? Here we’ll discuss growing trends in EDA, including cloud adoption.
The use of artificial intelligence (AI) and machine learning (ML) technology is growing rapidly due to many new applications. The result is chip makers need to produce more complex integrated circuits (ICs) like CPUs and GPUs with hundreds of cores, terabytes of memory, and multiple high-speed communication channels. They also require increasingly sophisticated EDA tools.
Furthermore, developers often identify a need to build dedicated logic and algorithms to optimize AI performance without compromising power consumption. EDA tools need to work with higher abstraction levels to get the right AI architecture.
While EDA can help with AI solution design, AI can also improve EDA tools. Recently, EDA vendors have begun integrating AI and ML into their EDA tools. ML can boost EDA performance because it requires large amounts of data to be effective, and EDA produces large amounts of data.
A shift toward domain-specific architectures is spawning a scramble among EDA tool vendors to simplify and optimize existing methodologies and tools. There's a push for architectures optimized for hyper-scale computing, automotive, mobile, communications, aerospace/defense, industrial, and medical applications.
Domain-specific design, also known as design for context, is driven by increased system complexity, performance and cost tradeoffs, and shortened development cycles. To address these issues, EDA vendors and users see closer collaboration in the ecosystem from developers of components, subsystems, and systems to address integration challenges and optimize performance.
Several opportunities and challenges for EDA tool providers are associated with this trend.
As part of design-for-context, EDA vendors should form closer partnerships and interoperability between EDA, computer-aided design, and computer-aided engineering tools. For increased productivity, EDA tools should be integrated with product lifecycle management systems, and simulation and test processes should be improved.
There is also a growing trend in EDA to use cloud computing. To increase productivity, chip makers are increasingly turning to the cloud.
Chip design works best with cloud computing in areas with limited computing resources. In large-scale verification projects, brute-force computation may precede human expertise and skills.
Developing tools and methodologies to handle rising computational demands and shorter design cycles have become increasingly important. Chip companies and designers will increasingly use cloud-based tools and techniques to keep up with chip and system design innovations.
Public cloud deployments offer scalability, elasticity, and HPC and a wide range of collaboration, performance, and project management tools.
Cloud computing provides scalable, elastic computing cycles and storage with virtually unlimited capacity. In addition, chip makers can maintain a certain baseline of storage and computing capabilities on-premises while using public clouds for burst workloads and higher-demand phases, such as validation.
In times of high demand, engineering teams have immediate access to computing, storage, and analytics. Rather than keeping idle servers until the next surge, the teams can return capacity to the cloud service provider (CSP).
With 草榴社区 Cloud, you'll be able to do more with cloud-based EDA than ever before.
Their cloud-based metering technology enables you to run unlimited parallel and regression jobs on-demand, making results available in minutes instead of weeks. No matter how much demand there is, everything is always available.
With unlimited EDA licenses on demand, you can manage the tools and compute resources you need without traditional licensing restrictions.
草榴社区 values the security and privacy of your data and IP. 草榴社区 Cloud ensures complete data isolation and encryption in transit and at rest for each deployment. The software integrity platform identifies and eliminates vulnerabilities in code before each release is enabled.
The security measures include multi-factor authentication, role-based access, a dedicated network with workload protection, vulnerability management, and round-the-clock incident response.
By leveraging 草榴社区’ innovative technology, small and medium-sized businesses can maximize their electronic design automation workflows and efficiency.
草榴社区 is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With 草榴社区 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, 草榴社区 has reimagined the future of chip design on the cloud, without disrupting proven workflows.
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草榴社区 technology drives innovations that change how people work and play using high-performance silicon chips. Let 草榴社区 power your innovation journey with cloud-based EDA tools. Sign up to try 草榴社区 Cloud for free!
Sridhar Panchapakesan is the Senior Director, Cloud Engagements at 草榴社区, 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 草榴社区. 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.