What Is Electronic Design Automation (EDA)?

Electronic design automation (EDA) refers to a category of tools used for designing electronic systems like integrated circuits and printed circuit boards. These tools help engineers with the entire design process, from conceptualization and design specification to layout and verification. EDA plays an incredibly important role in managing the complexity of modern electronic systems, enabling the design of computer chip circuitry that would be impractical, if not impossible, to create manually.

Why Is EDA Important?

EDA plays a very important role in semiconductor design, assisting with:

Reducing Complexity

Modern electronic systems, particularly integrated circuits and printed circuit boards are incredibly complex. EDA tools allow engineers to manage this complexity, enabling the design and manufacture of advanced systems that would be impossible to create manually.

Time and Cost Efficiency

EDA significantly reduces the time required to design and verify electronic systems. Automation of many design steps reduces the time to market and lowers the overall cost by minimizing the need for physical prototypes and repeated design iterations.

Accuracy and Reliability

EDA tools help detect and correct errors early in the design process, ensuring that the final product meets the required specifications and performance standards.

Optimization

EDA tools help optimize designs for various parameters such as performance, power consumption, and area. This optimization is crucial for meeting the stringent requirements of modern electronic devices, especially in fields like mobile computing, automotive electronics, and high-performance computing.

Verification and Testing

Ensuring that a design works correctly is a critical part of the design process. EDA tools provide robust simulation, verification, and testing capabilities, allowing designers to verify functionality, timing, and power consumption before manufacturing. This reduces the risk of costly post-manufacturing errors.

Innovation and Scalability

EDA tools enable innovation by allowing designers to experiment with new architectures and technologies. They also support design scalability, making it easier to create larger and more complex systems as technology advances.

Standardization and Reuse

EDA facilitates the use of standardized design practices and reusable design components. This promotes efficiency and consistency across different projects and teams, leading to higher productivity and better quality control.

Industry Requirements

Industries like automotive, aerospace, and consumer electronics rely heavily on EDA tools to meet their specific design and manufacturing requirements. EDA tools help companies comply with industry standards and regulations by helping them enforce design rules, verify compliance with specifications, and ensure the accuracy and reliability of electronic systems. These tools also automate the verification process against standards around signal integrity, electromagnetic interference, and thermal performance, reducing the risk of non-compliance and facilitating certification processes.

Types of EDA Tools

EDA works via a variety of tools that fall into three main categories: simulation, verification, and design.

Simulation tools simulate the behavior of electronic designs to verify functionality and performance before physical prototypes are made.

Simulation tool types include:

• Functional simulation, which tests the logical correctness of the design
• Timing simulation, which verifies that the design meets timing constraints and performance requirements
• Analog simulation, which simulates analog circuits to verify their behavior over time

Verification tools ensure that the design meets all specifications and constraints through various methods.

Verification tool types include:

• Formal verification mathematically proves the correctness of the design.
• Static timing analysis checks the design for timing violations without simulating its behavior.
• Power analysis evaluates the power consumption of the design to ensure it meets power budgets.
   

Finally, design tools automate component placement and connection routing to optimize performance, area, and power consumption while ensuring compliance with design rules.

Design tool types include:

• Design-for-test tools, which help designers incorporate testability features into their designs, making it easier to test and diagnose faults in manufactured hardware.
• Analog/mixed-signal design tools, which are tailored for designing and simulating analog and mixed-signal circuits.
• System-level design tools, which enable designers to work at a higher abstraction level, modeling and simulating entire systems to evaluate their performance and interaction before detailed design begins.

EDA products are usually software, but hardware is commonly used when companies require extremely high performance.

EDA Trends and Challenges

EDA tools rely on data to function well, and like all other data-related tools, EDA tools often face challenges around the sheer amount and variety of data coming at them at all times.

These challenges then transfer over to the EDA manufacturer and vendors in the form of:

• Slower time to market due to builds and regressions taking too long 
• Management complexity and a resulting lack of productivity due to IT teams being resource-constrained
• Increasing costs from application infrastructures that still run on legacy storage, which doesn’t have the capacity for EDA workloads

These challenges are changing the face of EDA as we know it, leading EDA manufacturers and vendors to rethink how they do things.

And you also have to factor in certain trends.

AI and EDA 

The biggest trend in EDA right now is the incorporation of AI, which is leading to other challenges.

AI-augmented electronic design automation (EDA) workflows demand variable storage performance during design verification. Overburdened storage can lead to delays, hindering development processes. Additionally, AI operations and intensive GPU usage increase data center footprint and power consumption, driving up costs due to rack space overages and risking service interruptions. Traditional data center infrastructures struggle to support the dynamic workloads required by modern AI-driven applications.

In light of all this, IT departments are now spending more as their infrastructure gets overprovisioned to achieve higher scalability. Sub-10nm chip design is now the standard, but this process generates a massive amount of files during different phases of the workflow. These files require high-performance and high-capacity data storage. Also, verification and simulation job completion times have become unpredictable, design complexity is increasing, and design workloads are run in hybrid cloud environments.

All this is creating a perfect storm that demands a new way to look at how EDA companies store and manage their data.

Related reading: Boosting the Power of EDA Workloads on a Modern Data Platform

Pure Storage and EDA

Companies like Silicon Labs use Pure Storage for a reason: We know our way around the above-mentioned EDA challenges. Pure Storage® FlashBlade//S™ accelerates EDA builds, regressions, and tapeout cycles by running more semiconductor design projects in parallel.

FlashBlade’s modular architecture lets you add storage or compute independently and on demand with maximum performance per rack space, leading to higher scalability and eliminating overprovisioning.

FlashBlade® enables you to cut job completion times in half so you can run more projects and get maximum value from your software tool licenses, lowering total cost and reducing time to market.

Learn more about how Pure Storage helps you accelerate chip design and delivery and minimize EDA costs.