Azure NetApp Files for Next-Gen Silicon Design

Building silicon chips has never been simple, but today’s demands are on a completely different level. Every new chip design must push performance further while meeting stricter power efficiency standards. The problem? The sheer volume of data that chip design tools generate is massive—way beyond what traditional storage can handle. 

In the world of Electronic Design Automation (EDA), speed isn’t just nice to have—it’s the difference between staying ahead or falling behind. Engineers need storage that moves as fast as their ideas, something that won’t slow them down when running simulations or processing terabytes of data. This is exactly where Azure NetApp Files changes the game. 

Unlike legacy cloud storage, Azure NetApp Files provides the ultra-low latency, high-speed data access, and scalability that modern chip designers need. And with Microsoft integrating the latest Azure AI Foundry updates, Azure OpenAI Service, and even leveraging OpenAI’s GPT-4.5, silicon design is evolving faster than ever. The combination of AI-driven acceleration and next-gen cloud storage is helping companies redefine what’s possible—one breakthrough at a time.

Why Traditional Storage Can’t Keep Up with Chip Design 

Designing a microchip isn’t just complex—it’s an all-out data war. Every single iteration of a chip involves enormous simulations, verification processes, and testing phases, all of which generate staggering amounts of data. But here’s the catch: not all storage can handle that kind of load. 

Most cloud storage systems were built for general-purpose workloads, not for the extreme demands of Electronic Design Automation (EDA). If you’ve ever waited for a simulation to finish, only to realize the bottleneck wasn’t your computing power but your storage, you know exactly what we’re talking about. 

The biggest challenges? 

• Slow access speeds: When engineers need to pull massive design files in real-time, delays of even a few milliseconds add up fast. Traditional storage just isn’t fast enough. 
• Throughput limits: EDA workloads don’t just store files—they constantly read and write data at high speeds. If the storage can’t keep up, everything drags. 
• Scaling headaches: Chip complexity keeps growing, but many cloud file systems struggle to scale efficiently. Expanding storage often means dealing with downtime, performance dips, or manual intervention. 
• Data chaos: Managing thousands—sometimes millions—of files, versions, and test results across a distributed team isn’t easy. Standard cloud storage lacks the tools to do this smoothly.

This is exactly why Microsoft developed Azure NetApp Files—a storage solution purpose-built for high-performance computing, capable of handling the punishing demands of silicon design. 

What EDA Workloads Demand from Infrastructure 

If there’s one thing engineers know about EDA, it’s that it’s a beast when it comes to computing and storage demands. From early-stage logic design to final physical layout, each phase of chip development involves heavy-duty simulation, verification, and optimization. And here’s the thing—every step generates massive amounts of data that must be processed at lightning speed. 

The more accurate the simulations, the fewer errors in production. This is why silicon engineers run multiple iterations, testing different configurations to fine-tune a chip’s Power, Performance, and Area (PPA). But all of this comes at a cost: traditional storage just can’t keep up with the sheer scale and complexity of these workloads. 

This raises an important question: what is a performance chip? Essentially, it is a semiconductor designed to handle high-speed, compute-intensive tasks, often found in AI accelerators, GPUs, and next-gen CPUs. These chips require an infrastructure that can match their speed—both in processing power and data access. That’s why storage solutions like Azure NetApp Files are critical. It ensures that engineers can move vast amounts of data without bottlenecks. 

To understand what’s really happening under the hood, EDA workloads are split into two categories: 

• Frontend Workloads – This is where the logic and functionality of the chip take shape. Think of it as the “brain” of the processor being designed. It involves running thousands of short, parallel jobs that continuously read and write data in unpredictable patterns across millions of tiny files. Speed and low-latency access are critical.
  
• Backend Workloads – Once the logic is nailed down, it’s time to translate it into a physical blueprint for manufacturing. This stage works with fewer, but much larger files, relying heavily on sequential read/write operations. Storage throughput and scalability become the key factors here.

Source: Microsoft 

Balancing both frontend and backend workload requirements is no easy task. That’s why benchmarking is crucial. The SPEC SFS benchmark, particularly the EDA_BLENDED workload test, provides a standardized way to measure how well different storage solutions perform under real-world EDA conditions. 

So, what’s the best storage solution to handle this complexity? That’s where Microsoft Azure NetApp Files comes in. 

Performance testing using the SPEC SFS EDA_BLENDED benchmark reveals just how powerful Azure NetApp Files are. The results show that it can achieve an impressive throughput of ~10 GiB/s while maintaining ultra-low latency of under 2 milliseconds, even when handling large volumes of data. This level of performance ensures that EDA workloads run smoothly without storage bottlenecks slowing down critical simulations and design processes. 

Source: Microsoft 

Microsoft’s Breakthroughs in Electronic Design Automation 

Microsoft is redefining silicon design by combining AI and cloud computing. To keep pace with Moore’s Law, it has optimized Azure for EDA, streamlining chip development and enabling faster, smarter design processes. 

This approach has been key to developing Microsoft’s custom silicon chips, including: 

• Azure Maia 100 AI Accelerator – Designed for AI and generative AI workloads. 
• Azure Cobalt 100 CPU – An Arm-based processor for general-purpose computing in Microsoft Azure. 
• Azure Integrated Hardware Security Module – Strengthens encryption and key management. 
• Azure Boost DPU – A high-efficiency data processing unit for data-intensive tasks.

Running EDA workflows on Azure gives Microsoft’s cloud hardware team: 

• Scalable high-performance computing for intensive workloads. 
• Optimized CPU pairing for each EDA tool. 
• AI-driven automation, accelerating semiconductor design.

These innovations extend beyond Microsoft—businesses can leverage Azure cloud management services to access the same cutting-edge infrastructure for their chip design needs. 

Accelerating Semiconductor Innovation with Azure NetApp Files 

Bringing a chip from concept to production demands lightning-fast storage, scalable computing, and high-performance data management. Azure NetApp Files is built to handle the intense requirements of semiconductor development, delivering unmatched speed, efficiency, and security. 

• Blazing-Fast Performance – Delivers up to 652,260 IOPS with ultra-low sub-2ms latency and reaches 826,000 IOPS at peak performance. 
• Scalability Without Limits – Supports up to 2PiB of storage and integrates seamlessly with compute clusters of 50,000+ cores. 
• Effortless Management – Simplifies deployment and operations through the Azure Portal or automation APIs. 
• Cost Optimization – Uses tiered storage to move inactive data to cost-effective Azure storage automatically, while reserved capacity plans offer savings over pay-as-you-go pricing. 
• Uncompromising Security – Provides enterprise-grade encryption, access controls, and data protection for semiconductor designs in transit and at rest.

In production environments, Azure NetApp Files powers some of the world’s most advanced EDA clusters, supporting Microsoft’s own chip development efforts with computing at an unprecedented scale. 

Conclusion

Chip design is a game of precision and speed. Without the right storage and compute infrastructure, even the most advanced high-performance computing systems can slow down under the weight of massive datasets and complex simulations. Azure NetApp Files changes the game by providing seamless scalability, ultra-fast high-performance data management, and enterprise-grade reliability—giving semiconductor engineers the edge they need. 

At DynaTech Systems being Microsoft Dynamics Partner, we help businesses harness the power of Azure to optimize their EDA workflows. Contact us today!