Last year, we outlined how Azure NetApp Files helped reshape silicon design by delivering the low-latency, high-throughput storage required for Electronic Design Automation (EDA) workloads at cloud scale. Since then, we have continued to extend performance and scalability. Today, we are advancing that progress with another significant step forward. Modern semiconductor design is defined by scale. Thousands of concurrent EDA jobs spanning simulation, synthesis, and verification run continuously against shared datasets, where even small variations in storage latency can ripple across entire design cycles. For many teams, this has historically limited how far EDA workflows could scale in the cloud. That constraint is now changing. Azure NetApp Files (ANF) is redefining what is possible for EDA in the cloud by delivering predictable, high-performance shared storage at massive concurrency. With new independent benchmark results and growing adoption by leading semiconductor companies, Azure is establishing itself as a viable—and in many cases superior—platform for modern EDA environments. See how Azure NetApp Files delivers scalable, high-performance storage for EDA Why EDA storage has been difficult to scale in the cloud EDA workloads combine three characteristics that have traditionally challenged cloud storage architectures: Extremely high concurrency, with thousands of jobs accessing shared file systems simultaneously. Strict latency sensitivity, where even minor delays reduce compute efficiency and extend runtimes. Intensive shared data access patterns, creating contention under load. While cloud compute scales easily, shared storage has often introduced variability that limits overall system efficiency. As concurrency increases, storage becomes the bottleneck, impacting regression cycles, increasing…
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