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EDA workloads demand high IOPS and throughput from shared network storage. Additionally, running multiple EDA jobs in parallel requires a large amount of resources, more than on-premises environments can usually provide.

BlueXP solves these EDA challenges by combining the unlimited compute power of the cloud with highly performant NetApp storage solutions. Migrate or burst data to the cloud as needed. With BlueXP you don’t just optimize storage, you optimize the entire development cycle.

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Semiconductor Case Study Roundup: Leveraging Cloud Volumes ONTAP in the EDA Sector

Semiconductor case study after case study shows: Cloud Volumes ONTAP helps address the EDA industry’s performance, availability, and data protection needs.

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Build a unified hybrid storage infrastructure

Control all the ONTAP-based storage solutions serving your EDA workloads from a single, unified console.

  • Discover and manage data across your NetApp storage environments on-premises and in the cloud with Cloud Volumes ONTAP
  • Leverage fully managed ONTAP-based solutions that run on native cloud resources: Amazon FSx for NetApp ONTAP, Azure NetApp Files, and Cloud Volumes Service
  • Automate operations across environments with RESTful API calls
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Accelerate operations by bursting data to the cloud

Exceed on-premises performance limits by extending your deployment to the cloud.

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The caching mechanism only uploads the data needed in the cloud. Obsolete versions of tools and libraries are not transferred or cached

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Only relevant data is cached, reducing storage footprint by 90%

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Data is kept available across multiple environments with fewer data replications

Scale up while retaining the storage performance your EDA workloads require

Benefit from the cloud’s unlimited infrastructure resources natively integrated with NetApp’s scale-out storage performance.

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Fully managed cloud storage service options reduce management overhead

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ONTAP’s high parallelism, metadata operations, and IOPS make it highly performant for demanding EDA file workloads

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Storage and compute resources can be scaled as needed to meet the workload requirements