Amazon Lab126 also uses Amazon FSx for Lustre for the most I/O-intensive workloads and AWS Backup to make the cluster more fault-resilient. It relies on Amazon Elastic Block Store (Amazon EBS) and Amazon Elastic File System (Amazon EFS) for data storage. The new framework integrates and simplifies compute-heavy Amazon Elastic Compute Cloud (Amazon EC2) instances with a fast network backbone, unlimited storage, and budget and cost management. In 2018, Amazon Lab126 built a flexible HPC reference framework on AWS, which replaces its on-premises HPC solution and enables an AWS-based, multi-user R&D environment for scale-out workloads such as HPC and machine learning. “We also trusted AWS to own our compute and host our data.” “We evaluated third-party HPC services, but AWS ultimately offered the best technology in terms of scalability and flexibility of compute instance types,” says Crozes. To address its internal customer needs, the Amazon Lab126 team chose to create a new cloud HPC environment on Amazon Web Services (AWS) in late 2017. We didn’t have the ability to launch new HPC clusters for each team when they needed them.” We wanted to centralize HPC resources so each team could access their own environment on demand. Mickael Crozes, senior system/software developer engineer for Amazon Lab126, says, “Different teams have different compute capacity needs, and we lacked the flexibility to accommodate them all. Self-service capability was an important requirement to support these diverse teams. “We needed more compute capacity to support these workloads.” Amit Gaikwad, senior manager of wireless engineering for Amazon Lab126, adds, “We were architecting and building more customer-facing solutions, and the on-premises HPC environment didn’t give us the scalability and speed we needed.”Īmazon design and engineering teams perform simulation and modeling on a range of applications such as computational fluid dynamics, finite element analysis, electronic design automation, and computational electromagnetics. “We run large simulations with long runtimes, such as looking at mechanical and thermal responses of consumer devices under certain conditions,” says Shankar Ganapathysubramanian, senior manager of the architecture team at Amazon Lab126. However, its aging, costly, on-premises HPC environment could not deliver the scalability and ease of use the teams required. The California-based research and development organization has created such high-profile devices as the Amazon Kindle e-reader and the Amazon Echo smart speaker.Īmazon Lab126 Devices teams use high-performance compute (HPC) capacity and machine learning capabilities to scale design environments to accelerate product development, gain efficiencies, and speed time-to-market. Some of today’s most popular consumer technology devices were born at Amazon Lab126.
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