Topic 1 Question 646
A solutions architect needs to host a high performance computing (HPC) workload in the AWS Cloud. The workload will run on hundreds of Amazon EC2 instances and will require parallel access to a shared file system to enable distributed processing of large datasets. Datasets will be accessed across multiple instances simultaneously. The workload requires access latency within 1 ms. After processing has completed, engineers will need access to the dataset for manual postprocessing.
Which solution will meet these requirements?
Use Amazon Elastic File System (Amazon EFS) as a shared file system. Access the dataset from Amazon EFS.
Mount an Amazon S3 bucket to serve as the shared file system. Perform postprocessing directly from the S3 bucket.
Use Amazon FSx for Lustre as a shared file system. Link the file system to an Amazon S3 bucket for postprocessing.
Configure AWS Resource Access Manager to share an Amazon S3 bucket so that it can be mounted to all instances for processing and postprocessing.
ユーザの投票
コメント(3)
- 正解だと思う選択肢: C
Amazon FSx for Lustre is a fully managed, high-performance file system optimized for HPC workloads. It is designed to deliver sub-millisecond latencies and high throughput, making it ideal for applications that require parallel access to shared storage, such as simulations and data analytics.
👍 5potomac2023/11/07 - 正解だと思う 選択肢: C
high performance computing (HPC) workloads, shared file system= Amazon FSx for Lustre
👍 2TariqKipkemei2023/12/04 - 正解だと思う選択肢: C
EFS could meet the latency requirement for most (!) read (!) operations, but this is not enough here. FSx for Lustre ist specifically designed for HPC.
👍 1pentium752024/01/02
シャッフルモード