A solutions architect must host a high performance computing (HPC) workload on hundreds of Amazon EC2 instances that require parallel access to a shared file system for distributed processing of large datasets. Multiple instances will access the datasets simultaneously. The workload requires access latency within 1 ms. After processing, engineers need access to the dataset for manual postprocessing. Which solution will meet these requirements?

Amazon FSx for Lustre is designed for high-performance computing (HPC) workloads, offering sub-millisecond latencies and high throughput, which is crucial for distributed processing of large datasets across hundreds of EC2 instances. It supports parallel access from multiple instances. Linking it to an Amazon S3 bucket allows for seamless data import/export and provides a durable, accessible location for engineers to perform manual postprocessing after the high-performance computation is complete. Amazon EFS is a shared file system but generally has higher latencies than FSx for Lustre, making it less suitable for the strict 1ms requirement of HPC. Mounting an S3 bucket directly as a file system is not a native or performant solution for parallel access and low-latency processing. AWS Resource Access Manager (RAM) is for sharing resources, not for mounting S3 buckets as a file system for HPC workloads.