AWS HPC Blog
Tag: AWS Batch
Scalable and Cost-Effective Batch Processing for ML workloads with AWS Batch and Amazon FSx
Batch processing is a common need across varied machine learning use cases such as video production, financial modeling, drug discovery, or genomic research. The elasticity of the cloud provides efficient ways to scale and simplify batch processing workloads while cutting costs. In this post, you’ll learn a scalable and cost-effective approach to configure AWS Batch Array jobs to process datasets that are stored on Amazon S3 and presented to compute instances with Amazon FSx for Lustre.
Read MoreReader Question: What is the difference between canceling and terminating a job in AWS Batch?
A customer asked us what is the difference between the CancelJob and TerminateJob API calls in AWS Batch. This post provides an overview of AWS Batch job states, and how these two API calls effect the job requests that you have submitted.
Read MoreIntroducing support for per-job Amazon EFS volumes in AWS Batch
Large-scale data analysis usually involves some multi-step process where the output of one job acts as the input of subsequent jobs. Customers using AWS Batch for data analysis want a simple and performant storage solution to share with and between jobs. We are excited to announce that customers can now use Amazon Elastic File System (Amazon […]
Read MoreWelcome to the AWS HPC Blog
This post is written by Deepak Singh, Vice President of Compute Services. At AWS, we love working with customers to solve their toughest challenges. High performance computing (HPC) is one of those challenges that pushes against the boundaries of AWS performance at scale. HPC is also a personal interest of mine, as I came to […]
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