Suppose you are trying to solve a problem of interest (e.g., portfolio optimization or machine learning), and you are given some classical data, neatly arranged into a matrix A. Your plan is to solve this problem using a quantum algorithm …
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Deep learning (DL) models have been increasing in size and complexity over the last few years, pushing the time to train from days to weeks. Training large language models the size of GPT-3 can take months, leading to an exponential growth …
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In this post, we describe how to orchestrate protein folding jobs on AWS Batch. We also compare the performance of OpenFold and AlphaFold on a set of public targets. Finally, we will discuss how to optimize your protein folding costs. Read …
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I am pleased to announce today the availability of Amazon File Cache, a new high-speed cache service on AWS designed for processing file data stored in disparate locations—including on premises. File Cache accelerates and simplifies your …
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In this post, we demonstrate how Kubeflow on AWS (an AWS-specific distribution of Kubeflow) used with AWS Deep Learning Containers and Amazon Elastic File System (Amazon EFS) simplifies collaboration and provides flexibility in training …
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In this post, we will provide an overview of Numerical Weather Prediction (NWP) workloads, and the AWS HPC-optimized services for it. We’ll test three popular NWP codes: WRF, MPAS, and FV3GFS. Read the Post on the AWS Blog Channel
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Amazon’s product search engine indexes billions of products, serves hundreds of millions of customers worldwide, and is one of the most heavily used services in the world. The Amazon Search team develops machine learning (ML) technology …
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AWS service teams continuously improve the underlying infrastructure and operations of managed services, and AWS Batch is no exception. The AWS Batch team recently moved most of their job scheduler fleet to a serverless infrastructure model …
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