Introduction – the need for randomness Random numbers are a crucial resource used throughout modern computer science. For example, in computation, randomized algorithms give efficient solutions for a variety of fundamental problems for …
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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 …
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By Fabio Sanches, Quantum Computing Services Lead, QC Ware In this post, I introduce you to QC Ware Forge, which is built on Amazon Braket. It provides turnkey quantum algorithms, so you can speed up research into applying quantum computing …
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By Michael Fischer, Chief of Innovation at Aioi Insurance Services USA, Daniel Brooks, Research Data Scientist formerly of Aioi Insurance Services USA, with AWS quantum solution architects Pavel Lougovski and Tyler Takeshita. This post …
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This post was written by Dario La Porta, AWS Professional Services Senior Consultant for HPC. Customers across a wide range of industries such as energy, life sciences, and design and engineering are facing challenges in managing and …
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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 …
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This post was written by Benjamin Meyer, AWS Solutions Architect When companies and labs start their high performance computing (HPC) journey in the AWS Cloud, it’s not only because they’re in search of elasticity and scale – they’re also …
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