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Amazon Braket launches Braket Pulse to develop quantum programs at the pulse level

When experimenting on a quantum computer, customers often need to program at the lower-level language of the device. Today, we are launching Braket Pulse, a feature that provides pulse-level access to quantum processing units (QPUs) from …

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AWS open-sources OQpy to make it easier to write quantum programs in OpenQASM 3

In September 2021, we announced that AWS would be joining the OpenQASM 3 Technical Steering Committee in an effort to establish a consistent, industry-wide approach for describing quantum programs. In that blog post we also shared our plans …

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Minimize HPC compute costs with all-or-nothing instance launching

In this post, we highlight a little-known configuration option for Slurm on @awscloud ParallelCluster that can reduce costs and increase your iteration speed by preventing idle batch instances from launching when EC2 capacity is limited. …

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BioContainers are now available in Amazon ECR Public Gallery

Today we are excited to announce that all 9000+ applications provided by the BioContainers community are available within ECR Public Gallery! You don’t need an AWS account to access these images, but having one allows many more pulls to the …

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Goldman Sachs and AWS examine efficient ways to load data into quantum computers

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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KEK's novel solution for CryoEM's software and infra (Part 2 of 4)

CryoEM is an awesome research tool, but it also comes with some challenges. The software stack is complex, and the hardware it needs is sometimes exotic and hard to get. Afterwards, there’s a massive dataset and a serious set of …

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Amazon EC2 Trn1 Instances for High-Performance Model Training are Now Available

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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The Challenges of CryoEM with our friends from KEK in Japan (Part 1 of 4)

CryoEM is an awesome research tool, but it also comes with some challenges. The software stack is complex, and the hardware it needs is sometimes exotic and hard to get. Afterwards, there’s a massive dataset and a serious set of …

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