Amazon Technologies, Inc.

Rajankumar Singh

Swaminathan Sivasubramanian

Nafea Bshara

Sudipta Sengupta

Leo Parker Dirac

Andrea Olgiati

Rahul Sharma

Poorna Chand Srinivas Perumalla

Matthew James Wood

David Robert Thomas

Dominic Rajeev Divakaruni

Sandeep Krishnamurthy

Bratin Saha

Jalaja C Kurubarahalli

Pragya Agarwal

Lai Wei

Karan Hemant Kothari

Samuel Oshin

Cory Pruce

Jun Wu

Eftiquar Shaikh

Daniel Evans

Umang Wadhwa

Mark Klunder

Aaron Markham

Zdravko Pantic

Techniques for partitioning data flow operations between execution on a compute instance and an attached accelerator instance are described. A set of operations supported by the accelerator is obtained. A set of operations associated with the data flow is obtained. An operation in the set of operations associated with the data flow is identified based on the set of operations supported by the accelerator. The accelerator executes the first operation.

Framework integration for instance-attachable accelerator

Techniques are described for using machine learning (ML) models to create information technology (IT) infrastructures at a service provider network based on image of IT system architecture diagrams. To create IT system architecture diagrams, system architects often use tools ranging from pen and paper and whiteboards to various types of software-based drawing programs. Based on a user-provided image of an IT system architecture diagram (for example, a digital scan of a hand drawn system diagram, an image file created by a software-based drawing program, or the like), a service provider network uses one or more ML models to analyze the image to identify the constituent elements of the depicted IT system architecture and to create an infrastructure template that can be used to automatically provision corresponding computing resources at the service provider network.

Provisioning information technology (IT) infrastructures based on images of system architecture diagrams

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San Jose, CA, United States of America

Rajankumar Singh