Amazon Technologies, Inc.

University of California

University of Washington

James Michael Thompson

Marc John Brooker

Danny Wei

Marc Stephen Olson

Benjamin Arthur Hawks

John Luther Guthrie, Ii

Christopher Magee Greenwood

Kerry Quintin Lee

Surya Prakash Dhoolam

Jianhua Fan

Nandakumar Gopalakrishnan

David R Richardson

Anthony Nicholas Liguori

Norbert Paul Kusters

Jiahua He

Nachiappan Arumugam

Mitchell Gannon Flaherty

John Michael Rauser

John Robert Smiley

John Luther Guthrie

Sonali Roy

Valentin Gabriel Priescu

Jeevan Shankar

Fnu Amit Anand Amleshwaram

Dragos Diaconescu

David Baker

James Liao

Igor A Kostic

Colin Harrison Brace

Bhavesh Anil Doshi

Gary Michael Herndon

Justin Bloomfield Siegel

Kristina Kraemer Brenneman

Ganesh Viswanathan

Vaibhav Sharma

Wai Shun Mak

Steve Bertolani

Stephen Tran

Ryan Marcheschi

Anandh Mahalingam

Norbert P Kusters

Ii John Luther Guthrie

Methods, systems, and computer-readable media for a service for managing quantum computing resources are disclosed. A task management service receives a description of a task specified by a client. From a pool of computing resources of a provider network, the service selects a quantum computing resource for implementation of the task. The quantum computing resource comprises a plurality of quantum bits. The service causes the quantum computing resource to run a quantum algorithm associated with the task. The service receives one or more results of the quantum algorithm from the quantum computing resource.

Service for managing quantum computing resources

A data storage manager may manage storage locations for blocks of a storage volume. The blocks of the storage volume may be assigned to a logical volume exposed to a computing instance supported by a host. Furthermore, the data storage manager may also generate and maintain a set of rules that specify the locations of blocks of the storage volume, and provides the set of rules to the host. The set of rules may be included in a data structure enabling the host to access the blocks based at least in part on the information included in the set of rules.

Enabling host computer systems to access logical volumes by dynamic updates to data structure rules

A distributed system may implement identifying correlated workloads for resource allocation. Resource data for resources hosted at resource hosts in a distributed system may be analyzed to determine behavioral similarities. Historical behavior data or resource configuration data, for instance, may be compared between resources. Behaviors between resources may be identified as correlated according to the determined behavioral similarities. An allocation of one or more resource hosts in the distributed system may be made for a resource based on the behaviors identified as correlated. For instance, resources may be migrated from a current resource host to another resource host, new resources may be placed at a resource host, or resources may be reconfigured into different resources. Machine learning techniques may be implemented to refine techniques for identifying correlated behaviors.

Identifying correlated resource behaviors for resource allocation

A block-based storage system may implement page cache write logging. Write requests for a data volume maintained at a storage node may be received at a storage node. A page cache for may be updated in accordance with the request. A log record describing the page cache update may be stored in a page cache write log maintained in a persistent storage device. Once the write request is performed in the page cache and recorded in a log record in the page cache write log, the write request may be acknowledged. Upon recovery from a system failure where data in the page cache is lost, log records in the page cache write log may be replayed to restore to the page cache a state of the page cache prior to the system failure.

Page cache write logging at block-based storage

Methods, systems, and computer-readable media for cloud-based simulation of quantum computing resources are disclosed. One or more classical computing resources are selected based at least in part on a quantum algorithm. The resources are selected by a quantum computing simulation service of a provider network. The quantum algorithm is executable using a quantum computing resource comprising a plurality of quantum bits. The one or more classical computing resources are selected from a pool of computing resources of the provider network. The quantum algorithm is simulated using the one or more classical computing resources.

Cloud-based simulation of quantum computing resources

Aspects relate to techniques for using read-only volume replicas in a distributed computing environment to enable over-subscription on server performance. In order to provide a good customer experience, the I/O handling replicas of a volume are typically reserved at a high percentage of the customer's desired performance. A read-only replica of the volume does not serve user I/O, and can therefore be reserved at a much lower percentage of desired performance. Particularly, as the number of read-only replicas increases, the performance reservation can be lowered due to the statistical likelihood that the server(s) hosting at least one read-only replica will have sufficient performance to support the desired reads during new volume creation (even though that performance has not been fully reserved). Aspects relate to techniques for selecting among read-only replicas to serve reads during creation of a new volume copy.

Utilizing mutiple snapshot sources for creating new copy of volume in a networked environment wherein additional snapshot sources are reserved with lower performance levels than a primary snapshot source

Notice of migration of a portion of a data volume from a first location to a second location is received by a first computer system from a second computer system, where the data volume is separated over a network from the first computer system. A third computer system, separated over a network from the first computer system, is caused to invalidate a mapping between the portion and the first location. An indication that the third computer system seeks access to the portion is identified. A third computer system is enabled, by providing a mapping between the portion and the second location, to access portion at the second location.

Rule invalidation for a block store management system

2-ketoacid decarboxylase enzymes, compositions encoding for 2 ketoacid decarboxylase enzymes, and host cells comprising such enzymes or compositions are provided.

Discovery of enzymes from the alpha-keto acid decarboxylase family

Methods, systems, and computer-readable media for cloud-based access to quantum computing resources are disclosed. A classical computing instance is launched based at least in part on a request. The computing instance is launched by a control plane of a provider network. A quantum computing resource is accessible to the computing instance and is selected based at least in part on input from a user associated with the request. The quantum computing resource is implemented in the provider network and comprises a plurality of quantum bits. A quantum algorithm is run on the quantum computing resource.

Cloud-based access to quantum computing resources

First information about regions of storage space in a storage environment available for a volume is provided to a service provider, with the storage environment being external to the service provider. The service provider is notified that information usable to locate a storage destination of a portion of the volume is unavailable. Second information that includes the storage destination in the storage environment is obtained from the service provider. A data operation is performed at the storage destination, with the storage destination determined based at least in part from the second information.

Block store management for remote storage systems

Placement decisions can be made for data storage volumes based at least in part upon the requirements of the storage volumes and the capabilities of the types of hardware available to host those volumes. There may be multiple types of hardware capable of supporting a volume, and the placement can be biased to hardware capable of supporting fewer types of storage volumes in order to ensure sufficient capacity for the various types of storage volumes. A consistent level of performance can also be provided independent of the type of hardware utilized. Hardware can be selected to host a volume that is able to satisfy various volume requirements, and the operation can be adjusted to ensure that the volume requirements are satisfied over time.

Managing volume placement on disparate hardware

A distributed system may implement opportunistic resource migration to optimize resource placement. Resources may be placed amongst different resource hosts of a distributed system. An evaluation of the current placement may be performed according placement criteria that improve placement of the resources at the distributed system. Based on the evaluation, the prospective migration of resources that exceed an improvement threshold may be identified as candidate resources to migrate. Migration for the candidate resources may be opportunistically performed. In some embodiments, a priority may be assigned to the candidate resources according to which the candidate resources are selected for performing migration.

Opportunistic resource migration to optimize resource placement

A remote data storage service may operate one or more storage servers configured to maintain logical volumes on behalf of customers of the remote data storage service. Historical data associated with customer interaction with the logical volumes may be obtained by the remote data storage service. One or more probability models may be generated to evaluate various different configurations of the storage servers. The various configurations of the storage servers may be simulated using the one or more probability models and an optimal configuration may be determined.

Simulating storage server configurations

Methods, systems, and computer-readable media for a development environment for programming quantum computing resources are disclosed. A development environment receives information associated with a quantum algorithm. A quantum computing resource is selected for implementation of the quantum algorithm based at least in part on one or more metrics analyzed by the development environment. The quantum computing resource comprises a plurality of quantum bits and is selected from a pool of computing resources of a provider network. A program executable on the quantum computing resource is generated based at least in part on the information associated with the quantum algorithm.

Development environment for programming quantum computing resources

Growing community of inventors

Seattle, WA, United States of America

James Michael Thompson