ABSTRACT
Abstract
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.
Description
This application is a continuation of U.S. patent application Ser. No. 15/814,304, filed Nov. 15, 2017, which are here incorporated by reference herein in its entirety.
BACKGROUND
Many companies and other organizations operate computer networks that interconnect numerous computing systems to support their operations, such as with the computing systems being co-located (e.g., as part of a local network) or instead located in multiple distinct geographical locations (e.g., connected via one or more private or public intermediate networks). For example, distributed systems housing significant numbers of interconnected computing systems have become commonplace. Such distributed systems may provide back-end services to servers that interact with clients. Such distributed systems may also include data centers that are operated by entities to provide computing resources to customers. Some data center operators provide network access, power, and secure installation facilities for hardware owned by various customers, while other data center operators provide âfull serviceâ facilities that also include hardware resources made available for use by their customers. As the scale and scope of distributed systems have increased, the tasks of provisioning, administering, and managing the resources have become increasingly complicated.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 A illustrates an example system environment for cloud-based access to quantum computing resources, including a classical computing instance within the same provider network as a quantum computing instance, according to one embodiment.
FIG. 1 B illustrates an example system environment for cloud-based access to quantum computing resources, including a virtual computing instance within the same provider network as a quantum computing instance, according to one embodiment.
FIG. 1 C illustrates an example system environment for cloud-based access to quantum computing resources, including a classical computing instance external to the provider network that hosts a quantum computing instance, according to one embodiment.
FIG. 1 D illustrates an example system environment for cloud-based access to quantum computing resources, including a data center that hosts a quantum computing instance, according to one embodiment.
FIG. 1 E illustrates an example system environment for cloud-based access to quantum computing resources, including a computing instance with a locally accessible quantum computing resource, according to one embodiment.
FIG. 2 A illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum computing instances of different instance types, according to one embodiment.
FIG. 2 B illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum computing instances with pre-loaded quantum algorithms, according to one embodiment.
FIG. 2 C illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum algorithms for use with quantum computing instances, according to one embodiment.
FIG. 2 D illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum algorithms with options for different initial configurations, according to one embodiment.
FIG. 3 A illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including reclamation of a quantum computing instance whose attachment to a classical computing instance has been terminated, according to one embodiment.
FIG. 3 B illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including reuse of a reclaimed quantum computing instance for attachment to another classical computing instance, according to one embodiment.
FIG. 4 A illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including an elastic quantum computing library that permits interaction between a classical computing instance and a quantum computing instance, according to one embodiment.
FIG. 4 B illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including an elastic quantum computing library that permits interaction between a classical computing instance and various types of accelerators, according to one embodiment.
FIG. 5 A and FIG. 5 B are a flowcharts illustrating methods for cloud-based access to quantum computing resources, according to one embodiment.
FIG. 6 illustrates an example system environment for a service for managing quantum computing resources, according to one embodiment.
FIG. 7 A illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service using a quantum computing resource to run a quantum algorithm with an initial configuration, according to one embodiment.
FIG. 7 B illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service using the quantum computing resource to run the quantum algorithm with a different initial configuration, according to one embodiment.
FIG. 7 C illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service using the quantum computing resource to run a different quantum algorithm, according to one embodiment.
FIG. 8 illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service aggregating the results of multiple runs of one or more quantum algorithms, according to one embodiment.
FIG. 9 illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service aggregating the results from a quantum computing resource and a classical computing resource, according to one embodiment.
FIG. 10 is a flowchart illustrating a method for using a service for managing quantum computing resources, according to one embodiment.
FIG. 11 A illustrates an example system environment for a development environment for programming quantum computing resources, according to one embodiment.
FIG. 11 B illustrates an example system environment for a development environment for programming quantum computing resources, including a development environment generating and sending a display to a client, according to one embodiment.
FIG. 11 C illustrates an example system environment for a development environment for programming quantum computing resources, including a development environment executable on a client computing device, according to one embodiment.
FIG. 12 illustrates further aspects of the example system environment for a development environment for programming quantum computing resources, including a repository of programming elements usable for building a quantum algorithm, according to one embodiment.
FIG. 13 A illustrates further aspects of the example system environment for a development environment for programming quantum computing resources, including testing variants of a quantum algorithm using different quantum computing resources, according to one embodiment.
FIG. 13 B illustrates further aspects of the example system environment for a development environment for programming quantum computing resources, including testing a quantum algorithm using both a quantum computing resource and a classical computing resource, according to one embodiment.
FIG. 14 is a flowchart illustrating a method for using a development environment for programming quantum computing resources, according to one embodiment.
FIG. 15 illustrates an example system environment for cloud-based simulation of quantum computing resources, according to one embodiment.
FIG. 16 illustrates further aspects of the example system environment for cloud-based simulation of quantum computing resources, including using classical computing resources of different instance types, according to one embodiment.
FIG. 17 illustrates further aspects of the example system environment for cloud-based simulation of quantum computing resources, including a catalog of quantum algorithms, according to one embodiment.
FIG. 18 illustrates further aspects of the example system environment for cloud-based simulation of quantum computing resources, including the use of a development environment to provide the quantum algorithm, according to one embodiment.
FIG. 19 is a flowchart illustrating a method for cloud-based simulation of quantum computing resources, according to one embodiment.
FIG. 20 illustrates an example computing device that may be used in some embodiments.
While embodiments are described herein by way of example for several embodiments and illustrative drawings, those skilled in the art will recognize that embodiments are not limited to the embodiments or drawings described. It should be understood, that the drawings and detailed description thereto are not intended to limit embodiments to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope as defined by the appended claims. The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word âmayâ is used in a permissive sense (i.e., meaning âhaving the potential toâ), rather than the mandatory sense (i.e., meaning âmustâ). Similarly, the words âinclude,â âincluding,â and âincludesâ mean âincluding, but not limited to.â
DETAILED DESCRIPTION OF EMBODIMENTS
Various embodiments of methods, systems, and computer-readable media for cloud-based access to quantum computing resources are described. Using the techniques described herein, quantum computing resources that are hosted âin the cloudâ can be accessed by client computing devices. The client devices may represent âclassicalâ (e.g., binary digital) computing devices that may seek to take advantage of the speed of quantum computing for solving particular problems. The client devices may be hosted inside or outside the same provider network that hosts the quantum computing resources. On request, a control plane may attach a quantum computing instance to a classical computing instance over a network. When a quantum instance is attached, the classical instance may have remote control of that quantum instance (exclusive of other classical instances) until the attachment is terminated. When the attachment is terminated, the quantum computing resource may be reclaimed and prepared for re-use by the same client or a different client at a later time. A particular quantum computing resource (e.g., a quantum computing instance) may be used and re-used by different client devices. Similarly, a particular client device may use different quantum computing resources over time. On request, a control plane of the provider network may provide access to a classical instance that includes or can locally access a quantum computing resource over an interconnect. A quantum computing instance may run a particular quantum algorithm with a particular initial configuration. The instance type of the quantum instance, the quantum algorithm, and/or the initial configuration may be selected by the client from a catalog. Different instance types may have different quantum computing characteristics such as the number or configuration of quantum bits. In one embodiment, a client may select an instance type that represents a template for solving a particular type of problem and that includes a pre-loaded quantum algorithm. In one embodiment, the elastic quantum computing service may recommend particular instance types, quantum algorithms, and/or initial configurations to a client, e.g., based on a specified problem domain or workload and to optimize speed, cost, or accuracy.
Various embodiments of methods, systems, and computer-readable media for a service for managing quantum computing resources are described. Using the techniques described herein, quantum computing resources that are hosted âin the cloudâ may be managed using a task management service. The task management service may receive task descriptions from clients and select and orchestrate computing resources, including quantum computing resources, to perform the tasks on behalf of the clients. The computing resources may be selected based (at least in part) on task descriptions and on performance metrics of prior tasks. The task management service may select appropriate computing resources, select and/or optimize quantum algorithms to implement a task, determine how many times to run a quantum algorithm, determine when to change the initial values for a quantum algorithm, determine when to run quantum algorithms or other operations, and otherwise perform intelligent management of computing resources. The computing resources managed by the task management service may also include classical computing resources such as computing devices and accelerators. In some embodiments, the task management service may use both quantum computing resources and classical computing resources to perform a particular task, e.g., where the different types of resources perform different portions of the task. In some embodiments, the task management service may use both quantum computing resources and classical computing resources to perform the same task, and the service may analyze the results to influence the selection of resources for future tasks. The task management service may introduce a layer of intelligent management of computing resources such that clients may delegate management of resources to the service.
Various embodiments of methods, systems, and computer-readable media for a development environment for programming quantum computing resources are described. Using the techniques described herein, clients may use a development environment to build programs executable on qu
This application is a continuation of U.S. patent application Ser. No. 15/814,304, filed Nov. 15, 2017, which are here incorporated by reference herein in its entirety.
BACKGROUND
Many companies and other organizations operate computer networks that interconnect numerous computing systems to support their operations, such as with the computing systems being co-located (e.g., as part of a local network) or instead located in multiple distinct geographical locations (e.g., connected via one or more private or public intermediate networks). For example, distributed systems housing significant numbers of interconnected computing systems have become commonplace. Such distributed systems may provide back-end services to servers that interact with clients. Such distributed systems may also include data centers that are operated by entities to provide computing resources to customers. Some data center operators provide network access, power, and secure installation facilities for hardware owned by various customers, while other data center operators provide âfull serviceâ facilities that also include hardware resources made available for use by their customers. As the scale and scope of distributed systems have increased, the tasks of provisioning, administering, and managing the resources have become increasingly complicated.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 A illustrates an example system environment for cloud-based access to quantum computing resources, including a classical computing instance within the same provider network as a quantum computing instance, according to one embodiment.
FIG. 1 B illustrates an example system environment for cloud-based access to quantum computing resources, including a virtual computing instance within the same provider network as a quantum computing instance, according to one embodiment.
FIG. 1 C illustrates an example system environment for cloud-based access to quantum computing resources, including a classical computing instance external to the provider network that hosts a quantum computing instance, according to one embodiment.
FIG. 1 D illustrates an example system environment for cloud-based access to quantum computing resources, including a data center that hosts a quantum computing instance, according to one embodiment.
FIG. 1 E illustrates an example system environment for cloud-based access to quantum computing resources, including a computing instance with a locally accessible quantum computing resource, according to one embodiment.
FIG. 2 A illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum computing instances of different instance types, according to one embodiment.
FIG. 2 B illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum computing instances with pre-loaded quantum algorithms, according to one embodiment.
FIG. 2 C illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum algorithms for use with quantum computing instances, according to one embodiment.
FIG. 2 D illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including a catalog that offers quantum algorithms with options for different initial configurations, according to one embodiment.
FIG. 3 A illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including reclamation of a quantum computing instance whose attachment to a classical computing instance has been terminated, according to one embodiment.
FIG. 3 B illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including reuse of a reclaimed quantum computing instance for attachment to another classical computing instance, according to one embodiment.
FIG. 4 A illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including an elastic quantum computing library that permits interaction between a classical computing instance and a quantum computing instance, according to one embodiment.
FIG. 4 B illustrates further aspects of the example system environment for cloud-based access to quantum computing resources, including an elastic quantum computing library that permits interaction between a classical computing instance and various types of accelerators, according to one embodiment.
FIG. 5 A and FIG. 5 B are a flowcharts illustrating methods for cloud-based access to quantum computing resources, according to one embodiment.
FIG. 6 illustrates an example system environment for a service for managing quantum computing resources, according to one embodiment.
FIG. 7 A illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service using a quantum computing resource to run a quantum algorithm with an initial configuration, according to one embodiment.
FIG. 7 B illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service using the quantum computing resource to run the quantum algorithm with a different initial configuration, according to one embodiment.
FIG. 7 C illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service using the quantum computing resource to run a different quantum algorithm, according to one embodiment.
FIG. 8 illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service aggregating the results of multiple runs of one or more quantum algorithms, according to one embodiment.
FIG. 9 illustrates further aspects of the example system environment for a service for managing quantum computing resources, including the service aggregating the results from a quantum computing resource and a classical computing resource, according to one embodiment.
FIG. 10 is a flowchart illustrating a method for using a service for managing quantum computing resources, according to one embodiment.
FIG. 11 A illustrates an example system environment for a development environment for programming quantum computing resources, according to one embodiment.
FIG. 11 B illustrates an example system environment for a development environment for programming quantum computing resources, including a development environment generating and sending a display to a client, according to one embodiment.
FIG. 11 C illustrates an example system environment for a development environment for programming quantum computing resources, including a development environment executable on a client computing device, according to one embodiment.
FIG. 12 illustrates further aspects of the example system environment for a development environment for programming quantum computing resources, including a repository of programming elements usable for building a quantum algorithm, according to one embodiment.
FIG. 13 A illustrates further aspects of the example system environment for a development environment for programming quantum computing resources, including testing variants of a quantum algorithm using different quantum computing resources, according to one embodiment.
FIG. 13 B illustrates further aspects of the example system environment for a development environment for programming quantum computing resources, including testing a quantum algorithm using both a quantum computing resource and a classical computing resource, according to one embodiment.
FIG. 14 is a flowchart illustrating a method for using a development environment for programming quantum computing resources, according to one embodiment.
FIG. 15 illustrates an example system environment for cloud-based simulation of quantum computing resources, according to one embodiment.
FIG. 16 illustrates further aspects of the example system environment for cloud-based simulation of quantum computing resources, including using classical computing resources of different instance types, according to one embodiment.
FIG. 17 illustrates further aspects of the example system environment for cloud-based simulation of quantum computing resources, including a catalog of quantum algorithms, according to one embodiment.
FIG. 18 illustrates further aspects of the example system environment for cloud-based simulation of quantum computing resources, including the use of a development environment to provide the quantum algorithm, according to one embodiment.
FIG. 19 is a flowchart illustrating a method for cloud-based simulation of quantum computing resources, according to one embodiment.
FIG. 20 illustrates an example computing device that may be used in some embodiments.
While embodiments are described herein by way of example for several embodiments and illustrative drawings, those skilled in the art will recognize that embodiments are not limited to the embodiments or drawings described. It should be understood, that the drawings and detailed description thereto are not intended to limit embodiments to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope as defined by the appended claims. The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word âmayâ is used in a permissive sense (i.e., meaning âhaving the potential toâ), rather than the mandatory sense (i.e., meaning âmustâ). Similarly, the words âinclude,â âincluding,â and âincludesâ mean âincluding, but not limited to.â
DETAILED DESCRIPTION OF EMBODIMENTS
Various embodiments of methods, systems, and computer-readable media for cloud-based access to quantum computing resources are described. Using the techniques described herein, quantum computing resources that are hosted âin the cloudâ can be accessed by client computing devices. The client devices may represent âclassicalâ (e.g., binary digital) computing devices that may seek to take advantage of the speed of quantum computing for solving particular problems. The client devices may be hosted inside or outside the same provider network that hosts the quantum computing resources. On request, a control plane may attach a quantum computing instance to a classical computing instance over a network. When a quantum instance is attached, the classical instance may have remote control of that quantum instance (exclusive of other classical instances) until the attachment is terminated. When the attachment is terminated, the quantum computing resource may be reclaimed and prepared for re-use by the same client or a different client at a later time. A particular quantum computing resource (e.g., a quantum computing instance) may be used and re-used by different client devices. Similarly, a particular client device may use different quantum computing resources over time. On request, a control plane of the provider network may provide access to a classical instance that includes or can locally access a quantum computing resource over an interconnect. A quantum computing instance may run a particular quantum algorithm with a particular initial configuration. The instance type of the quantum instance, the quantum algorithm, and/or the initial configuration may be selected by the client from a catalog. Different instance types may have different quantum computing characteristics such as the number or configuration of quantum bits. In one embodiment, a client may select an instance type that represents a template for solving a particular type of problem and that includes a pre-loaded quantum algorithm. In one embodiment, the elastic quantum computing service may recommend particular instance types, quantum algorithms, and/or initial configurations to a client, e.g., based on a specified problem domain or workload and to optimize speed, cost, or accuracy.
Various embodiments of methods, systems, and computer-readable media for a service for managing quantum computing resources are described. Using the techniques described herein, quantum computing resources that are hosted âin the cloudâ may be managed using a task management service. The task management service may receive task descriptions from clients and select and orchestrate computing resources, including quantum computing resources, to perform the tasks on behalf of the clients. The computing resources may be selected based (at least in part) on task descriptions and on performance metrics of prior tasks. The task management service may select appropriate computing resources, select and/or optimize quantum algorithms to implement a task, determine how many times to run a quantum algorithm, determine when to change the initial values for a quantum algorithm, determine when to run quantum algorithms or other operations, and otherwise perform intelligent management of computing resources. The computing resources managed by the task management service may also include classical computing resources such as computing devices and accelerators. In some embodiments, the task management service may use both quantum computing resources and classical computing resources to perform a particular task, e.g., where the different types of resources perform different portions of the task. In some embodiments, the task management service may use both quantum computing resources and classical computing resources to perform the same task, and the service may analyze the results to influence the selection of resources for future tasks. The task management service may introduce a layer of intelligent management of computing resources such that clients may delegate management of resources to the service.
Various embodiments of methods, systems, and computer-readable media for a development environment for programming quantum computing resources are described. Using the techniques described herein, clients may use a development environment to build programs executable on quantum computing resources. The development environment may be hosted in the cloud (at least in part) or executed locally on a client computing device (at least in part). The development environment may be associated with a particular type of quantum computing resource or with a higher-level abstraction of quantum computing resources. Using the development environment, a client may enter information associated with a quantum algorithm, such as programming elements of the algorithm or other program code. The program code may be entered as text, as visual or graphical programming elements (e.g., nodes in a graphical program), or using any other suitable input modality. In one embodiment, programming elements may be selected by the client or by the environment itself from a repository. In one embodiment, programming elements may be recommended to the developer (the client) by the environment. The development environment may optimize the program code and compile the code into a quantum algorithm that is executable on a quantum computing resource. The development environment may select one or more quantum resources to run the quantum algorithm, e.g., from a pool of computing resources hosted in a cloud-based provider network. A quantum computing resource may be selected based (at least in part) on characteristics of the quantum algorithm, e.g., to select a quantum resource that is particularly suited for a specific problem domain such as molecular modeling, traffic optimization, and so on. A quantum computing resource may be selected based (at least in part) on optimization of speed, accuracy, and/or cost. In one embodiment, the quantum algorithm may be run on a quantum computing resource managed by the client. In one embodiment, a quantum algorithm may be tested on different quantum computing resources, or variants of an algorithm may be tested on different instances of the same type of quantum resource. In one embodiment, a quantum algorithm may be tested on both quantum resources and classical computing resources. Based on the testing, the environment may recommend particular resource types for the algorithm or may recommend one variant of the algorithm over another.
Various embodiments of methods, systems, and computer-readable media for cloud-based simulation of quantum computing resources are described. Using the techniques described herein, clients may submit quantum algorithms to a quantum computing simulation service. The quantum computing simulation service may implement simulation of the quantum algorithms using classical computing resources. In one embodiment, the quantum computing simulation service and the classical computing resources may be offered to clients by a cloud-based provider network. The quantum computing simulation service may select the classical resources, such as a plurality of virtual compute instances, from a pool of available computing resources of the provider network, and the resources may vary in their instance type or other characteristics. The quantum computing simulation service may select an appropriate number and type of classical resources for a particular quantum algorithm. In one embodiment, the quantum computing simulation service may recommend a number and/or type of classical resources to a client. In one embodiment, the selected classical resources may simulate the quantum algorithm using executable instructions that represent similar logic as the quantum algorithm. In one embodiment, at least some of the classical resources may run a simulator for quantum computing hardware, and any of the classical resources may simulate all or part of the quantum algorithm. In one embodiment, the quantum computing simulation service may orchestrate the use of many classical computing resources to perform various tasks associated with the simulation. The simulation may often require many more classical computing resources or more runtime than the use of a quantum computing resource. However, in some scenarios, the cost of the classical computing resources may be less than the quantum computing resource, or the classical computing resources may have greater availability than the quantum computing resource. In one embodiment, quantum algorithms may be selected from a catalog in the provider network and then simulated on classical resources. The quantum computing simulation service may be used to test quantum algorithms on classical computing resources prior to using genuine quantum computing resources. In one embodiment, the quantum computing simulation service may simulate quantum algorithms developed using a development environment for quantum computing.
Cloud-Based Access to Quantum Computing Resources
FIG. 1 A , FIG. 1 B , and FIG. 1 C illustrate an example system environment for cloud-based access to quantum computing resources, according to some embodiments. An elastic quantum computing service 100 may provide access to quantum computing resources 160 . The quantum computing resources may be hosted âin the cloud,â e.g., in a cloud-based provider network 190 whose resources are remotely accessible to clients. Quantum computing resources 160 may include computing devices that rely on quantum-mechanical phenomena for their operation. A quantum computing device, also referred to as a quantum computer, may include a plurality of quantum bits (qubits). A quantum bit can be in a superposition of states. A quantum computer with n qubits may be in a superposition of 2 n different states simultaneously, while a non-quantum (classical) computer may be in only one of those states at a given time. A quantum computer may run a quantum algorithm that includes a sequence of quantum logic gates; a problem may be encoded by setting the initial configuration of values of the qubits. When measured, the system of qubits may collapse into one of the 2 n states, where each qubit represents a binary value (one or zero). Using these principles, quantum computing resources 160 may solve some problems much faster than a classical computer. For example, the quantum computing resources 160 may be used to solve complex problems in domains such as machine learning, financial portfolio optimization, molecular modeling, climate modeling, integer factorization, simulation, and so on. Quantum algorithms may often provide an exponential or quadratic speedup over their classical computing counterparts.
In some embodiments, the quantum computing resources 160 may run quantum algorithms such as Grover's algorithm, the Deutsch-Jozsa algorithm, Shor's algorithm, a quantum Fourier transform, a family of quantum algorithms involving amplitude amplification, adiabatic quantum computation, quantum error connection, and so on. Quantum algorithms may represent a translation of problems in various domains, such as chemistry and materials science, into quantum circuits that can be executed on quantum computing resources. Quantum algorithms may be generated by transforming physics equations which describe chemical and material systems into representations that can be interpreted by quantum computing resources. For example, to simulate the energy surface of a molecule using a quantum algorithm, several types of input may be used: e.g., a specification of the coordinates of the nuclei in the molecule, a basis set usable to discretize the molecule, and the charge and spin multiplicity of the system (if known). Classical computation may be used to optimally stage the computation of the quantum algorithm, e.g., to select an initial configuration for the algorithm using a Hartree-Fock calculation. A researcher may then specify the active space representing the electrons that are of greatest interest. The equations for these electrons may be mapped to a representation suitable for the quantum bits of a quantum computing resource, e.g., using the Bravyi-Kitaev transformation. A quantum algorithm may then be selected to solve for the properties of interest to the researcher. To run the quantum algorithm, the quantum circuit may be output in assembly language or another low-level language that can be run on the quantum computing resource.
Quantum computing is currently associated with numerous technical problems. For example, quantum computers may be very expensive to purchase due to their exotic nature and rarity. Additionally, quantum computers may be difficult to manage and maintain for similar reasons. Furthermore, quantum algorithms may be complex to develop and test, especially for developers who are accustomed to a classical computing paradigm. These problems may be addressed by providing cloud-based access to quantum computing resources and management of such resources such that clients need not purchase or maintain the quantum computing resources on their own but may instead lease the quantum resources on an as-needed basis. In one embodiment, a plurality of quantum computing instances may be provided to clients based on a set of quantum computing resources 160 . In one embodiment, a quantum computing instance 161 may correspond to one physical quantum computing device in the quantum resources 160 . In one embodiment, a plurality of quantum computing instances (including instance 161 ) may be provided by one physical quantum computing device in the quantum resources 160 . In one embodiment, a single quantum computing device in the quantum resources 160 may be time-shared to offer its functionality to multiple tenants in manner that appears concurrent to the tenants. The time-sharing may be implemented using a control plane associated with the quantum computing resources 160 , e.g., using the service 100 to facilitate the use of a single quantum computing device by different clients. In one embodiment, the quantum computing instance 161 may represent a virtual instance that is implemented on top of the underlying physical quantum resources 160 .
In one embodiment, the elastic quantum computing service 100 may provide remote access to quantum computing resources 160 for a plurality of clients of a provider network 190 . The service 100 may represent a control plane of the provider network 190 . The clients may represent customers of the provider network 190 , and the clients may use various resources and services of the provider network in exchange for fees. The clients may operate various computing devices that represent a âclassicalâ approach to computing in that they do not rely on quantum-mechanical phenomena for their operation. The classical computing resources may represent binary digital computing devices such as the example computing device 3000 as shown in FIG. 20 . Using the elastic quantum computing service 100 , quantum computing instances may be attached to classical computing instances via network connections (e.g., over network 150 ). In one embodiment, an attached quantum computing instance may act as an accelerator for particular tasks that are especially suited for quantum computing, such that quantum computing approaches are likely to provide faster or more accurate answers than classical computing approaches. In one embodiment, an attached quantum computing instance may be used solely by a particular classical instance as long as the attachment is maintained, such that other classical instances may not have concurrent access to the functionality of that particular quantum computing instance. Quantum instances may be used by classical instances on a temporary basis, and when an attachment is terminated, the quantum computing resource(s) used for a particular quantum instance may be returned to the pool of quantum computing resources 160 for potential re-use by the same client or different clients. In one embodiment, a quantum computing instance 161 may be attached to a classical computing instance based on an attachment request sent to the elastic quantum computing service 100 . The attachment request may be sent by the classical instance itself (e.g., if the classical instance is already running), by a client associated with the classical instance, or by a client or other entity that seeks to provision both the classical instance and the attached quantum instance in the same transaction.
In various embodiments, clients who seek to attach quantum computing instances to classical computing instances may have varying relationships to the provider network 190 . In some embodiments, a classical computing instance within the provider network 190 may be provisioned by a control plane of the provider network, e.g., based (at least in part) on a request from a client. As shown in the example of FIG. 1 A , a client may operate a classical computing instance 110 that is internal to the provider network 190 , e.g., such that the underlying hardware resources of the instance 110 are hosted by the provider network. As shown in the example of FIG. 1 B , a client 140 may operate a virtual computing instance 120 that is internal to the provider network 190 . Using a client computing device 140 (such as the example computing device 3000 as shown in FIG. 20 ), a client of the provider network 190 may interact with and control the virtual computing instance 120 . The virtual computing instance 120 may be provided by a computing virtualization service of the provider network 190 using classical computing resources 170 that are hosted in the provider network. As shown in the example of FIG. 1 C , a classical computing instance 130 may be external to the provider network 190 , e.g., on client premises or otherwise in an environment not under the management of the provider network.
In various embodiments, the elastic quantum computing service 100 may include components to implement various types of functionality. In one embodiment, the elastic quantum computing service 100 may include a component for quantum instance recommendation 102 . The quantum instance recommendation 102 may recommend the quantum computing instance 161 , quantum algorithm 165 , and/or initial configuration 166 to the client. For example, based on a particular problem domain or workload that the client specifies, the quantum instance recommendation 102 may recommend a particular instance type of the quantum instance 161 that is designed for the problem domain. The recommendation may seek to optimize a speed, accuracy, or cost of the problem, based (at least in part) on input concerning the client's goals. The instance type may be associated with a quantum computing resource that has particular quantum computing characteristics, such as a particular number of qubits. The recommended instance may be pre-loaded with a suitable quantum algorithm 165 and/or an initial configuration 166 (e.g., initial values for the qubits) for that algorithm, or the algorithm may be recommended separately. The recommendation may be communicated to the client through any suitable interface, e.g., a graphical user interface (GUI) associated with the elastic quantum computing service 100 . In one embodiment, the recommended instance may be provisioned and attached to a classical instance specified by the client based on user input accepting the recommendation.
In one embodiment, the elastic quantum computing service 100 may include a component for quantum instance provisioning 104 . The quantum instance provisioning 104 may interact with a resource manager 180 of the provider network 190 to reserve, configure, and/or attach at least one of the quantum computing resources 160 on behalf of a client associated with the
classical computing instance
110 , 120 , or 130 . The quantum computing resources 160 may represent a pool of available resources, including quantum computers in one or more data centers managed by the provider network 190 . Provisioning the quantum computing instance 161 may include reserving one of the quantum computers, or a portion of one of the quantum computers, for attachment to the classical computing instance. The service 100 may also perform the attachment of the quantum instance 161 to the classical instance. In one embodiment, the elastic quantum computing service 100 may include a component for quantum instance deprovisioning 106 . The attachment may be temporary, and the quantum computing resource(s) used to implement the quantum computing instance 161 may be returned to the pool of available quantum computing resources 160 when no longer needed or used by the classical instance. Deprovisioning the quantum computing instance 161 may include terminating the attachment (if not already terminated), deprogramming the quantum algorithm, erasing or resetting the values of any qubits, removing any client-specific data or metadata associated with the quantum instance (e.g., in a classical component that is local to the quantum computer and that manages the quantum computer), and/or otherwise preparing the reclaimed quantum computing resources for reuse by the same client or another client.
In one embodiment, the elastic quantum computing service 100 may include a component for quantum instance programming 108 . The quantum instance programming 108 may deploy a quantum algorithm 165 to the quantum computing instance 161 . The quantum instance programming 108 may configure a quantum algorithm 165 on the quantum computing instance 161 , e.g., by providing an initial configuration 166 for the algorithm. The initial configuration 166 may represent initial values for qubits. In one embodiment, the quantum algorithm 165 may be provided by the client associated with the classical computing instance and deployed to the quantum instance 161 by the client device. In one embodiment, the quantum algorithm 165 may be selected by the client associated with the classical computing instance, e.g., from a catalog of algorithms offered by the provider network 190 . In one embodiment, the quantum algorithm 165 may be pre-loaded on the quantum computing instance, and the quantum computing instance may be selected by the client due to its suitability for a particular problem domain.
The quantum algorithm 165 may be run based (at least in part) on input 116 from the classical computing instance. The input 116 may represent a selection of the algorithm 165 , a selection of the initial configuration 166 , a decision to start the run at a particular time, and/or other control signals associated with operation of the quantum computing instance 161 . In one embodiment, the
classical instance
110 , 120 , or 130 may run an application 115 , and the application may generate at least a portion of the input 116 used by the quantum computing instance 161 . Upon measuring (observing) the qubits, the qubits may collapse into a particular state where each qubit represents a binary value (one or zero). This state may represent the result(s) 117 of the run of the algorithm 165 and may be provided back to the classical computing instance. Quantum algorithms may be considered probabilistic such that they provide a solution with a certain probability, and the algorithm 165 may be run more than once to arrive at different results 117 . In one embodiment, by repeatedly setting the algorithm's initial values, running the algorithm, and measuring the algorithm's results, the probability of arriving at the correct answer may be increased.
FIG. 1 D illustrates an example system environment for cloud-based access to quantum computing resources, including a data center that hosts a quantum computing instance, according to one embodiment. In one embodiment, the quantum computing resources 160 may be hosted in a data center 199 that is not necessarily part of the provider network 190 . For example, the data center 199 may be owned or managed by a different entity than the entity that provides the elastic quantum computing service 100 . As another example, the data center 199 may represent a client-managed data center. In one embodiment, the service 100 may have access to the quantum computing resources 160 in the data center 199 and may interact with the data center to provision a quantum computing instance 161 on behalf of a client 140 , e.g., in response to a request from the client. The client 140 may then remotely access and/or control the quantum computing instance 161 as discussed above.
FIG. 1 E illustrates an example system environment for cloud-based access
CLAIMS
Claims ( 20 )
What is claimed is:
1. A system comprising:
classical computing resources;
quantum computing resources;
classical hardware accelerators; and
a resource manager, configured to:
provide a client an interface for submitting a workload to be executed using a service-oriented architecture comprising a given one or more classical computing resources, a given one or more quantum computing resources, and a given one or more classical hardware accelerators,
wherein the classical computing resources are configured to implement a virtualized computing instance configured to:
route tasks from an application executing on the virtualized computing instance to one or more quantum computing resources of the quantum computing resources; and
route tasks from the application execution on the virtualized computing instance to one or more hardware accelerators of the classical hardware accelerators.
2. The system of claim 1 , wherein:
the given one or more quantum computing resources comprises a quantum computing instance; and
the virtualized computing instance and the quantum computing instance are configured to exchange inputs and results via a network of the service-oriented architecture.
3. The system of claim 2 , wherein:
the virtualized computing instance further comprises an elastic computing library, configured to:
route the tasks from the application executing on the virtualized computing instance to the quantum computing instance; and
route the tasks from the application execution on the virtualized computing instance to the one or more hardware accelerators of the classical hardware accelerators.
4. The system of claim 1 , wherein the classical hardware accelerators comprise one or more of:
a graphics processing unit (GPU);
a field programmable gate array (FPGA); or
an application specific integrated circuit (ASIC).
5. The system of claim 1 , wherein the given one or more quantum computing resources are provisioned to be used to execute the client's workload with a quantum algorithm implemented on the given one or more quantum computing resources.
6. The system of claim 5 , wherein the quantum algorithm is provisioned with an initial configuration for performing a task of the client's workload.
7. The system of claim 1 , further comprising:
a task management service configured to:
select, based on characteristics of one or more tasks included in the client's workload, the collection of classical, quantum and hardware accelerator resources that are configured by the resource manager to interact with one another in the service-oriented architecture.
8. The system of claim 7 , wherein the task management service is further configured to:
perform quantum algorithm selection for the given one or more quantum computing resources.
9. The system of claim 8 , wherein the task management service is further configured to:
perform metric analysis based on performance of a given task of the client's workload using the quantum algorithm; and
perform an optimization with regard to the quantum algorithm for performing subsequent tasks of the client's workload.
10. The system of claim 7 , wherein the task management service is further configured to perform results aggregation for results generated using:
the given one or more of the classical computing resources;
the given one or more of the quantum computing resources; and
the given one or more of the classical hardware accelerators.
11. The system of claim 1 , further comprising one or more computing devices configured to implement an elastic computing service, wherein:
the elastic computing service is configured to:
instruct the resource manager to provision and deprovision the classical computing resources, the quantum computing resources, and the hardware accelerators in order to execute the client's workload.
12. The system of claim 11 , wherein the elastic computing service is further configured to:
provide the client with a catalog of available configurations that may be used to execute the client's workload; and
receive, from the client, a configuration selection for executing the client's workload.
13. The system of claim 12 , wherein the elastic computing service is further configured to:
receive one or more inputs from the client describing the client's workload; and
provide a recommendation for a quantum computing resource to be used to execute, at least in part, the client's workload.
14. The system of claim 11 , wherein the elastic computing service is further configured to:
provide the client with a catalog of quantum algorithms that may be used with the one or more quantum computing resources; and
program the one or more quantum computing resources based on a client selection of a given one or more quantum algorithms to be used to execute the client's workload.
15. A method, comprising:
providing an elastic computing service comprising:
classical computing resources;
quantum computing resources;
classical hardware accelerators; and
configuring a collection of resources to interact with one another, wherein the collection of resources comprises:
a given one or more of the classical computing resources;
a given one or more of the quantum computing resources; and
a given one or more of the classical hardware accelerators; and
providing a client an interface for submitting a workload to be executed using the given one or more classical computing resources, the given one or more quantum computing resources, and the given one or more classical hardware accelerators,
wherein the classical computing resources are configured to implement a virtualized computing instance configured to:
route tasks from an application executing on the virtualized computing instance to one or more quantum computing resources of the quantum computing resources; and
route tasks from the application execution on the virtualized computing instance to one or more hardware accelerators of the classical hardware accelerators.
16. The method of claim 15 , further comprising:
providing the client with a catalog of available configurations that may be used to execute the client's workload; and
receiving, from the client, a configuration selection.
17. The method of claim 15 , further comprising:
receiving one or more inputs from the client describing the client's workload; and
providing a recommendation for a quantum computing resource to be used to execute, at least in part, the client's workload.
18. The method of claim 15 , further comprising:
providing the client with a catalog of quantum algorithms that may be used with the one or more quantum computing resources; and
programing the one or more quantum computing resources based on a client selection of a given one or more quantum algorithms of the catalog that are to be used to execute the client's workload.
19. The method of claim 15 , further comprising:
performing metric analysis based on performance of a given task of the client's workload using the quantum algorithm; and
performing optimization with regard to the quantum algorithm for performing subsequent tasks of the client's workload.
20. One or more non-transitory, computer-readable storage media, storing program instructions, that when executed on or across one or more processors, cause the one or more processor to:
implement a resource manager for an elastic computing service, the resource manager configured to:
configure a collection of resources to interact with one another, wherein the collection of resources comprises:
a classical computing resource;
a quantum computing resource; and
a classical hardware accelerator; and
provide a client an interface for submitting a workload to be executed using the classical computing resource, the quantum computing resource, and the classical hardware accelerator,
wherein the classical computing resources are configured to implement a virtualized computing instance configured to:
route tasks from an application executing on the virtualized computing instance to one or more quantum computing resources of the quantum computing resources; and
route tasks from the application execution on the virtualized computing instance to one or more hardware accelerators of the classical hardware accelerators.
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