ABSTRACT
Abstract
Systems, computer-implemented methods, and computer program products to facilitate quantum computing job scheduling are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a run queue component that can store the quantum computing jobs based on the run order. In an embodiment, the scheduler component can determine the run order based on availability of one or more qubits comprising a defined level of fidelity.
Description
BACKGROUND
The subject disclosure relates to scheduling quantum computing jobs, and more specifically, to co-scheduling quantum computing jobs based on quantum based run constraints.
Quantum computing is generally the use of quantum-mechanical phenomena for the purpose of performing computing and information processing functions. Quantum computing can be viewed in contrast to classical computing, which generally operates on binary values with transistors. That is, while classical computers can operate on bit values that are either 0 or 1, quantum computers operate on quantum bits (qubits) that comprise superpositions of both 0 and 1, can entangle multiple quantum bits, and use interference.
Quantum computing hardware is different from classical computing hardware. In particular, superconducting quantum circuits generally rely on Josephson junctions, which can be fabricated in a semiconductor device. A Josephson junction generally manifests the Josephson effect of a supercurrent, where current can flow indefinitely across a Josephson junction without an applied voltage. A Josephson junction can be created by weakly coupling two superconductors (a material that conducts electricity without resistance), for example, by a tunnel barrier.
One way in which a Josephson junction can be used in quantum computing is by embedding the Josephson junction in a superconducting circuit to form a quantum bit (qubit). A Josephson junction can be used to form a qubit by arranging the Josephson junction in parallel with a shunting capacitor. A plurality of such qubits can be arranged on a superconducting quantum circuit fabricated on a semiconductor device. The qubits can be arranged in a lattice (i.e., a grid) formation such that they can be coupled to nearest-neighbor qubits. Such an arrangement of qubits coupled to nearest-neighbor qubits can constitute a quantum computing architecture. An example of an existing quantum computing architecture is the quantum surface code architecture, which can further comprise microwave readout resonators coupled to the respective qubits that facilitate reading quantum information of the qubits (i.e., also referred to as âaddressingâ or âreading a quantum logic state of the qubitâ). Such a quantum surface code architecture can be integrated on a semiconducting device to form an integrated quantum processor that can execute computations and information processing functions that are substantially more complex than can be executed by classical computing devices (e.g., general-purpose computers, special-purpose computers, etc.).
Quantum computing has the potential to solve problems that, due to their computational complexity, cannot be solved, either at all or for all practical purposes, on a classical computer. However, quantum computing requires very specialized skills to, for example, co-schedule quantum computing jobs based on quantum based run constraints, where such quantum computing jobs can be executed by a quantum computing device (e.g., a quantum computer, quantum processor, etc.) based on such a co-schedule. For example, based on such a co-schedule (e.g., also referred to as a run order throughout this disclosure), the quantum computing device can execute a certain quantum computing job using certain qubits.
Many industry experts believe that a common use of quantum computing systems (e.g., quantum computers, quantum processors, etc.) will be as adjuncts to classical computing systems (e.g., cloud based computing systems). As a result, it is likely that quantum computers will become a shared resource, and as with all shared resources, efficient and fair job scheduling becomes important for optimal use of a quantum computer.
It is important to note that quantum computers, unlike classical computers, must run jobs to completion; swapping jobs to disk is not possible. Consequently, efficient scheduling is particularly important. However, efficient scheduling of quantum computing jobs requires consideration of one or more quantum based run constraints unique to quantum computing that are associated with such quantum computing jobs and/or with quantum computing systems that execute such jobs. A problem with existing classical and/or quantum computing job scheduling systems is that they do not account for such quantum based run constraints when scheduling quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.), which results in inefficient and/or unfair use of such quantum computing devices.
SUMMARY
The following presents a summary to provide a basic understanding of one or more embodiments of the invention. This summary is not intended to identify key or critical elements, or delineate any scope of the particular embodiments or any scope of the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description that is presented later. In one or more embodiments described herein, systems, devices, computer-implemented methods, and/or computer program products that facilitate quantum computing job scheduling are described.
According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a run queue component that can store references to the quantum computing jobs based on the run order. An advantage of such a system is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the scheduler component can determine the run order based on availability of one or more qubits comprising a defined level of fidelity. An advantage of such a system is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a computer-implemented method can comprise determining, by a system operatively coupled to a processor, a run order of quantum computing jobs based on one or more quantum based run constraints. The computer-implemented method can further comprise storing, by the system, references to the quantum computing jobs based on the run order. An advantage of such a computer-implemented method is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the determining can comprise, determining, by the system, the run order based on availability of one or more qubits comprising a defined level of fidelity. An advantage of such a computer-implemented method is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a computer program product that can facilitate a quantum computation job scheduling process is provided. The computer program product can comprise a computer readable storage medium having program instructions embodied therewith, the program instructions can be executable by a processing component to cause the processing component to determine, by the processor, a run order of quantum computing jobs based on one or more quantum based run constraints. The program instructions can also cause the processing component to store, by the processor, references to the quantum computing jobs based on the run order. An advantage of such a computer program product is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the program instructions are further executable by the processor to cause the processor to determine, by the processor, the run order based on at least one of: an approximation of runtimes of the quantum computing jobs; availability of one or more qubits comprising a defined level of fidelity; or a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs. An advantage of such a computer program product is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a submit component that can submit at least one of the quantum computing jobs to one or more quantum computing devices based on the run order. An advantage of such a system is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the scheduler component can determine the run order based on at least one of: approximations of longest runtimes corresponding to the quantum computing jobs; availability of one or more preferred qubits; or a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs. An advantage of such a system is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a computer-implemented method can comprise determining, by a system operatively coupled to a processor, a run order of quantum computing jobs based on one or more quantum based run constraints. The computer-implemented method can further comprise submitting, by the system, at least one of the quantum computing jobs to one or more quantum computing devices based on the run order. An advantage of such a computer-implemented method is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the determining can comprise, determining, by the system, the run order based on at least one of: approximations of longest runtimes corresponding to the quantum computing jobs; availability of one or more preferred qubits; or a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs. An advantage of such a computer-implemented method is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 2 A illustrates an example, non-limiting run order that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 2 B illustrates an example, non-limiting run order that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 3 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 4 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 5 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 6 illustrates a flow diagram of an example, non-limiting computer-implemented method that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 7 illustrates a flow diagram of an example, non-limiting computer-implemented method that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 8 illustrates a block diagram of an example, non-limiting operating environment in which one or more embodiments described herein can be facilitated.
FIG. 9 illustrates a block diagram of an example, non-limiting cloud computing environment in accordance with one or more embodiments of the subject disclosure.
FIG. 10 illustrates a block diagram of example, non-limiting abstraction model layers in accordance with one or more embodiments of the subject disclosure.
DETAILED DESCRIPTION
The following detailed description is merely illustrative and is not intended to limit embodiments and/or application or uses of embodiments. Furthermore, there is no intention to be bound by any expressed or implied information presented in the preceding Background or Summary sections, or in the Detailed Description section.
One or more embodiments are now described with reference to the drawings, wherein like referenced numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a more thorough understanding of the one or more embodiments. It is evident, however, in various cases, that the one or more embodiments can be practiced without these specific details.
Given the above problem with existing classical and/or quantum computing job scheduling systems that do not account for quantum based run constraints when scheduling quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.), which results in inefficient and/or unfair use of such quantum computing devices, the present disclosure can be implemented to produce a solution to this problem in the form of a system comprising a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. An advantage of such a system is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
FIG. 1 illustrates a block diagram of an example, non-limiting system 100 that can facilitate quantum computing job scheduling components in accordance with one or more embodiments de
BACKGROUND
The subject disclosure relates to scheduling quantum computing jobs, and more specifically, to co-scheduling quantum computing jobs based on quantum based run constraints.
Quantum computing is generally the use of quantum-mechanical phenomena for the purpose of performing computing and information processing functions. Quantum computing can be viewed in contrast to classical computing, which generally operates on binary values with transistors. That is, while classical computers can operate on bit values that are either 0 or 1, quantum computers operate on quantum bits (qubits) that comprise superpositions of both 0 and 1, can entangle multiple quantum bits, and use interference.
Quantum computing hardware is different from classical computing hardware. In particular, superconducting quantum circuits generally rely on Josephson junctions, which can be fabricated in a semiconductor device. A Josephson junction generally manifests the Josephson effect of a supercurrent, where current can flow indefinitely across a Josephson junction without an applied voltage. A Josephson junction can be created by weakly coupling two superconductors (a material that conducts electricity without resistance), for example, by a tunnel barrier.
One way in which a Josephson junction can be used in quantum computing is by embedding the Josephson junction in a superconducting circuit to form a quantum bit (qubit). A Josephson junction can be used to form a qubit by arranging the Josephson junction in parallel with a shunting capacitor. A plurality of such qubits can be arranged on a superconducting quantum circuit fabricated on a semiconductor device. The qubits can be arranged in a lattice (i.e., a grid) formation such that they can be coupled to nearest-neighbor qubits. Such an arrangement of qubits coupled to nearest-neighbor qubits can constitute a quantum computing architecture. An example of an existing quantum computing architecture is the quantum surface code architecture, which can further comprise microwave readout resonators coupled to the respective qubits that facilitate reading quantum information of the qubits (i.e., also referred to as âaddressingâ or âreading a quantum logic state of the qubitâ). Such a quantum surface code architecture can be integrated on a semiconducting device to form an integrated quantum processor that can execute computations and information processing functions that are substantially more complex than can be executed by classical computing devices (e.g., general-purpose computers, special-purpose computers, etc.).
Quantum computing has the potential to solve problems that, due to their computational complexity, cannot be solved, either at all or for all practical purposes, on a classical computer. However, quantum computing requires very specialized skills to, for example, co-schedule quantum computing jobs based on quantum based run constraints, where such quantum computing jobs can be executed by a quantum computing device (e.g., a quantum computer, quantum processor, etc.) based on such a co-schedule. For example, based on such a co-schedule (e.g., also referred to as a run order throughout this disclosure), the quantum computing device can execute a certain quantum computing job using certain qubits.
Many industry experts believe that a common use of quantum computing systems (e.g., quantum computers, quantum processors, etc.) will be as adjuncts to classical computing systems (e.g., cloud based computing systems). As a result, it is likely that quantum computers will become a shared resource, and as with all shared resources, efficient and fair job scheduling becomes important for optimal use of a quantum computer.
It is important to note that quantum computers, unlike classical computers, must run jobs to completion; swapping jobs to disk is not possible. Consequently, efficient scheduling is particularly important. However, efficient scheduling of quantum computing jobs requires consideration of one or more quantum based run constraints unique to quantum computing that are associated with such quantum computing jobs and/or with quantum computing systems that execute such jobs. A problem with existing classical and/or quantum computing job scheduling systems is that they do not account for such quantum based run constraints when scheduling quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.), which results in inefficient and/or unfair use of such quantum computing devices.
SUMMARY
The following presents a summary to provide a basic understanding of one or more embodiments of the invention. This summary is not intended to identify key or critical elements, or delineate any scope of the particular embodiments or any scope of the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description that is presented later. In one or more embodiments described herein, systems, devices, computer-implemented methods, and/or computer program products that facilitate quantum computing job scheduling are described.
According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a run queue component that can store references to the quantum computing jobs based on the run order. An advantage of such a system is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the scheduler component can determine the run order based on availability of one or more qubits comprising a defined level of fidelity. An advantage of such a system is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a computer-implemented method can comprise determining, by a system operatively coupled to a processor, a run order of quantum computing jobs based on one or more quantum based run constraints. The computer-implemented method can further comprise storing, by the system, references to the quantum computing jobs based on the run order. An advantage of such a computer-implemented method is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the determining can comprise, determining, by the system, the run order based on availability of one or more qubits comprising a defined level of fidelity. An advantage of such a computer-implemented method is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a computer program product that can facilitate a quantum computation job scheduling process is provided. The computer program product can comprise a computer readable storage medium having program instructions embodied therewith, the program instructions can be executable by a processing component to cause the processing component to determine, by the processor, a run order of quantum computing jobs based on one or more quantum based run constraints. The program instructions can also cause the processing component to store, by the processor, references to the quantum computing jobs based on the run order. An advantage of such a computer program product is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the program instructions are further executable by the processor to cause the processor to determine, by the processor, the run order based on at least one of: an approximation of runtimes of the quantum computing jobs; availability of one or more qubits comprising a defined level of fidelity; or a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs. An advantage of such a computer program product is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a submit component that can submit at least one of the quantum computing jobs to one or more quantum computing devices based on the run order. An advantage of such a system is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the scheduler component can determine the run order based on at least one of: approximations of longest runtimes corresponding to the quantum computing jobs; availability of one or more preferred qubits; or a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs. An advantage of such a system is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
According to an embodiment, a computer-implemented method can comprise determining, by a system operatively coupled to a processor, a run order of quantum computing jobs based on one or more quantum based run constraints. The computer-implemented method can further comprise submitting, by the system, at least one of the quantum computing jobs to one or more quantum computing devices based on the run order. An advantage of such a computer-implemented method is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
In an embodiment, the determining can comprise, determining, by the system, the run order based on at least one of: approximations of longest runtimes corresponding to the quantum computing jobs; availability of one or more preferred qubits; or a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs. An advantage of such a computer-implemented method is that it can facilitate accurate solutions to computations executed by one or more quantum computing devices.
DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 2 A illustrates an example, non-limiting run order that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 2 B illustrates an example, non-limiting run order that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 3 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 4 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 5 illustrates a block diagram of an example, non-limiting system that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 6 illustrates a flow diagram of an example, non-limiting computer-implemented method that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 7 illustrates a flow diagram of an example, non-limiting computer-implemented method that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein.
FIG. 8 illustrates a block diagram of an example, non-limiting operating environment in which one or more embodiments described herein can be facilitated.
FIG. 9 illustrates a block diagram of an example, non-limiting cloud computing environment in accordance with one or more embodiments of the subject disclosure.
FIG. 10 illustrates a block diagram of example, non-limiting abstraction model layers in accordance with one or more embodiments of the subject disclosure.
DETAILED DESCRIPTION
The following detailed description is merely illustrative and is not intended to limit embodiments and/or application or uses of embodiments. Furthermore, there is no intention to be bound by any expressed or implied information presented in the preceding Background or Summary sections, or in the Detailed Description section.
One or more embodiments are now described with reference to the drawings, wherein like referenced numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a more thorough understanding of the one or more embodiments. It is evident, however, in various cases, that the one or more embodiments can be practiced without these specific details.
Given the above problem with existing classical and/or quantum computing job scheduling systems that do not account for quantum based run constraints when scheduling quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.), which results in inefficient and/or unfair use of such quantum computing devices, the present disclosure can be implemented to produce a solution to this problem in the form of a system comprising a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. An advantage of such a system is that it can facilitate efficient and fair scheduling (e.g., co-scheduling) of quantum computing jobs to be executed by one or more quantum computing devices (e.g., quantum computer, quantum processor, etc.) that can be utilized by a plurality of entities (e.g., via a cloud computing environment).
FIG. 1 illustrates a block diagram of an example, non-limiting system 100 that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein. In some embodiments, system 100 can comprise a quantum computing job scheduling system 102 , which can be associated with a cloud computing environment. For example, quantum computing job scheduling system 102 can be associated with cloud computing environment 950 described below with reference to FIG. 9 and/or one or more functional abstraction layers described below with reference to FIG. 10 (e.g., hardware and software layer 1060 , virtualization layer 1070 , management layer 1080 , and/or workloads layer 1090 ).
It is to be understood that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed.
Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.
Characteristics are as follows:
On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service's provider.
Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).
Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).
Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.
Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service.
Service Models are as follows:
Software as a Service (SaaS): the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.
Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations.
Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).
Deployment Models are as follows:
Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.
Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.
Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.
Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).
A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure that includes a network of interconnected nodes.
Continuing now with FIG. 1 , according to several embodiments, system 100 can comprise a quantum computing job scheduling system 102 . In some embodiments, quantum computing job scheduling system 102 can comprise a memory 104 , a processor 106 , a scheduler component 108 , a run queue component 110 , and/or a bus 112 .
It should be appreciated that the embodiments of the subject disclosure depicted in various figures disclosed herein are for illustration only, and as such, the architecture of such embodiments are not limited to the systems, devices, and/or components depicted therein. For example, in some embodiments, system 100 and/or quantum computing job scheduling system 102 can further comprise various computer and/or computing-based elements described herein with reference to operating environment 800 and FIG. 8 . In several embodiments, such computer and/or computing-based elements can be used in connection with implementing one or more of the systems, devices, components, and/or computer-implemented operations shown and described in connection with FIG. 1 or other figures disclosed herein.
According to multiple embodiments, memory 104 can store one or more computer and/or machine readable, writable, and/or executable components and/or instructions that, when executed by processor 106 , can facilitate performance of operations defined by the executable component(s) and/or instruction(s). For example, memory 104 can store computer and/or machine readable, writable, and/or executable components and/or instructions that, when executed by processor 106 , can facilitate execution of the various functions described herein relating to quantum computing job scheduling system 102 , scheduler component 108 , run queue component 110 , and/or another component associated with quantum computing job scheduling system 102 (e.g., constraint checker component 302 , submit component 402 , non-starvation component 502 , etc.), as described herein with or without reference to the various figures of the subject disclosure.
In some embodiments, memory 104 can comprise volatile memory (e.g., random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), etc.) and/or non-volatile memory (e.g., read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), etc.) that can employ one or more memory architectures. Further examples of memory 104 are described below with reference to system memory 816 and FIG. 8 . Such examples of memory 104 can be employed to implement any embodiments of the subject disclosure.
According to multiple embodiments, processor 106 can comprise one or more types of processors and/or electronic circuitry that can implement one or more computer and/or machine readable, writable, and/or executable components and/or instructions that can be stored on memory 104 . For example, processor 106 can perform various operations that can be specified by such computer and/or machine readable, writable, and/or executable components and/or instructions including, but not limited to, logic, control, input/output (I/O), arithmetic, and/or the like. In some embodiments, processor 106 can comprise one or more central processing unit, multi-core processor, microprocessor, dual microprocessors, microcontroller, System on a Chip (SOC), array processor, vector processor, and/or another type of processor. Further examples of processor 106 are described below with reference to processing unit 814 and FIG. 8 . Such examples of processor 106 can be employed to implement any embodiments of the subject disclosure.
In some embodiments, quantum computing job scheduling system 102 , memory 104 , processor 106 , scheduler component 108 , run queue component 110 , and/or another component of quantum computing job scheduling system 102 as described herein can be communicatively, electrically, and/or operatively coupled to one another via a bus 112 to perform functions of system 100 , quantum computing job scheduling system 102 , and/or any components coupled therewith. In several embodiments, bus 112 can comprise one or more memory bus, memory controller, peripheral bus, external bus, local bus, and/or another type of bus that can employ various bus architectures. Further examples of bus 112 are described below with reference to system bus 818 and FIG. 8 . Such examples of bus 112 can be employed to implement any embodiments of the subject disclosure.
In some embodiments, quantum computing job scheduling system 102 can comprise any type of component, machine, device, facility, apparatus, and/or instrument that comprises a processor and/or can be capable of effective and/or operative communication with a wired and/or wireless network. All such embodiments are envisioned. For example, quantum computing job scheduling system 102 can comprise a server device, a computing device, a general-purpose computer, a special-purpose computer, a quantum computing device (e.g., a quantum computer), a tablet computing device, a handheld device, a server class computing machine and/or database, a laptop computer, a notebook computer, a desktop computer, a cell phone, a smart phone, a consumer appliance and/or instrumentation, an industrial and/or commercial device, a digital assistant, a multimedia Internet enabled phone, a multimedia players, and/or another type of device.
In some embodiments, quantum computing job scheduling system 102 can be coupled (e.g., communicatively, electrically, operatively, etc.) to one or more external systems, sources, and/or devices (e.g., computing devices, communication devices, etc.) via a data cable (e.g., High-Definition Multimedia Interface (HDMI), recommended standard (RS) 232 , Ethernet cable, etc.). In some embodiments, quantum computing job scheduling system 102 can be coupled (e.g., communicatively, electrically, operatively, etc.) to one or more external systems, sources, and/or devices (e.g., computing devices, communication devices, etc.) via a network.
According to multiple embodiments, such a network can comprise wired and wireless networks, including, but not limited to, a cellular network, a wide area network (WAN) (e.g., the Internet) or a local area network (LAN). For example, quantum computing job scheduling system 102 can communicate with one or more external systems, sources, and/or devices, for instance, computing devices (and vice versa) using virtually any desired wired or wireless technology, including but not limited to: wireless fidelity (Wi-Fi), global system for mobile communications (GSM), universal mobile telecommunications system (UMTS), worldwide interoperability for microwave access (WiMAX), enhanced general packet radio service (enhanced GPRS), third generation partnership project (3GPP) long term evolution (LTE), third generation partnership project 2 (3GPP2) ultra mobile broadband (UMB), high speed packet access (HSPA), Zigbee and other 802.XX wireless technologies and/or legacy telecommunication technologies, BLUETOOTH®, Session Initiation Protocol (SIP), ZIGBEE®, RF4CE protocol, WirelessHART protocol, 6LoWPAN (IPv6 over Low power Wireless Area Networks), Z-Wave, an ANT, an ultra-wideband (UWB) standard protocol, and/or other proprietary and non-proprietary communication protocols. In such an example, quantum computing job scheduling system 102 can thus include hardware (e.g., a central processing unit (CPU), a transceiver, a decoder), software (e.g., a set of threads, a set of processes, software in execution) or a combination of hardware and software that facilitates communicating information between quantum computing job scheduling system 102 and external systems, sources, and/or devices (e.g., computing devices, communication devices, etc.).
According to multiple embodiments, quantum computing job scheduling system 102 can comprise one or more computer and/or machine readable, writable, and/or executable components and/or instructions that, when executed by processor 106 , can facilitate performance of operations defined by such component(s) and/or instruction(s). Further, in numerous embodiments, any component associated with quantum computing job scheduling system 102 , as described herein with or without reference to the various figures of the subject disclosure, can comprise one or more computer and/or machine readable, writable, and/or executable components and/or instructions that, when executed by processor 106 , can facilitate performance of operations defined by such component(s) and/or instruction(s). For example, scheduler component 108 , run queue component 110 , and/or any other components associated with quantum computing job scheduling system 102 as disclosed herein (e.g., communicatively, electronically, and/or operatively coupled with and/or employed by quantum computing job scheduling system 102 ), can comprise such computer and/or machine readable, writable, and/or executable component(s) and/or instruction(s). Consequently, according to numerous embodiments, quantum computing job scheduling system 102 and/or any components associated therewith as disclosed herein, can employ processor 106 to execute such computer and/or machine readable, writable, and/or executable component(s) and/or instruction(s) to facilitate performance of one or more operations described herein with reference to quantum computing job scheduling system 102 and/or any such components associated therewith.
In some embodiments, to implement one or more quantum computing job scheduling operations, quantum computing job scheduling system 102 can facilitate performance of operations executed by and/or associated with scheduler component 108 , run queue component 110 , and/or another component associated with quantum computing job scheduling system 102 as disclosed herein (e.g., constraint checker component 302 , submit component 402 , non-starvation component 502 , etc.). For example, as described in detail below, quantum computing job scheduling system 102 can facilitate: determining a run order of quantum computing jobs based on one or more quantum based run constraints; storing the quantum computing jobs based on the run order; submitting at least one of the quantum computing jobs to one or more quantum computing devices based on the run order; determining the run order based on an approximation of runtimes of the quantum computing jobs; determining whether the run order violates a qubit communication constraint; determining the run order based on availability of one or more qubits comprising a defined level of fidelity; determining the run order based on a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs; and/or determining the run order based on at least one of: approximations of longest runtimes corresponding to the quantum computing jobs, availability of one or more preferred qubits, or a defined level of confidence corresponding to correctness of at least one of the quantum computing jobs.
According to multiple embodiments, scheduler component 108 can determine a run order of quantum computing jobs based on one or more quantum based run constraints. For example, scheduler component 108 can determine a run order of quantum computing jobs (e.g., pending quantum computing run instances to be executed) that can be executed by one or more quantum computing devices such as, for instance, one or more quantum computers, one or more quantum processors, and/or another quantum computing device. In some embodiments, such a run order can comprise a run schedule comprising references to and/or descriptions of quantum computing jobs (e.g., pending quantum computing run instances to be executed), where such a run schedule can indicate when each quantum computing job can be executed by a certain quantum computer and/or by certain qubits of such quantum computer. In some embodiments, such quantum computing jobs can comprise quantum computing run instances including, but not limited to, computations, data processing, and/or another quantum computing run instance. In some embodiments, such one or more quantum based run constraints can include, but are not limited to, a defined number of qubits required to execute a quantum computing job, a defined number of qubits required to execute a quantum computing job based on error correction, and/or another quantum based run constraint (e.g., as described below with reference to run order 200 a , run order 200 b , FIG. 2 A , and FIG. 2 B ). In these embodiments, such defined number of qubits required to execute a quantum computing job and/or such defined number of qubits required to execute a quantum computing job based on error correction can be defined by an entity (e.g., a human) using one or more input devices, output devices, and/or a user interface of quantum computing job scheduling system 102 as described below.
In some embodiments, scheduler component 108 can determine a run order of quantum computing jobs based on one or more quantum based run constraints by co-scheduling such quantum computing jobs using one or more bin packing algorithms. For example, scheduler component 108 can employ a bin packing algorithm to co-schedule quantum computing jobs requiring M(i) qubits that can be executed using an N-qubit quantum computer, provided the sum of all qubits used concurrently is less than or equal to N (e.g., sum of all qubits used concurrently â¤N). For instance, scheduler component 108 can employ one or more bin packing algorithms including, but not limited to, one-dimensional (1D) bin packing algorithm, two-dimensional (2D) bin packing algorithm, three-dimensional (3D) bin packing algorithm, best-fit algorithm, first-fit algorithm, best-fit decreasing algorithm, first-fit decreasing algorithm, and/or another bin packing algorithm.
In some embodiments, scheduler component 108 can determine a run order of quantum computing jobs based on one or more quantum based run constraints by employing one or more bin packing algorithms described above to schedule the quantum computing jobs such that they fit into the smallest number of iterations (e.g., execution cycles). For example, given an N-qubit (e.g., 8 qubits) quantum computer, scheduler component 108 can co-schedule J(i) quantum computing jobs (e.g., 2 jobs) per iteration, where each job requires M(i) qubits (e.g., as illustrated by run order 200 a depicted in FIG. 2 A ).
FIG. 2 A illustrates an example, non-limiting run order 200 a that can facilitate quantum computing job scheduling components in accordance with one or more embodiments described herein. Repetitive description of like elements and/or processes employed in various embodiments described herein is omitted for sake of brevity.
According to multiple embodiments, run order 200 a can represent a run order (e.g., a run schedule) of J(i) references to pending quantum computing jobs (e.g., quantum computing run instances denoted as Job 1 , Job 2 , etc. in FIG. 2 A ) that can be executed over R(i) iterations 202 (e.g., denoted as Iteration 1 , Iteration 2 , etc. in FIG. 2 A ) by a quantum computer having a total quantity of total qubits 204 , where each quantum computing job requires M(i) qubits. For example, Iteration 1 of run order 200 a can comprise references to pending quantum computing jobs Job 1 and Job 2 (e.g., quantum computing run instances), where Job 1 can require six (6) required qubits 206 and Job 2 can require two (2) required qubits 208 . In some embodiments, scheduler component 108 can determine run order 200 a by employing one or more bin packing algorithms described above to schedule the quantum computing jobs such that they fit into the smallest number of iterations (e.g., execution cycles).
In some embodiments, however, run order 200 a does not account for one or more complex quantum computing based constraints (e.g., constraints associated with executing processing workloads using a quantum computer). For example, run order 200 a does not account for quantum computing based constraints including, but not limited to: quantum computing jobs (e.g., computations, data processing, etc.) must be executed to completion once started; quantum computing jobs do not all take the same amount of time to execute; not all qubits can communicate directly with one another (e.g., not all qubits are interconnected and/or located in a single quantum computing device); not all quantum computing devices (e.g., quantum computers, quantum processors, etc.) will have the same quantity of qubits; and/or another quantum computing based constraint.
In some embodiments, to address one or more such quantum based constr
CLAIMS
Claims ( 20 )
What is claimed is:
1. A system, comprising:
a memory that stores computer executable components; and
a processor that executes the computer executable components stored in the memory, to cause the processor to:
determine respective priorities of quantum computing jobs based on respective levels of confidence of obtaining respective correct answers to the quantum computing jobs, wherein as level of confidence increases priority decreases, and
determine a run order of the quantum computing jobs that employs a minimum number of execution cycles based on a group of quantum computing devices comprising respective groups of qubits, quantum based run constraints associated with the quantum computing jobs, and the respective priorities of the quantum computing jobs, wherein the run order enables concurrent execution of at least two of the quantum computing jobs, and wherein the quantum based run constraints comprise for each of the quantum computing jobs:
a number of qubits required to execute the quantum computing job based on error correction,
at least one preferred qubit specified for the quantum computing job,
availability of a set of qubits from the group of quantum computing devices comprising the number of qubits and the at least one preferred qubit, and
each qubit in the set of qubits is able to directly communicate with all other qubits in the set of qubits; and
executing at least one of the quantum computing jobs using the group of quantum computing devices based on the determined run order.
2. The system of claim 1 , wherein the execution of the computer executable components, further causes the processor to determine the run order further based on respective estimated runtimes for the quantum computing jobs.
3. The system of claim 1 , wherein the quantum based run constraints further comprises the quantum computing jobs must be executed to completion once started.
4. The system of claim 1 , wherein the quantum based run constraints further comprises a longest-running computing job first criterion.
5. The system of claim 1 , wherein the execution of the computer executable components, further causes the processor to determine the run order using a bin packing algorithm.
6. The system of claim 1 , wherein the execution of the computer executable components, further causes the processor to modify the respective priorities of remaining ones of the quantum computing jobs based on changes to the respective levels of confidence determined based on completed quantum computing jobs of quantum computing jobs.
7. The system of claim 1 , wherein the execution of the computer executable components, further causes the processor to determine a new run order of the remaining ones of the quantum computing jobs, based on the modified respective priorities.
8. A computer implemented method, comprising:
determining, by a system operatively coupled to a processor, respective priorities of quantum computing jobs based on respective levels of confidence of obtaining respective correct answers to the quantum computing jobs, wherein as level of confidence increases priority decreases;
determining, by the system, a run order of the quantum computing jobs that employs a minimum number of execution cycles based on a group of quantum computing devices comprising respective groups of qubits, quantum based run constraints associated with the quantum computing jobs, and the respective priorities of the quantum computing jobs, wherein the run order enables concurrent execution of at least two of the quantum computing jobs, and wherein the quantum based run constraints comprise for each of the quantum computing jobs:
a number of qubits required to execute the quantum computing job based on error correction,
at least one preferred qubit specified for the quantum computing job,
availability of a set of qubits from the group of quantum computing devices comprising the number of qubits and the at least one preferred qubit, and
each qubit in the set of qubits is able to directly communicate with all other qubits in the set of qubits; and
executing, by the system, at least one of the quantum computing jobs using the group of quantum computing devices based on the determined run order.
9. The computer implemented method of claim 8 , further comprising:
determining, by the system, the run order further based on respective estimated runtimes for the quantum computing jobs.
10. The computer implemented method of claim 8 , wherein the quantum based run constraints further comprises the quantum computing jobs must be executed to completion once started.
11. The computer implemented method of claim 8 , wherein the quantum based run constraints further comprises a longest-running computing job first criterion.
12. The computer implemented method of claim 8 , determining, by the system, the run order using a bin packing algorithm.
13. The computer implemented method of claim 8 , modifying, by the system, the respective priorities of remaining ones of the quantum computing jobs based on changes to the respective levels of confidence determined based on completed quantum computing jobs of quantum computing jobs.
14. The computer implemented method of claim 13 , further comprising:
determining, by the system, a new run order of the remaining ones of the quantum computing jobs, based on the modified respective priorities.
15. A computer program product facilitating a quantum computing job scheduling process, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
determine respective priorities of quantum computing jobs based on respective levels of confidence of obtaining respective correct answers to the quantum computing jobs, wherein as level of confidence increases priority decreases;
determine a run order of the quantum computing jobs that employs a minimum number of execution cycles based on a group of quantum computing devices comprising respective groups of qubits, quantum based run constraints associated with the quantum computing jobs, and the respective priorities of the quantum computing jobs, wherein the run order enables concurrent execution of at least two of the quantum computing jobs, and wherein the quantum based run constraints comprise for each of the quantum computing jobs:
a number of qubits required to execute the quantum computing job based on error correction,
at least one preferred qubit specified for the quantum computing job,
availability of a set of qubits from the group of quantum computing devices comprising the number of qubits and the at least one preferred qubit, and
each qubit in the set of qubits is able to directly communicate with all other qubits in the set of qubits; and
execute at least one of the quantum computing jobs via the group of quantum computing devices based on the determined run order.
16. The computer program product of claim 15 , wherein the program instructions are further executable by the processor to cause the processor to:
determine the run order further based on respective estimated runtimes for the quantum computing jobs.
17. The computer program product of claim 15 , wherein the quantum based run constraints further comprises the quantum computing jobs must be executed to completion once started.
18. The computer program product of claim 15 , wherein the quantum based run constraints further comprises a longest-running computing job first criterion.
19. The computer program product of claim 15 , wherein the program instructions are further executable by the processor to cause the processor to:
determine the run order using a bin packing algorithm.
20. The computer program product of claim 15 , wherein the program instructions are further executable by the processor to cause the processor to:
modify the respective priorities of remaining ones of the quantum computing jobs based on changes to the respective levels of confidence determined based on completed quantum computing jobs of quantum computing jobs; and
determine a new run order of the remaining ones of the quantum computing jobs, based on the modified respective priorities.
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