Information processing apparatus, information processing method, and program

Abstract

To improve the trade-off relationship between wait time and cloud cost.SOLUTION: An information processing apparatus includes: a calculation unit which calculates a cloud appropriateness value using a cost when a cloud is used for a job to be scheduled and an index indicative of the quantity of all jobs that are yet to be allocated to a server and waiting to be scheduled; and a determination unit which determines, in accordance with the cloud appropriateness value, whether to offload the job to be scheduled to the cloud.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an information processing method, and a program that utilize cloud bursting. [Background technology]

[0002] When the load on the servers in an HPC (High Performance Computing) system is high (high load), the waiting time from when a job is submitted until the processing starts can be long. Therefore, technologies such as cloud bursting have been disclosed as a technique for shortening the waiting time. In cloud bursting, for example, it is determined whether or not a job can be executed using a free server in a cloud that can communicate with the HPC system, and if so, the free server is made to process the job.

[0003] As a related technique, Cited Document 1 discloses a burstable instance recommendation device that appropriately recommends burstable instances that are candidates for instance migration. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-197039 Summary of the Invention [Problem to be solved by the invention]

[0005] To shorten the average server latency of an HPC system, more processing can be done in the cloud. However, doing more processing in the cloud increases cloud costs. In other words, there is a trade-off between average latency and cloud costs.

[0006] It should be noted that the techniques described in the above cited reference 1 and the like do not improve the trade-off between average latency and cloud costs.

[0007] An example objective of the present disclosure is to improve the trade-off between average latency and cloud cost. [Means for solving the problem]

[0008] In order to achieve the above object, an information processing device according to one aspect of the present disclosure includes: a calculation unit that calculates a cloud optimum value using an index that indicates the amount of all jobs waiting to be scheduled before being assigned to a server and a cost of using the cloud for a job to be scheduled; a decision unit that decides whether to offload the job to be scheduled to a cloud according to the cloud optimum value; The present invention is characterized by having the following.

[0009] In order to achieve the above object, an information processing method according to one aspect of the present disclosure includes: An information processing device, Calculate the cloud appropriate value using an index that indicates the amount of all jobs waiting to be scheduled before being assigned to the server and the cost of using the cloud for the jobs to be scheduled; determining whether to offload the scheduled job to a cloud according to the cloud suitability value; It is characterized by:

[0010] Furthermore, in order to achieve the above object, a program according to one aspect of the present disclosure includes: On the computer, Calculate the cloud appropriate value using an index representing the amount of all jobs waiting to be scheduled before being assigned to the server and the cost of using the cloud for the job to be scheduled; determining whether to offload the scheduled job to a cloud according to the cloud suitability value; It is characterized by: Effect of the Invention

[0011] As described above, according to the present disclosure, it is possible to improve the trade-off between average latency and cloud costs. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an information processing device. [Diagram 2] FIG. 2 is a diagram illustrating an example of a configuration of a system having an information processing device. [Diagram 3] FIG. 3 is a diagram illustrating an example of the operation of the information processing device. [Figure 4] FIG. 4 is a diagram showing the relationship between waiting time and cost. [Diagram 5] FIG. 5 is a diagram showing the relationship between waiting time and cost. [Figure 6] FIG. 6 is a diagram illustrating an example of a computer that realizes the information processing device in the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, an embodiment will be described with reference to the drawings. In the drawings described below, elements having the same or corresponding functions are denoted by the same reference numerals, and repeated description thereof may be omitted.

[0014] (Embodiment) The configuration of an information processing device in an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram for explaining an example of the configuration of an information processing device.

[0015] [Device configuration] 1, the information processing device 10 improves the trade-off between the average latency and the cloud cost. In addition, in the example of FIG. 1, the information processing device 10 includes a calculation unit 11 and a determination unit 12.

[0016] The calculation unit 11 calculates a cloud optimum value using an index indicating the amount of all jobs waiting to be scheduled before being assigned to a server and a cost (cloud cost) incurred when using the cloud (cloud server) for a job to be scheduled.

[0017] Specifically, the index represents the amount of all jobs submitted from a terminal device before allocation to a server. Furthermore, the timing of a job includes, for example, the timing of submission, allocation, completion, etc. The timing of submission is the timing when a terminal submits a job to an information processing device at an HPC center. The timing of allocation is the timing when the information processing device assigns the submitted job to a server and execution of the job starts on the server. The timing of completion is the timing when execution of a job executed on a server is completed.

[0018] The job to be scheduled is one of a set of jobs in the waiting time, which is the time from the time of submission to the time of allocation.

[0019] The determination unit 12 determines whether or not to offload the scheduled job to the cloud, depending on the cloud optimum value.

[0020] A job is a job input from each of a plurality of terminal devices to the information processing device 10. A job includes information such as a server, a program and data to be executed in the cloud, the number of servers to be used when executing the program (requested server number), and the time required to execute the program (requested time).

[0021] The cost (cloud cost) is, for example, the usage fee for the cloud (cloud server). The cloud optimum value is information used to improve the trade-off relationship between latency and cost, and is information for determining whether to offload to the cloud.

[0022] In this way, in the embodiment, a cloud optimum value is calculated using an index representing the quantity of all jobs waiting to be scheduled and the cost of using the cloud for the jobs to be scheduled, thereby improving the trade-off between waiting time and cloud costs.

[0023] [System Configuration] The configuration of the information processing device 10 in the embodiment will be described more specifically with reference to the example of Fig. 2. Fig. 2 is a diagram for explaining an example of the configuration of a system having an information processing device.

[0024] In the example of Fig. 2, the system 100 has at least an HPC center 1, a cloud 30, terminal devices 40 (40a, 40b, 40c, etc.), and an output device 50. In the example of Fig. 2, the HPC center 1 has at least an information processing device 10 and a server 20. The information processing device 10, the server 20, the cloud 30, and the terminal device 40 are connected via a communication network.

[0025] The network is a general network constructed using communication lines such as the Internet, a LAN (Local Area Network), a dedicated line, a telephone line, an in-house network, a mobile communication network, Bluetooth (registered trademark), or Wi-Fi (Wireless Fidelity) (registered trademark).

[0026] The information processing device 10 is, for example, an information processing device such as a CPU (Central Processing Unit), a programmable device such as an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing Unit), or a circuit equipped with any one or more of these, a scheduler, etc.

[0027] The server 20 includes one or more servers. Each of the servers constituting the server 20 is an information processing device such as a CPU, a programmable device such as an FPGA, a GPU, or a circuit equipped with any one or more of them.

[0028] The cloud 30 has one or more servers. Each of the servers constituting the server 30 is, for example, an information processing device such as a CPU, a programmable device such as an FPGA, a GPU, or a circuit equipped with any one or more of them, or a server computer.

[0029] The terminal devices 40 (40a, 40b, 40c, . . . ) are information processing devices such as personal computers and mobile terminals equipped with a CPU, an FPGA, or both.

[0030] The output device 50 acquires output information, which is converted into an outputtable format and will be described later, and outputs generated images and sounds based on the output information. The output device 50 is, for example, an image display device using a liquid crystal, an organic EL (Electro Luminescence), or a CRT (Cathode Ray Tube). Furthermore, the image display device may also include an audio output device such as a speaker. The output device 50 may also be a printing device such as a printer.

[0031] The information processing device will now be described in detail. The information processing device 10 includes a calculation unit 11, a determination unit 12, a distribution unit 13, and an output information generation unit 14. First, the operations of the calculation unit 11 and the determination unit 12 will be described using the following examples (1) to (4).

[0032] (1) A case where the number of all jobs from input to before allocation (from the timing of input to the timing of allocation) and the cost are used will be described. When the index is the number Jk of all jobs from input to before allocation, the calculation unit 11 divides it by the cost (cloud cost) Cc of the schedule target to calculate the cloud appropriate value Ca1 (=Jk / Cc).

[0033] The determination unit 12 determines whether or not to offload a scheduled job to the cloud 30 based on the cloud appropriateness value Ca1 and a preset first threshold value Th1. The first threshold value Th1 is determined, for example, by an experiment, a simulation, or the like. The first threshold value Th1 may be manually set by an administrator or the like.

[0034] (2) A case where the sum of the resource amounts required by all jobs from input to allocation and the cost are used will be described. When the index is the sum of the resource amounts Rak required by all jobs from input to allocation (SRa = ΣRak (k = 1, 2 · · · n) = Ra1 + Ra2 + · · · + Ran: n is a positive integer), the calculation unit 11 divides the sum of the resource amounts required by all jobs SRa by the cost (cloud cost) Cc to calculate the cloud optimum value Ca2 (= SRa / Cc).

[0035] The resource amount is, for example, a value Ra (=Rsn×Rst) obtained by multiplying the number of requested servers (requested server count) Rsn included in a job by the time (requested time) Rst required to process the requested job.

[0036] The determination unit 12 determines whether or not to offload the scheduled job to the cloud 30 based on the cloud appropriateness value Ca2 and a preset second threshold value Th2. The second threshold value Th2 is determined, for example, by an experiment, a simulation, or the like. The second threshold value Th2 may be manually set by an administrator or the like.

[0037] (3) A case will be described in which the number of all jobs from input to before allocation and the amount of resources required by the jobs to be scheduled are used. When the index is the number Jk of all jobs from input to before allocation, the calculation unit 11 calculates the cloud optimum value Ca3 (=Jk / Rak) by dividing the number Jk of all jobs by the amount of resources Rak required by the jobs to be scheduled.

[0038] The resource amount Rak is the amount of resources required when a scheduled job is executed in the cloud 30 .

[0039] The determination unit 12 determines whether or not to offload the scheduled job to the cloud 30 based on the cloud appropriateness value Ca3 and a preset third threshold value Th3. The third threshold value Th3 is determined, for example, by an experiment, a simulation, or the like. The third threshold value Th3 may be manually set by an administrator or the like.

[0040] (4) A case where the sum of the resource amounts required by all jobs and the resource amount required by the job to be scheduled are used will be described. When the index is the sum of the resource amounts required by all jobs SRa, the calculation unit 11 divides the sum of the resource amounts required by all jobs Rat by the resource amount required by the job to be scheduled Rak to calculate the cloud optimum value Ca4 (=SRa / Rak).

[0041] The determination unit 12 determines whether or not to offload the scheduled job to the cloud 30 based on the cloud appropriateness value Ca4 and a fourth threshold value Th4 set in advance. The fourth threshold value Th4 is determined, for example, by an experiment, a simulation, or the like. The fourth threshold value Th4 may be set manually by an administrator or the like.

[0042] When the determination unit 12 determines that the job to be scheduled is to be offloaded to the cloud 30, the distribution unit 13 transmits the job to be scheduled to the cloud 30. On the other hand, when the determination unit 12 determines that the job to be scheduled is not to be offloaded to the cloud 30, the distribution unit 13 transmits the job to be scheduled to the server 20.

[0043] The output information generating unit 13 generates output information to be displayed on the output device 50 by combining one or more of at least the number of all jobs, the sum of the amounts of resources required by all jobs, the cost, the amount of resources required by jobs to be scheduled, the cloud optimum value, information on jobs to be scheduled, the determination result of the determining unit 12, and the time. Thereafter, the output information generating unit 13 outputs the output information to the output device 50. However, the output information generating unit 13 does not have to be provided in the information processing device 10.

[0044] [Device operation] Next, the operation of the information processing device in the embodiment will be described with reference to FIG. 3. FIG. 3 is a diagram for explaining an example of the operation of the information processing device. In the following description, the diagram will be referred to as appropriate. Also, in the embodiment, an information processing method is implemented by operating the information processing device. Therefore, the description of the information processing method in the embodiment will be replaced with the description of the operation of the information processing device below.

[0045] In the example of Figure 3, first, the calculation unit 11 calculates a cloud optimum value using an index representing the amount of all jobs waiting to be scheduled and the cost (cloud cost) of using the cloud 30 for the job to be scheduled (step A1).

[0046] Next, the determination unit 12 determines whether or not to offload the job to be scheduled to the cloud 30, depending on the cloud suitability value (step A2).

[0047] Steps A1 and A2 will be explained using the following examples (1) to (4). (1) A case will be described in which the number of all jobs from input to before allocation (from the timing of input to the timing of allocation) and the cost are used in steps A1 and A2. In step A1 of (1), when the index is the number Jk of all jobs from input to before allocation, the calculation unit 11 divides it by the cost (cloud cost) Cc to be scheduled to calculate the cloud appropriate value Ca1 (=Jk / Cc).

[0048] In step A2 of (1), the decision unit 12 decides whether or not to offload the job to be scheduled to the cloud 30 based on the cloud appropriateness value Ca1 and a first threshold value Th1 set in advance.

[0049] (2) A case will be described in which the sum of the resource amounts required by all jobs from the time of input until allocation and the cost are used. In step A1 of (2), when the index is the sum of the resource amounts Rak required by all jobs from the time of input until allocation (SRa=ΣRak(k=1,2···n)=Ra1+Ra2+···+Ran: n is a positive integer), the calculation unit 11 divides the sum of the resource amounts required by all jobs SRa by the cost (cloud cost) Cc to calculate the cloud optimum value Ca2 (=SRa / Cc).

[0050] In step A2 of (2), the decision unit 12 decides whether or not to offload the job to be scheduled to the cloud 30 based on the cloud appropriateness value Ca2 and a second threshold value Th2 set in advance.

[0051] (3) A case will be described in which the number of all jobs from input to before allocation and the amount of resources required by the jobs to be scheduled are used. In step A1 of (3), when the index is the number Jk of all jobs from input to before allocation, the calculation unit 11 calculates the cloud optimum value Ca3 (=Jk / Rak) by dividing the number Jk of all jobs by the amount of resources Rak required by the jobs to be scheduled.

[0052] In step A2 of (3), the decision unit 12 decides whether or not to offload the job to be scheduled to the cloud 30 based on the cloud appropriateness value Ca3 and a third threshold value Th3 set in advance.

[0053] (4) A case where the sum of the resource amounts required by all jobs and the resource amount required by the job to be scheduled are used will be described. In step A1 of (4), when the index is the sum of the resource amounts required by all jobs SRa, the calculation unit 11 divides the sum of the resource amounts required by all jobs SRa by the resource amount Rak required by the job to be scheduled to calculate the cloud optimum value Ca4 (=SRa / Rak).

[0054] In step A2 of (4), the decision unit 12 decides whether or not to offload the job to be scheduled to the cloud, based on the cloud appropriateness value Ca4 and a fourth threshold value Th4 set in advance.

[0055] Next, if the determination unit 12 decides to offload the job to be scheduled to the cloud 30 (step A3: Yes), the distribution unit 13 transmits the job to be scheduled to the cloud 30 (step A5). On the other hand, if the determination unit 12 decides not to offload the job to be scheduled to the cloud 30 (step A3: No), the distribution unit 13 transmits the job to be scheduled to the server 20 (step A4). In this manner, the processes of steps A1 to A5 described above are repeatedly executed.

[0056] [Effects of the embodiment] As described above, according to the embodiment, a cloud optimum value is calculated using an index representing the volume of all jobs waiting to be scheduled and the cost of using the cloud for the jobs to be scheduled, thereby improving the trade-off between waiting time and cloud costs.

[0057] In the conventional technology, an upper limit on the number of servers to be temporarily used in the cloud 30 is set in advance, and for a job to be scheduled, if the number of available servers in the server 20 is less than the number of servers required by the job and the number of available servers in the cloud 30, i.e., the upper limit minus the number of allocated servers, is equal to or greater than the number of servers required by the job, the job is sent to the cloud 30.

[0058] That is, the average waiting time can be reduced by increasing the upper limit on the number of servers in the cloud 30. However, using more servers in the cloud 30 increases costs (cloud costs).

[0059] Figures 4 and 5 show the relationship between latency and cost. For example, these are the results of evaluations using a general workload. The evaluation was conducted using the "Logs of Real Parallel Workloads from Production Systems"<https: / / www.cs.huji.ac.il / labs / parallel / workload / logs.html> Among the many workloads published on the Internet, we used two workloads: "The ANL Intrepid log" (hereafter referred to as ANL) and "The KIT ForHLR II log" (hereafter referred to as KIT). Figure 4 shows the evaluation results for ANL. Figure 5 shows the evaluation results for KIT.

[0060] The line for cloud serves (●) in Figures 4 and 5 represents the relationship between average waiting time and cost when using conventional technology. The line for reward threshold (1) (▼) and the line for reward threshold (2) (▲) in Figures 4 and 5 represent the relationship between average waiting time and cost when using information processing device 10 of the embodiment.

[0061] The reward threshold (1) (▼) line in Figures 4 and 5 represents the evaluation result when using the number of all jobs from submission to allocation and the amount of resources required by the jobs to be scheduled, as explained in (3) above. Also, the reward threshold (2) (▲) line in Figures 4 and 5 represents the evaluation result when using the sum of the amount of resources required by all jobs and the amount of resources required by the jobs to be scheduled, as explained in (4) above.

[0062] As shown in Figures 4 and 5, the reward threshold (1) (▼) and reward threshold (2) (▲) lines show a lower average latency to cost ratio than the cloud serves (●) line. In other words, the trade-off between latency and cloud costs has been improved.

[0063] [program] The program in the embodiment may be a program that causes a computer to execute steps A1 to A5 shown in Fig. 3. By installing and executing this program in a computer, the information processing device and the information processing method in the embodiment can be realized. In this case, the processor of the computer functions as the calculation unit 11, the determination unit 12, and the distribution unit 13 and performs the processing.

[0064] The program in the embodiment may be executed by a computer system constructed by a plurality of computers. In this case, for example, each computer may function as any one of the calculation unit 11, the determination unit 12, and the distribution unit 13.

[0065] [Physical configuration] Here, a computer that realizes an information processing device by executing a program in the embodiment will be described with reference to Fig. 6. Fig. 6 is a diagram for explaining an example of a computer that realizes an information processing device in the embodiment.

[0066] 6, the computer 110 includes a CPU (Central Processing Unit) 111, a main memory 112, a storage device 113, an input interface 114, a display controller 115, a data reader / writer 116, and a communication interface 117. These components are connected to each other via a bus 121 so as to be able to communicate data with each other. Note that the computer 110 may include a GPU or an FPGA in addition to the CPU 111 or instead of the CPU 111.

[0067] The CPU 111 loads a program in the embodiment, which is composed of a group of codes and is stored in the storage device 113, into the main memory 112, and executes each code in a predetermined order to perform various calculations. The main memory 112 is typically a volatile storage device such as a DRAM (Dynamic Random Access Memory).

[0068] Moreover, the program in the embodiment is provided in a state stored in a computer-readable recording medium 120. Note that the program in the embodiment may be distributed on the Internet connected via the communication interface 117.

[0069] Specific examples of the storage device 113 include a hard disk drive and a semiconductor storage device such as a flash memory. The input interface 114 mediates data transmission between the CPU 111 and input devices 118 such as a keyboard and a mouse. The display controller 115 is connected to a display device 119 and controls the display on the display device 119.

[0070] Data reader / writer 116 mediates data transmission between CPU 111 and recording medium 120, reads programs from recording medium 120, and writes processing results in computer 110 to recording medium 120. Communication interface 117 mediates data transmission between CPU 111 and other computers.

[0071] Specific examples of recording medium 120 include general-purpose semiconductor storage devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital), magnetic recording media such as a flexible disk, or optical recording media such as a CD-ROM (Compact Disk Read Only Memory).

[0072] The information processing device 10 in the embodiment can be realized not by a computer with a program installed, but by hardware corresponding to each part, for example, an electronic circuit. Furthermore, the information processing device 10 may be partially realized by a program and the remaining part by hardware. In the embodiment, the computer is not limited to the computer shown in FIG. 6.

[0073] [Note] The following supplementary notes are further disclosed regarding the above-described embodiments. A part or all of the above-described embodiments can be expressed by (Supplementary Note 1) to (Supplementary Note 18) described below, but are not limited to the following descriptions.

[0074] (Appendix 1) a calculation unit that calculates a cloud optimum value using an index that indicates the amount of all jobs waiting to be scheduled before being assigned to a server and a cost of using the cloud for a job to be scheduled; a decision unit that decides whether to offload the job to be scheduled to a cloud according to the cloud optimum value; An information processing device having the above configuration.

[0075] (Appendix 2) When the index is the number of all the jobs, the calculation unit calculates a cloud optimum value by dividing the number of all the jobs by the cost; the determination means determines whether or not to offload the scheduled job to the cloud based on the cloud appropriateness value and a first threshold value set in advance; 2. An information processing device according to claim 1.

[0076] (Appendix 3) When the index is a sum of the resource amounts required by all of the jobs, the calculation unit calculates a cloud optimum value by dividing the sum of the resource amounts required by all of the jobs by the cost; the determination unit determines whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a second threshold value set in advance; 2. An information processing device according to claim 1.

[0077] (Appendix 4) When the index is the number of all the jobs, the calculation unit calculates a cloud optimum value by dividing the number of all the jobs by an amount of resources required by the job to be scheduled; the determination unit determines whether to offload the job to be scheduled to the cloud based on the cloud appropriateness value and a third threshold value set in advance; 2. An information processing device according to claim 1.

[0078] (Appendix 5) when the index is a sum of the resource amounts required by all of the jobs, the calculation unit calculates a cloud optimum value by dividing the sum of the resource amounts required by all of the jobs by the resource amount required by the job to be scheduled; the determination unit determines whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a fourth threshold value set in advance; 2. An information processing device according to claim 1.

[0079] (Appendix 6) The resource amount is a value obtained by multiplying the number of requested servers included in each of the jobs by the time required to process the requested jobs. 6. An information processing device according to any one of appendix 2 to 5.

[0080] (Appendix 7) An information processing device, Calculate the cloud appropriate value using an index that indicates the amount of all jobs waiting to be scheduled before being assigned to the server and the cost of using the cloud for the job to be scheduled; determining whether to offload the scheduled job to a cloud according to the cloud suitability value; Information processing methods.

[0081] (Appendix 8) If the indicator is the number of all the jobs, calculate a cloud fairness value by dividing the number of all the jobs by the cost; determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a first threshold value set in advance; 8. An information processing method as described in Appendix 7.

[0082] (Appendix 9) When the index is a sum of the resource amounts required by all of the jobs, the sum of the resource amounts required by all of the jobs is divided by the cost to calculate a cloud appropriate value; determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a second threshold value set in advance; 8. An information processing method as described in Appendix 7.

[0083] (Appendix 10) If the indicator is the number of all the jobs, calculate a cloud fairness value by dividing the number of all the jobs by the amount of resources required by the scheduled job; determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a third threshold value set in advance; 8. An information processing method as described in Appendix 7.

[0084] (Appendix 11) If the index is a sum of the resource amounts required by all of the jobs, calculate a cloud appropriate value by dividing the sum of the resource amounts required by all of the jobs by the resource amount required by the job to be scheduled; determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a fourth threshold value set in advance; 8. An information processing method as described in Appendix 7.

[0085] (Appendix 12) The resource amount is a value obtained by multiplying the number of requested servers included in each of the jobs by the time required to process the requested jobs. 12. An information processing method according to any one of appendix 8 to 11.

[0086] (Appendix 13) On the computer, Calculate the cloud appropriate value using an index representing the amount of all jobs waiting to be scheduled before being assigned to the server and the cost of using the cloud for the job to be scheduled; determining whether to offload the scheduled job to a cloud according to the cloud suitability value; A program containing instructions.

[0087] (Appendix 14) If the indicator is the number of all the jobs, the number of all the jobs is divided by the cost to calculate a cloud appropriateness value; determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a first threshold value set in advance; 14. The program according to claim 13.

[0088] (Appendix 15) When the index is a sum of the resource amounts required by all of the jobs, the sum of the resource amounts required by all of the jobs is divided by the cost to calculate a cloud optimum value; determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a second threshold value set in advance; 14. The program according to claim 13.

[0089] (Appendix 16) If the indicator is the number of all the jobs, the number of all the jobs is divided by the amount of resources required by the scheduled job to calculate a cloud fairness value. determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a third threshold value set in advance; 14. The program according to claim 13.

[0090] (Appendix 17) When the index is a sum of the resource amounts required by all of the jobs, the sum of the resource amounts required by all of the jobs is divided by the resource amount required by the job to be scheduled to calculate a cloud optimum value; determining whether to offload the scheduled job to the cloud based on the cloud appropriateness value and a fourth threshold value set in advance; 14. The program according to claim 13.

[0091] (Appendix 18) The resource amount is a value obtained by multiplying the number of requested servers included in each of the jobs by the time required to process the requested jobs. 18. The program according to any one of appendixes 14 to 17.

[0092] Although the invention has been described above with reference to the embodiments, the invention is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the invention within the scope of the invention. [Industrial Applicability]

[0093] The above description provides an improved trade-off between latency and cloud costs, and is useful in applications where cloud bursting is required. [Explanation of symbols]

[0094] 1 HPC Center 10. Information processing device 11 Calculation section 12 Decision Section 13 Distribution section 14 Output information generation unit 20 Servers 30. Cloud 40, 40a, 40b, 40c Terminal device 50 Output Device 100 Systems 110 Computer 111 CPU 112 Main memory 113 Storage device 114 Input Interface 115 Display Controller 116 Data Reader / Writer 117 Communication Interface 118 Input Devices 119 Display device 120 Recording media 121 Bus

Claims

1. A calculation means for calculating a cloud optimum value using an index representing the amount of all jobs waiting to be scheduled before being assigned to a server and a cost of using the cloud for a job to be scheduled; a decision unit that decides whether to offload the scheduled job to a cloud according to the cloud suitability value; An information processing device having the above configuration.

2. When the index is the number of all the jobs, the calculation means calculates a cloud optimum value by dividing the number of all the jobs by the cost; the determination means determines whether or not to offload the scheduled job to the cloud based on the cloud appropriateness value and a first threshold value set in advance; The information processing device according to claim 1 .

3. When the index is a sum of the resource amounts required by all of the jobs, the calculation means calculates a cloud optimum value by dividing the sum of the resource amounts required by all of the jobs by the cost; the determination means determines whether or not to offload the scheduled job to the cloud based on the cloud appropriateness value and a second threshold value set in advance; The information processing device according to claim 1 .

4. When the index is the number of all the jobs, the calculation means calculates a cloud optimum value by dividing the number of all the jobs by the amount of resources required by the job to be scheduled. the determination means determines whether or not to offload the scheduled job to the cloud based on the cloud appropriateness value and a third threshold value set in advance; The information processing device according to claim 1 .

5. When the index is a sum of the resource amounts required by all of the jobs, the calculation means calculates a cloud optimum value by dividing the sum of the resource amounts required by all of the jobs by the resource amount required by the job to be scheduled. the determination means determines whether or not to offload the scheduled job to the cloud based on the cloud appropriateness value and a fourth threshold value set in advance; The information processing device according to claim 1 .

6. The resource amount is a value obtained by multiplying the number of requested servers included in each of the jobs by the time required to process the requested jobs.

6. The information processing device according to claim 3.

7. An information processing device, Calculate the cloud appropriate value using an index that indicates the amount of all jobs waiting to be scheduled before being assigned to the server and the cost of using the cloud for the job to be scheduled; determining whether to offload the scheduled job to a cloud according to the cloud suitability value; Information processing methods.

8. On the computer, Calculate the cloud appropriate value using an index representing the amount of all jobs waiting to be scheduled before being assigned to the server and the cost of using the cloud for the job to be scheduled; determining whether to offload the scheduled job to a cloud according to the cloud suitability value; A program containing instructions.

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