OPTIMIZED EFFICIENT LPAR CAPACITY CONSOLIDATION

• US 20110106922A1
• Filed: 11/03/2009
• Published: 05/05/2011
• Est. Priority Date: 11/03/2009
• Status: Active Grant

• Current Assignee: ServiceNow Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Bouillet, Eric, Northway, Tedrick Neal, Johnson, Randy Scott, Zolotow, Clea Anne, Zhang, Li
• Granted Patent: US 8,700,752 B2
• Time in Patent Office: Days
• US Class Current: 709/221
• CPC Class Codes: G06F 9/5077 Logical partitioning of resources; Management or configuration of virtualized resources specific details on emulation or internal functioning of virtual machines G06F9/455
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

A method and system for optimizing a configuration of a set of LPARs and a set of servers that host the LPARs. Configuration data and optimization characteristics are received. By applying the configuration data and optimization characteristics, a best fit of the LPARs into the servers is determined, thereby determining an optimized configuration. The best fit is based on a variant of bin packing or multidimensional bin packing methodology. The optimized configuration is stored. In one embodiment, comparisons of shadow costs are utilized to determine an optimal placement of the LPARs in the servers. LPAR(s) in the set of LPARs are migrated to other server(s) in the set of servers, which results in the LPARs and servers being configured in the optimized configuration.

Claims

1. A computer-implemented method of optimizing a configuration of a plurality of logical partitions (LPARs) and a plurality of server computer systems (servers) that host the LPARs, said method comprising:

receiving configuration data that describes an enterprise configuration of said plurality of LPARs and said plurality of servers;

receiving optimization characteristic data that describes one or more characteristics on which an optimized version of said enterprise configuration (optimized enterprise configuration) is to be based;

a processor of a computer determining said optimized enterprise configuration by determining a best fit of said LPARs into said servers based on a bin packing methodology that applies said configuration data and said optimization characteristic data;

storing said optimized enterprise configuration; and

migrating one or more LPARs of said plurality of LPARs to one or more servers of said plurality of servers, wherein a result of said migrating is said plurality of LPARs and said plurality of servers being configured in said optimized enterprise configuration.

2. The method of claim 1, wherein said bin packing methodology is a multidimensional bin packing methodology that employs a plurality of dimensions, wherein said dimensions are requirements of resource types of a plurality of resource types included in said configuration data, and wherein said plurality of resource types specifies a plurality of resources required by said plurality of servers.

3. The method of claim 2, wherein said plurality of resources is constrained by a plurality of capacity constraints, wherein said determining said optimized enterprise configuration includes performing vector packing in said multidimensional bin packing methodology, and wherein said performing vector packing includes satisfying said capacity constraints individually on each resource type of said plurality of resource types.

4. The method of claim 2, wherein said determining said optimized enterprise configuration includes performing rectangular packing in said multidimensional bin packing methodology, wherein said performing rectangular packing includes representing said plurality of resource types as a plurality of sides of an n-dimensional cube and fitting a plurality of cubes in a cube without overlapping any cubes of said plurality of cubes, wherein said plurality of cubes is formed by utilizations of said plurality of resources by multiple LPARs of said plurality of LPARs, and wherein said cube is formed by a server of said plurality of servers receiving said multiple LPARs.

5. A computer system comprising a processor coupled to a computer-readable memory unit, said memory unit comprising a software application, said software application comprising instructions that when carried out by said processor implement the method of claim 1.

6. A computer program product, comprising a computer-readable storage medium having a computer-readable program code stored therein, said computer-readable program code containing instructions configured to be carried out by a processor of a computer system to implement the method of claim 1.

7. A process for supporting computing infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in a computer system comprising a processor, wherein said computer-readable code includes instructions that when carried out by said processor, causes the computer system to specify the method of claim 1.

8. A computer-implemented method of determining an optimal configuration of a plurality of logical partitions (LPARs) and a plurality of server computer systems (servers) that host the LPARs, said method comprising:

a processor of a computing system determining a draft configuration of said plurality of LPARs and said plurality of servers is a tentative version of said optimal configuration of said plurality of LPARs and said plurality of servers by performing an iteration of a first loop, wherein said performing said iteration of said first loop includes iteratively evaluating LPARs from a list of n LPARs in a second loop, and wherein said tentative version of said optimal configuration has a tentative final total cost;

determining no other draft configuration resulting from one or more additional iterations of said second loop or one or more additional iterations of said first loop has a draft total cost less than said tentative final total cost of said tentative version of said optimal configuration;

in response to said determining no other draft configuration has said draft total cost less than said tentative final total cost, saving said tentative version of said optimal configuration as a final version of said optimal configuration of said plurality of LPARs and said plurality of servers; and

migrating one or more LPARs of said plurality of LPARs to one or more servers of said plurality of servers so that said plurality of LPARs and said plurality of servers are configured in said final version of said optimal configuration.

9. The method of claim 8, further comprising, prior to said determining said draft configuration is said tentative version of said optimal configuration:

receiving a first specification of said plurality of LPARs and a plurality of resources required by each LPAR;

receiving a second specification of said plurality of servers and a plurality of available resources provided by said plurality of servers in a current configuration of said plurality of LPARs and said plurality of servers; and

receiving a plurality of optimization characteristics.

10. The method of claim 9, further comprising, prior to said iteratively evaluating LPARs, sorting said plurality of LPARs into said list of n LPARs in a descending order according to amounts of said resources required by each LPAR of said n LPARs.

11. The method of claim 9, further comprising initializing a migrate count to an initialization value prior to said determining said draft configuration is said tentative version of said optimal configuration, wherein said plurality of LPARs consists of said n LPARs, and wherein said iteratively evaluating LPARs from said list of n LPARs includes evaluating an i-th LPAR from said list of n LPARs in an i-th iteration of said second loop, wherein 1<

i<

n, and wherein said evaluating said i-th LPAR includes;

selecting an i-th LPAR from said list of n LPARs, wherein said i-th LPAR is in an i-th position in said list of LPARs, and wherein said i-th LPAR is hosted on a corresponding server of said plurality of servers in said current configuration;

identifying an i-th set of one or more target servers from said plurality of servers based on each server of said i-th set of one or more target servers having a capacity of said available resources that is sufficient to satisfy an amount of said resources required by said i-th LPAR;

determining an i-th optimal placement of said i-th LPAR on a target server of said i-th set of one or more target servers, wherein said determining said i-th optimal placement is based on said plurality of optimization characteristics, wherein said i-th optimal placement is included in an i-th draft configuration of said plurality of LPARs and said plurality of servers, and wherein said draft configuration of said plurality of LPARs and said plurality of servers is said i-th draft configuration;

determining said target server of said i-th set of one or more target servers is not said corresponding server hosting said i-th LPAR;

in response to said determining said target server of said i-th set of one or more target servers is not said corresponding server hosting said i-th LPAR, indicating a migration of said i-th LPAR to said target server of said i-th set of one or more target servers and updating said migrate count;

determining a total cost of said i-th draft configuration;

determining said total cost of said i-th draft configuration is less than a total cost of said current configuration and less than one or more total costs of one or more other draft configurations resulting from 1 . . . (i−

1)-th iterations of said second loop; and

in response to said determining said total cost of said i-th draft configuration is less than said total cost of said current configuration and less than said one or more total costs of one or more other draft configurations resulting from said 1 . . . (i−

1)-th iterations, saving said i-th draft configuration as said tentative version of said optimal configuration and saving said total cost of said i-th draft configuration as said tentative final total cost of said tentative version of said optimal configuration.

12. The method of claim 11, wherein said evaluating said i-th LPAR further includes:

determining m shadow costs of migrating said i-th LPAR from said corresponding server of said plurality of servers in said current configuration to each server of said i-th set of one or more target servers consisting of m target servers; and

identifying a least shadow cost of said m shadow costs,

wherein said determining said i-th optimal placement of said i-th LPAR on said target server of said i-th set of one or more target servers is based on said least shadow cost being a shadow cost of migrating said i-th LPAR from said corresponding server in said current configuration to said target server of said i-th set of one or more target servers.

13. The method of claim 11, wherein said determining no other draft configuration resulting from said one or more additional iterations of said second loop or said one or more additional iterations of said first loop has said draft total cost less than said tentative final total cost of said tentative version of said optimal configuration includes determining that one or more total costs of one or more draft configurations resulting from (1+1)-th . . . n-th iterations of said second loop are greater than or equal to said tentative final total cost of said tentative version of said optimal configuration.

14. A computer system comprising a processor coupled to a computer-readable memory unit, said memory unit comprising a software application, said software application comprising instructions that when carried out by said processor implement the method of claim 8.

15. A computer program product, comprising a computer readable storage medium having a computer readable program code stored therein, said computer readable program code containing instructions carried out by a processor of a computer system to implement a method of determining an optimal configuration of a plurality of logical partitions (LPARs) and a plurality of server computer systems (servers) that host the LPARs, said method comprising:

determining a draft configuration of said plurality of LPARs and said plurality of servers is a tentative version of said optimal configuration of said plurality of LPARs and said plurality of servers by performing an iteration of a first loop, wherein said performing said iteration of said first loop includes iteratively evaluating LPARs from a list of n LPARs in a second loop, and wherein said tentative version of said optimal configuration has a tentative final total cost;

determining no other draft configuration resulting from one or more additional iterations of said second loop or one or more additional iterations of said first loop has a draft total cost less than said tentative final total cost of said tentative version of said optimal configuration;

in response to said determining no other draft configuration has said draft total cost less than said tentative final total cost, saving said tentative version of said optimal configuration as a final version of said optimal configuration of said plurality of LPARs and said plurality of servers; and

migrating one or more LPARs of said plurality of LPARs to one or more servers of said plurality of servers so that said plurality of LPARs and said plurality of servers are configured in said final version of said optimal configuration.

16. The program product of claim 15, wherein said method further comprises, prior to said determining said draft configuration is said tentative version of said optimal configuration:

receiving a first specification of said plurality of LPARs and a plurality of resources required by each LPAR;

receiving a second specification of said plurality of servers and a plurality of available resources provided by said plurality of servers in a current configuration of said plurality of LPARs and said plurality of servers; and

receiving a plurality of optimization characteristics.

17. The program product of claim 16, wherein said method further comprises initializing a migrate count to an initialization value prior to said determining said draft configuration is said tentative version of said optimal configuration, wherein said plurality of LPARs consists of said n LPARs, and wherein said iteratively evaluating LPARs from said list of n LPARs includes evaluating an i-th LPAR from said list of n LPARs in an i-th iteration of said second loop, wherein 1<

i<

n, and wherein said evaluating said i-th LPAR includes;

selecting an i-th LPAR from said list of n LPARs, wherein said i-th LPAR is in an i-th position in said list of LPARs, and wherein said i-th LPAR is hosted on a corresponding server of said plurality of servers in said current configuration;

identifying an i-th set of one or more target servers from said plurality of servers based on each server of said i-th set of one or more target servers having a capacity of said available resources that is sufficient to satisfy an amount of said resources required by said i-th LPAR;

determining an i-th optimal placement of said i-th LPAR on a target server of said i-th set of one or more target servers, wherein said determining said i-th optimal placement is based on said plurality of optimization characteristics, wherein said i-th optimal placement is included in an i-th draft configuration of said plurality of LPARs and said plurality of servers, and wherein said draft configuration of said plurality of LPARs and said plurality of servers is said i-th draft configuration;

determining said target server of said i-th set of one or more target servers is not said corresponding server hosting said i-th LPAR;

in response to said determining said target server of said i-th set of one or more target servers is not said corresponding server hosting said i-th LPAR, indicating a migration of said i-th LPAR to said target server of said i-th set of one or more target servers and updating said migrate count;

determining a total cost of said i-th draft configuration;

determining said total cost of said i-th draft configuration is less than a total cost of said current configuration and less than one or more total costs of one or more other draft configurations resulting from 1 . . . (i−

1)-th iterations of said second loop; and

in response to said determining said total cost of said i-th draft configuration is less than said total cost of said current configuration and less than said one or more total costs of one or more other draft configurations resulting from said 1 . . . (i−

1)-th iterations, saving said i-th draft configuration as said tentative version of said optimal configuration and saving said total cost of said 1-th draft configuration as said tentative final total cost of said tentative version of said optimal configuration.

18. A process for supporting computing infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in a computing system comprising a processor, wherein said processor carries out instructions of said code to cause the computing system to specify a method of determining an optimal configuration of a plurality of logical partitions (LPARs) and a plurality of server computer systems (servers) that host the LPARs, said method comprising:

determining a draft configuration of said plurality of LPARs and said plurality of servers is a tentative version of said optimal configuration of said plurality of LPARs and said plurality of servers by performing an iteration of a first loop, wherein said performing said iteration of said first loop includes iteratively evaluating LPARs from a list of n LPARs in a second loop, and wherein said tentative version of said optimal configuration has a tentative final total cost;

determining no other draft configuration resulting from one or more additional iterations of said second loop or one or more additional iterations of said first loop has a draft total cost less than said tentative final total cost of said tentative version of said optimal configuration;

in response to said determining no other draft configuration has said draft total cost less than said tentative final total cost, saving said tentative version of said optimal configuration as a final version of said optimal configuration of said plurality of LPARs and said plurality of servers; and

migrating one or more LPARs of said plurality of LPARs to one or more servers of said plurality of servers so that said plurality of LPARs and said plurality of servers are configured in said final version of said optimal configuration.

19. The process claim 18, wherein said method further comprises, prior to said determining said draft configuration is said tentative version of said optimal configuration:

receiving a first specification of said plurality of LPARs and a plurality of resources required by each LPAR;

receiving a second specification of said plurality of servers and a plurality of available resources provided by said plurality of servers in a current configuration of said plurality of LPARs and said plurality of servers; and

receiving a plurality of optimization characteristics.

20. The process of claim 19, wherein said method further comprises initializing a migrate count to an initialization value prior to said determining said draft configuration is said tentative version of said optimal configuration, wherein said plurality of LPARs consists of said n LPARs, and wherein said iteratively evaluating LPARs from said list of n LPARs includes evaluating an i-th LPAR from said list of n LPARs in an i-th iteration of said second loop, wherein 1<

i<

n, and wherein said evaluating said i-th LPAR includes;

selecting an i-th LPAR from said list of n LPARs, wherein said i-th LPAR is in an i-th position in said list of LPARs, and wherein said i-th LPAR is hosted on a corresponding server of said plurality of servers in said current configuration;

identifying an i-th set of one or more target servers from said plurality of servers based on each server of said i-th set of one or more target servers having a capacity of said available resources that is sufficient to satisfy an amount of said resources required by said i-th LPAR;

determining an i-th optimal placement of said i-th LPAR on a target server of said i-th set of one or more target servers, wherein said determining said i-th optimal placement is based on said plurality of optimization characteristics, wherein said i-th optimal placement is included in an i-th draft configuration of said plurality of LPARs and said plurality of servers, and wherein said draft configuration of said plurality of LPARs and said plurality of servers is said i-th draft configuration;

deteimining said target server of said i-th set of one or more target servers is not said corresponding server hosting said i-th LPAR;

in response to said determining said target server of said i-th set of one or more target servers is not said corresponding server hosting said i-th LPAR, indicating a migration of said i-th LPAR to said target server of said i-th set of one or more target servers and updating said migrate count;

determining a total cost of said i-th draft configuration;

determining said total cost of said i-th draft configuration is less than a total cost of said current configuration and less than one or more total costs of one or more other draft configurations resulting from 1 . . . (i−

1)-th iterations of said second loop; and

in response to said determining said total cost of said i-th draft configuration is less than said total cost of said current configuration and less than said one or more total costs of one or more other draft configurations resulting from said 1 . . . (i−

1)-th iterations, saving said i-th draft configuration as said tentative version of said optimal configuration and saving said total cost of said i-th draft configuration as said tentative final total cost of said tentative version of said optimal configuration.