Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster
Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the m...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cutillas-Lozano, José-Matías [verfasserIn] Giménez, Domingo [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
Parameterized metaheuristic schemes |
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| Übergeordnetes Werk: |
Enthalten in: Soft Computing - Springer-Verlag, 2003, 21(2016), 19 vom: 27. Sept., Seite 5557-5572 |
|---|---|
| Übergeordnetes Werk: |
volume:21 ; year:2016 ; number:19 ; day:27 ; month:09 ; pages:5557-5572 |
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| DOI / URN: |
10.1007/s00500-016-2371-z |
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| 520 | |a Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. | ||
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10.1007/s00500-016-2371-z doi (DE-627)SPR006493920 (SPR)s00500-016-2371-z-e DE-627 ger DE-627 rakwb eng Cutillas-Lozano, José-Matías verfasserin aut Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. Parameterized metaheuristic schemes (dpeaa)DE-He213 Parallel metaheuristics (dpeaa)DE-He213 Message-passing metaheuristic schemes (dpeaa)DE-He213 Heterogeneous computing (dpeaa)DE-He213 Auto-tuning (dpeaa)DE-He213 Giménez, Domingo verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 19 vom: 27. Sept., Seite 5557-5572 (DE-627)SPR006469531 nnns volume:21 year:2016 number:19 day:27 month:09 pages:5557-5572 https://dx.doi.org/10.1007/s00500-016-2371-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 19 27 09 5557-5572 |
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10.1007/s00500-016-2371-z doi (DE-627)SPR006493920 (SPR)s00500-016-2371-z-e DE-627 ger DE-627 rakwb eng Cutillas-Lozano, José-Matías verfasserin aut Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. Parameterized metaheuristic schemes (dpeaa)DE-He213 Parallel metaheuristics (dpeaa)DE-He213 Message-passing metaheuristic schemes (dpeaa)DE-He213 Heterogeneous computing (dpeaa)DE-He213 Auto-tuning (dpeaa)DE-He213 Giménez, Domingo verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 19 vom: 27. Sept., Seite 5557-5572 (DE-627)SPR006469531 nnns volume:21 year:2016 number:19 day:27 month:09 pages:5557-5572 https://dx.doi.org/10.1007/s00500-016-2371-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 19 27 09 5557-5572 |
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10.1007/s00500-016-2371-z doi (DE-627)SPR006493920 (SPR)s00500-016-2371-z-e DE-627 ger DE-627 rakwb eng Cutillas-Lozano, José-Matías verfasserin aut Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. Parameterized metaheuristic schemes (dpeaa)DE-He213 Parallel metaheuristics (dpeaa)DE-He213 Message-passing metaheuristic schemes (dpeaa)DE-He213 Heterogeneous computing (dpeaa)DE-He213 Auto-tuning (dpeaa)DE-He213 Giménez, Domingo verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 19 vom: 27. Sept., Seite 5557-5572 (DE-627)SPR006469531 nnns volume:21 year:2016 number:19 day:27 month:09 pages:5557-5572 https://dx.doi.org/10.1007/s00500-016-2371-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 19 27 09 5557-5572 |
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10.1007/s00500-016-2371-z doi (DE-627)SPR006493920 (SPR)s00500-016-2371-z-e DE-627 ger DE-627 rakwb eng Cutillas-Lozano, José-Matías verfasserin aut Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. Parameterized metaheuristic schemes (dpeaa)DE-He213 Parallel metaheuristics (dpeaa)DE-He213 Message-passing metaheuristic schemes (dpeaa)DE-He213 Heterogeneous computing (dpeaa)DE-He213 Auto-tuning (dpeaa)DE-He213 Giménez, Domingo verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 19 vom: 27. Sept., Seite 5557-5572 (DE-627)SPR006469531 nnns volume:21 year:2016 number:19 day:27 month:09 pages:5557-5572 https://dx.doi.org/10.1007/s00500-016-2371-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 19 27 09 5557-5572 |
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10.1007/s00500-016-2371-z doi (DE-627)SPR006493920 (SPR)s00500-016-2371-z-e DE-627 ger DE-627 rakwb eng Cutillas-Lozano, José-Matías verfasserin aut Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. Parameterized metaheuristic schemes (dpeaa)DE-He213 Parallel metaheuristics (dpeaa)DE-He213 Message-passing metaheuristic schemes (dpeaa)DE-He213 Heterogeneous computing (dpeaa)DE-He213 Auto-tuning (dpeaa)DE-He213 Giménez, Domingo verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 19 vom: 27. Sept., Seite 5557-5572 (DE-627)SPR006469531 nnns volume:21 year:2016 number:19 day:27 month:09 pages:5557-5572 https://dx.doi.org/10.1007/s00500-016-2371-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 19 27 09 5557-5572 |
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Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. |
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Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. |
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Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. Furthermore, optimized execution times can be achieved with auto-tuning techniques based on theoretical–empirical models of the execution time. |
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c |
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false |
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| doi_str |
10.1007/s00500-016-2371-z |
| up_date |
2024-07-03T23:16:39.554Z |
| _version_ |
1803601680326983680 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR006493920</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20201124002830.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00500-016-2371-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR006493920</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00500-016-2371-z-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Cutillas-Lozano, José-Matías</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Optimizing a parameterized message-passing metaheuristic scheme on a heterogeneous cluster</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper studies the development of message-passing parameterized schemes of metaheuristics and the use of auto-tuning techniques to optimize their execution time. Previous parameterized schemes on shared-memory are extended with new metaheuristic-parallelism parameters representing the migration frequency, the size of the migration and the number of processes. An optimization Problem of Electricity Consumption in Exploitation of Wells is used as test case. Experimental results in heterogeneous systems are reported for this problem, and the influence of the parallelism parameters is studied. The message-passing scheme proves to be preferable to the shared-memory scheme in terms of execution time, giving similar results for the goodness of the solutions. In the executions in a heterogeneous cluster, the best experimental results are obtained in terms of speed-up and quality of the solution by mapping a number of processes close to the value of the population size, and considering the relative speeds of the components of the heterogeneous system. 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7.4020987 |