Multilevel parallel optimization using massively parallel structural dynamics

Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict ma...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Eldred, M.S. [verfasserIn] Giunta, A.A. van Bloemen Waanders, B.G.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2004

Schlagwörter:	parallel optimization structural dynamics surrogate-based optimization

Anmerkung:	© Springer-Verlag 2004

Übergeordnetes Werk:	Enthalten in: Structural and multidisciplinary optimization - Berlin : Springer, 1989, 27(2004), 1-2 vom: 01. Apr., Seite 97-109
Übergeordnetes Werk:	volume:27 ; year:2004 ; number:1-2 ; day:01 ; month:04 ; pages:97-109

Links:	Volltext

DOI / URN:	10.1007/s00158-003-0371-y

Katalog-ID:	SPR001305948

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allfields	10.1007/s00158-003-0371-y doi (DE-627)SPR001305948 (SPR)s00158-003-0371-y-e DE-627 ger DE-627 rakwb eng Eldred, M.S. verfasserin aut Multilevel parallel optimization using massively parallel structural dynamics 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. parallel optimization (dpeaa)DE-He213 structural dynamics (dpeaa)DE-He213 surrogate-based optimization (dpeaa)DE-He213 Giunta, A.A. aut van Bloemen Waanders, B.G. aut Enthalten in Structural and multidisciplinary optimization Berlin : Springer, 1989 27(2004), 1-2 vom: 01. Apr., Seite 97-109 (DE-627)271602503 (DE-600)1481279-4 1615-1488 nnns volume:27 year:2004 number:1-2 day:01 month:04 pages:97-109 https://dx.doi.org/10.1007/s00158-003-0371-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2004 1-2 01 04 97-109
spelling	10.1007/s00158-003-0371-y doi (DE-627)SPR001305948 (SPR)s00158-003-0371-y-e DE-627 ger DE-627 rakwb eng Eldred, M.S. verfasserin aut Multilevel parallel optimization using massively parallel structural dynamics 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. parallel optimization (dpeaa)DE-He213 structural dynamics (dpeaa)DE-He213 surrogate-based optimization (dpeaa)DE-He213 Giunta, A.A. aut van Bloemen Waanders, B.G. aut Enthalten in Structural and multidisciplinary optimization Berlin : Springer, 1989 27(2004), 1-2 vom: 01. Apr., Seite 97-109 (DE-627)271602503 (DE-600)1481279-4 1615-1488 nnns volume:27 year:2004 number:1-2 day:01 month:04 pages:97-109 https://dx.doi.org/10.1007/s00158-003-0371-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2004 1-2 01 04 97-109
allfields_unstemmed	10.1007/s00158-003-0371-y doi (DE-627)SPR001305948 (SPR)s00158-003-0371-y-e DE-627 ger DE-627 rakwb eng Eldred, M.S. verfasserin aut Multilevel parallel optimization using massively parallel structural dynamics 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. parallel optimization (dpeaa)DE-He213 structural dynamics (dpeaa)DE-He213 surrogate-based optimization (dpeaa)DE-He213 Giunta, A.A. aut van Bloemen Waanders, B.G. aut Enthalten in Structural and multidisciplinary optimization Berlin : Springer, 1989 27(2004), 1-2 vom: 01. Apr., Seite 97-109 (DE-627)271602503 (DE-600)1481279-4 1615-1488 nnns volume:27 year:2004 number:1-2 day:01 month:04 pages:97-109 https://dx.doi.org/10.1007/s00158-003-0371-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2004 1-2 01 04 97-109
allfieldsGer	10.1007/s00158-003-0371-y doi (DE-627)SPR001305948 (SPR)s00158-003-0371-y-e DE-627 ger DE-627 rakwb eng Eldred, M.S. verfasserin aut Multilevel parallel optimization using massively parallel structural dynamics 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. parallel optimization (dpeaa)DE-He213 structural dynamics (dpeaa)DE-He213 surrogate-based optimization (dpeaa)DE-He213 Giunta, A.A. aut van Bloemen Waanders, B.G. aut Enthalten in Structural and multidisciplinary optimization Berlin : Springer, 1989 27(2004), 1-2 vom: 01. Apr., Seite 97-109 (DE-627)271602503 (DE-600)1481279-4 1615-1488 nnns volume:27 year:2004 number:1-2 day:01 month:04 pages:97-109 https://dx.doi.org/10.1007/s00158-003-0371-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2004 1-2 01 04 97-109
allfieldsSound	10.1007/s00158-003-0371-y doi (DE-627)SPR001305948 (SPR)s00158-003-0371-y-e DE-627 ger DE-627 rakwb eng Eldred, M.S. verfasserin aut Multilevel parallel optimization using massively parallel structural dynamics 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. parallel optimization (dpeaa)DE-He213 structural dynamics (dpeaa)DE-He213 surrogate-based optimization (dpeaa)DE-He213 Giunta, A.A. aut van Bloemen Waanders, B.G. aut Enthalten in Structural and multidisciplinary optimization Berlin : Springer, 1989 27(2004), 1-2 vom: 01. Apr., Seite 97-109 (DE-627)271602503 (DE-600)1481279-4 1615-1488 nnns volume:27 year:2004 number:1-2 day:01 month:04 pages:97-109 https://dx.doi.org/10.1007/s00158-003-0371-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 27 2004 1-2 01 04 97-109
language	English
source	Enthalten in Structural and multidisciplinary optimization 27(2004), 1-2 vom: 01. Apr., Seite 97-109 volume:27 year:2004 number:1-2 day:01 month:04 pages:97-109
sourceStr	Enthalten in Structural and multidisciplinary optimization 27(2004), 1-2 vom: 01. Apr., Seite 97-109 volume:27 year:2004 number:1-2 day:01 month:04 pages:97-109
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	parallel optimization structural dynamics surrogate-based optimization
isfreeaccess_bool	false
container_title	Structural and multidisciplinary optimization
authorswithroles_txt_mv	Eldred, M.S. @@aut@@ Giunta, A.A. @@aut@@ van Bloemen Waanders, B.G. @@aut@@
publishDateDaySort_date	2004-04-01T00:00:00Z
hierarchy_top_id	271602503
id	SPR001305948
language_de	englisch
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author	Eldred, M.S.
spellingShingle	Eldred, M.S. misc parallel optimization misc structural dynamics misc surrogate-based optimization Multilevel parallel optimization using massively parallel structural dynamics
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topic_title	Multilevel parallel optimization using massively parallel structural dynamics parallel optimization (dpeaa)DE-He213 structural dynamics (dpeaa)DE-He213 surrogate-based optimization (dpeaa)DE-He213
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title	Multilevel parallel optimization using massively parallel structural dynamics
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title_full	Multilevel parallel optimization using massively parallel structural dynamics
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title_sort	multilevel parallel optimization using massively parallel structural dynamics
title_auth	Multilevel parallel optimization using massively parallel structural dynamics
abstract	Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. © Springer-Verlag 2004
abstractGer	Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. © Springer-Verlag 2004
abstract_unstemmed	Abstract A large-scale structural optimization of an electronics package has been completed using a massively parallel structural dynamics code. The optimization goals were to maximize safety margins for stress and acceleration resulting from transient impulse loads, while remaining within strict mass limits. The optimization process utilized nongradient, gradient, and approximate optimization methods in succession to modify shell thickness and foam density values within the electronics package. This combination of optimization methods was successful in improving the performance from an infeasible design that violated response allowables by a factor of two to a completely feasible design with positive design margins, while remaining within the mass limits. In addition, a tradeoff curve of mass versus safety margin was developed to facilitate the design decision process. These studies employed the ASCI Red supercomputer and used multiple levels of parallelism on up to 2560 processors. In total, a series of calculations were performed on ASCI Red in five days, where an equivalent calculation on a single desktop computer would have taken greater than 12 years to complete. This paper conveys the approaches, results, and lessons learnt from this large-scale production design application. © Springer-Verlag 2004
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up_date	2024-07-03T21:40:25.411Z
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