Porting ONETEP to graphical processing unit-based coprocessors. 1. FFT box operations

We present the first graphical processing unit (GPU) coprocessor‐enabled version of the Order‐N Electronic Total Energy Package (ONETEP) code for linear‐scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve a...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Journal of computational chemistry Ročník 34; číslo 28; s. 2446 - 2459
Hlavní autori:	Wilkinson, Karl, Skylaris, Chris-Kriton
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Blackwell Publishing Ltd 30.10.2013 Wiley Subscription Services, Inc
Predmet:	Algorithms Fourier transforms graphical processing units heterogeneous computing Integrals linear scaling quantum chemistry Quantum theory Software quantum chemistry heterogeneous computing linear scaling graphical processing units
ISSN:	0192-8651, 1096-987X, 1096-987X
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Abstract	We present the first graphical processing unit (GPU) coprocessor‐enabled version of the Order‐N Electronic Total Energy Package (ONETEP) code for linear‐scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom‐localized fast Fourier transform (FFT) operations. These are among the most computationally intensive parts of the code and are used in core algorithms such as the calculation of the charge density, the local potential integrals, the kinetic energy integrals, and the nonorthogonal generalized Wannier function gradient. We have found that direct porting of the isolated FFT operations did not provide any benefit. Instead, it was necessary to tailor the port to each of the aforementioned algorithms to optimize data transfer to and from the GPU. A detailed discussion of the methods used and tests of the resulting performance are presented, which show that individual steps in the relevant algorithms are accelerated by a significant amount. However, the transfer of data between the GPU and host machine is a significant bottleneck in the reported version of the code. In addition, an initial investigation into a dynamic precision scheme for the ONETEP energy calculation has been performed to take advantage of the enhanced single precision capabilities of GPUs. The methods used here result in no disruption to the existing code base. Furthermore, as the developments reported here concern the core algorithms, they will benefit the full range of ONETEP functionality. Our use of a directive‐based programming model ensures portability to other forms of coprocessors and will allow this work to form the basis of future developments to the code designed to support emerging high‐performance computing platforms.Copyright © 2013 Wiley Periodicals, Inc. The Order–N Electronic Total Energy Package (ONETEP) linear‐scaling quantum chemistry code is ported on GPU coprocessorbased architectures in a manner that is highly portable, while maintaining the full functionality of the code.
AbstractList	We present the first graphical processing unit (GPU) coprocessor-enabled version of the Order-N Electronic Total Energy Package (ONETEP) code for linear-scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom-localized fast Fourier transform (FFT) operations. These are among the most computationally intensive parts of the code and are used in core algorithms such as the calculation of the charge density, the local potential integrals, the kinetic energy integrals, and the nonorthogonal generalized Wannier function gradient. We have found that direct porting of the isolated FFT operations did not provide any benefit. Instead, it was necessary to tailor the port to each of the aforementioned algorithms to optimize data transfer to and from the GPU. A detailed discussion of the methods used and tests of the resulting performance are presented, which show that individual steps in the relevant algorithms are accelerated by a significant amount. However, the transfer of data between the GPU and host machine is a significant bottleneck in the reported version of the code. In addition, an initial investigation into a dynamic precision scheme for the ONETEP energy calculation has been performed to take advantage of the enhanced single precision capabilities of GPUs. The methods used here result in no disruption to the existing code base. Furthermore, as the developments reported here concern the core algorithms, they will benefit the full range of ONETEP functionality. Our use of a directive-based programming model ensures portability to other forms of coprocessors and will allow this work to form the basis of future developments to the code designed to support emerging high-performance computing platforms. [PUBLICATION ABSTRACT] We present the first graphical processing unit (GPU) coprocessor-enabled version of the Order-N Electronic Total Energy Package (ONETEP) code for linear-scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom-localized fast Fourier transform (FFT) operations. These are among the most computationally intensive parts of the code and are used in core algorithms such as the calculation of the charge density, the local potential integrals, the kinetic energy integrals, and the nonorthogonal generalized Wannier function gradient. We have found that direct porting of the isolated FFT operations did not provide any benefit. Instead, it was necessary to tailor the port to each of the aforementioned algorithms to optimize data transfer to and from the GPU. A detailed discussion of the methods used and tests of the resulting performance are presented, which show that individual steps in the relevant algorithms are accelerated by a significant amount. However, the transfer of data between the GPU and host machine is a significant bottleneck in the reported version of the code. In addition, an initial investigation into a dynamic precision scheme for the ONETEP energy calculation has been performed to take advantage of the enhanced single precision capabilities of GPUs. The methods used here result in no disruption to the existing code base. Furthermore, as the developments reported here concern the core algorithms, they will benefit the full range of ONETEP functionality. Our use of a directive-based programming model ensures portability to other forms of coprocessors and will allow this work to form the basis of future developments to the code designed to support emerging high-performance computing platforms. We present the first graphical processing unit (GPU) coprocessor-enabled version of the Order-N Electronic Total Energy Package (ONETEP) code for linear-scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom-localized fast Fourier transform (FFT) operations. These are among the most computationally intensive parts of the code and are used in core algorithms such as the calculation of the charge density, the local potential integrals, the kinetic energy integrals, and the nonorthogonal generalized Wannier function gradient. We have found that direct porting of the isolated FFT operations did not provide any benefit. Instead, it was necessary to tailor the port to each of the aforementioned algorithms to optimize data transfer to and from the GPU. A detailed discussion of the methods used and tests of the resulting performance are presented, which show that individual steps in the relevant algorithms are accelerated by a significant amount. However, the transfer of data between the GPU and host machine is a significant bottleneck in the reported version of the code. In addition, an initial investigation into a dynamic precision scheme for the ONETEP energy calculation has been performed to take advantage of the enhanced single precision capabilities of GPUs. The methods used here result in no disruption to the existing code base. Furthermore, as the developments reported here concern the core algorithms, they will benefit the full range of ONETEP functionality. Our use of a directive-based programming model ensures portability to other forms of coprocessors and will allow this work to form the basis of future developments to the code designed to support emerging high-performance computing platforms.We present the first graphical processing unit (GPU) coprocessor-enabled version of the Order-N Electronic Total Energy Package (ONETEP) code for linear-scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom-localized fast Fourier transform (FFT) operations. These are among the most computationally intensive parts of the code and are used in core algorithms such as the calculation of the charge density, the local potential integrals, the kinetic energy integrals, and the nonorthogonal generalized Wannier function gradient. We have found that direct porting of the isolated FFT operations did not provide any benefit. Instead, it was necessary to tailor the port to each of the aforementioned algorithms to optimize data transfer to and from the GPU. A detailed discussion of the methods used and tests of the resulting performance are presented, which show that individual steps in the relevant algorithms are accelerated by a significant amount. However, the transfer of data between the GPU and host machine is a significant bottleneck in the reported version of the code. In addition, an initial investigation into a dynamic precision scheme for the ONETEP energy calculation has been performed to take advantage of the enhanced single precision capabilities of GPUs. The methods used here result in no disruption to the existing code base. Furthermore, as the developments reported here concern the core algorithms, they will benefit the full range of ONETEP functionality. Our use of a directive-based programming model ensures portability to other forms of coprocessors and will allow this work to form the basis of future developments to the code designed to support emerging high-performance computing platforms. We present the first graphical processing unit (GPU) coprocessor‐enabled version of the Order‐N Electronic Total Energy Package (ONETEP) code for linear‐scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom‐localized fast Fourier transform (FFT) operations. These are among the most computationally intensive parts of the code and are used in core algorithms such as the calculation of the charge density, the local potential integrals, the kinetic energy integrals, and the nonorthogonal generalized Wannier function gradient. We have found that direct porting of the isolated FFT operations did not provide any benefit. Instead, it was necessary to tailor the port to each of the aforementioned algorithms to optimize data transfer to and from the GPU. A detailed discussion of the methods used and tests of the resulting performance are presented, which show that individual steps in the relevant algorithms are accelerated by a significant amount. However, the transfer of data between the GPU and host machine is a significant bottleneck in the reported version of the code. In addition, an initial investigation into a dynamic precision scheme for the ONETEP energy calculation has been performed to take advantage of the enhanced single precision capabilities of GPUs. The methods used here result in no disruption to the existing code base. Furthermore, as the developments reported here concern the core algorithms, they will benefit the full range of ONETEP functionality. Our use of a directive‐based programming model ensures portability to other forms of coprocessors and will allow this work to form the basis of future developments to the code designed to support emerging high‐performance computing platforms.Copyright © 2013 Wiley Periodicals, Inc. We present the first graphical processing unit (GPU) coprocessor‐enabled version of the Order‐N Electronic Total Energy Package (ONETEP) code for linear‐scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom‐localized fast Fourier transform (FFT) operations. These are among the most computationally intensive parts of the code and are used in core algorithms such as the calculation of the charge density, the local potential integrals, the kinetic energy integrals, and the nonorthogonal generalized Wannier function gradient. We have found that direct porting of the isolated FFT operations did not provide any benefit. Instead, it was necessary to tailor the port to each of the aforementioned algorithms to optimize data transfer to and from the GPU. A detailed discussion of the methods used and tests of the resulting performance are presented, which show that individual steps in the relevant algorithms are accelerated by a significant amount. However, the transfer of data between the GPU and host machine is a significant bottleneck in the reported version of the code. In addition, an initial investigation into a dynamic precision scheme for the ONETEP energy calculation has been performed to take advantage of the enhanced single precision capabilities of GPUs. The methods used here result in no disruption to the existing code base. Furthermore, as the developments reported here concern the core algorithms, they will benefit the full range of ONETEP functionality. Our use of a directive‐based programming model ensures portability to other forms of coprocessors and will allow this work to form the basis of future developments to the code designed to support emerging high‐performance computing platforms.Copyright © 2013 Wiley Periodicals, Inc. The Order–N Electronic Total Energy Package (ONETEP) linear‐scaling quantum chemistry code is ported on GPU coprocessorbased architectures in a manner that is highly portable, while maintaining the full functionality of the code.
Author	Skylaris, Chris-Kriton Wilkinson, Karl
Author_xml	– sequence: 1 givenname: Karl surname: Wilkinson fullname: Wilkinson, Karl organization: School of Chemistry, University of Southampton, Southampton, SO17 1BJ, Highfield, United Kingdom – sequence: 2 givenname: Chris-Kriton surname: Skylaris fullname: Skylaris, Chris-Kriton email: c.skylaris@soton.ac.uk organization: School of Chemistry, University of Southampton, Southampton, SO17 1BJ, Highfield, United Kingdom
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/24038140$$D View this record in MEDLINE/PubMed
BookMark	eNp90c9P2zAUB3BrAkFhHPgHkKVdtkPa59hxkuMUtWxTaYtUxG6W49jMXRp3dqLBf7_0FwckdrL0_Pk-Pb13gU4a12iErgkMCUA8Wik1jCkj8AENCOQ8yrP05wkaAMnjKOMJOUcXIawAgCacnaHzmAHNCIMBelg439rmCc9n4-V4gVuHn7zc_LJK1njjndIhbL-7xrZRKYOusHKHuvNhiMkQTyZLXLpn7Dbay9a6JnxEp0bWQV8d3kv0MBkvi2_RdH77vfg6jRTNCUTaGFAJz1WZ0phmiqUZJKoCwysKNOWJ0Tw1KmfAdJUrIyuQTJaGlVzGpDL0En3e9-0n-tPp0Iq1DUrXtWy064IgjGYJT_OY9fTTG7pynW_66XaK9IjSXt0cVFeudSU23q6lfxHHhfXgyx4o70Lw2rwSAmJ7DNEfQ-yO0dvRG6tsu1tQ66Wt_5f4a2v98n5r8aMojolon7Ch1c-vCel_C57SNBGPs1sRT8j9Au7uREH_AeGzp8w
CODEN	JCCHDD
CitedBy_id	crossref_primary_10_1016_j_cpc_2020_107314 crossref_primary_10_1039_C4FD90024C crossref_primary_10_1016_j_cpc_2014_09_019 crossref_primary_10_1063_5_0260892 crossref_primary_10_1063_5_0004445 crossref_primary_10_1140_epjp_s13360_023_04732_5
Cites_doi	10.1021/ct1007247 10.1063/1.1613633 10.1021/ct800526s 10.1021/ct301130u 10.1103/RevModPhys.71.1085 10.1021/ct100584w 10.1145/882262.882364 10.1109/MC.2003.1220582 10.1002/jcc.20829 10.1145/1735688.1735697 10.1021/jp0776762 10.1016/S0010-4655(01)00248-X 10.1088/0034-4885/75/3/036503 10.1002/pssb.200541328 10.1021/ct9005079 10.1002/jcc.21815 10.1002/wcms.1101 10.1002/minf.201100042 10.1109/99.660313 10.1016/j.jmgm.2010.06.010 10.1016/j.cpc.2008.12.023 10.1103/PhysRevB.47.10891 10.1016/S0010-4655(02)00461-7 10.1103/PhysRevB.66.035119 10.1021/ct700268q 10.1016/j.cpc.2012.09.022 10.1063/1.3665893 10.1063/1.3166140 10.1103/PhysRevLett.76.3168 10.1088/0953-8984/20/29/294207 10.1145/1365490.1365500 10.1021/ct900275y 10.1145/1058129.1058148 10.1021/ct9003004 10.1021/ct300526w 10.1016/j.jcp.2008.01.047 10.1021/ct100701w 10.1063/1.470117 10.1073/pnas.0505436102 10.1063/1.1839852 10.1088/0305-4470/19/11/013 10.1016/j.cpc.2012.02.017 10.1021/ct200909j 10.1021/ct9000685
ContentType	Journal Article
Copyright	Copyright © 2013 Wiley Periodicals, Inc. Copyright Wiley Subscription Services, Inc. Oct 30, 2013
Copyright_xml	– notice: Copyright © 2013 Wiley Periodicals, Inc. – notice: Copyright Wiley Subscription Services, Inc. Oct 30, 2013
DBID	BSCLL AAYXX CITATION NPM JQ2 7X8
DOI	10.1002/jcc.23410
DatabaseName	Istex CrossRef PubMed ProQuest Computer Science Collection MEDLINE - Academic
DatabaseTitle	CrossRef PubMed ProQuest Computer Science Collection MEDLINE - Academic
DatabaseTitleList	ProQuest Computer Science Collection PubMed MEDLINE - Academic CrossRef
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Chemistry
EISSN	1096-987X
EndPage	2459
ExternalDocumentID	3086583351 24038140 10_1002_jcc_23410 JCC23410 ark_67375_WNG_2F1QP0MM_C
Genre	article Journal Article Feature
GrantInformation_xml	– fundername: Engineering and Physical Sciences Research Council funderid: EP/I006613/1 – fundername: Royal Society for a University Research Fellowship
GroupedDBID	--- -~X .3N .GA .Y3 05W 0R~ 10A 1L6 1OB 1OC 1ZS 33P 36B 3SF 3WU 4.4 4ZD 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 53G 5GY 5VS 66C 6P2 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 930 A03 AAESR AAEVG AAHQN AAMMB AAMNL AANHP AANLZ AAONW AASGY AAXRX AAYCA AAZKR ABCQN ABCUV ABIJN ABJNI ABLJU ABPVW ACAHQ ACBWZ ACCZN ACFBH ACGFO ACGFS ACIWK ACNCT ACPOU ACRPL ACXBN ACXQS ACYXJ ADBBV ADEOM ADIZJ ADKYN ADMGS ADMLS ADNMO ADOZA ADXAS ADZMN AEFGJ AEGXH AEIGN AEIMD AENEX AEUYR AEYWJ AFBPY AFFPM AFGKR AFWVQ AFZJQ AGQPQ AGXDD AGYGG AHBTC AIAGR AIDQK AIDYY AITYG AIURR AJXKR ALAGY ALMA_UNASSIGNED_HOLDINGS ALVPJ AMBMR AMYDB ASPBG ATUGU AUFTA AVWKF AZBYB AZFZN AZVAB BAFTC BDRZF BFHJK BHBCM BMNLL BMXJE BNHUX BROTX BRXPI BSCLL BY8 CS3 D-E D-F DCZOG DPXWK DR1 DR2 DRFUL DRSTM DU5 EBS EJD F00 F01 F04 F5P G-S G.N GNP GODZA H.T H.X HBH HGLYW HHY HHZ HZ~ IX1 J0M JPC KQQ LATKE LAW LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LW6 LYRES MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A NF~ NNB O66 O9- OIG P2P P2W P2X P4D PQQKQ Q.N Q11 QB0 QRW R.K RNS ROL RX1 RYL SUPJJ TN5 UB1 UPT V2E V8K W8V W99 WBFHL WBKPD WH7 WIB WIH WIK WJL WOHZO WQJ WXSBR WYISQ XG1 XPP XV2 YQT ZZTAW ~IA ~KM ~WT AAHHS ACCFJ AEEZP AEQDE AEUQT AFPWT AIWBW AJBDE ALUQN ESX RWI RWK WRC AAYXX CITATION O8X NPM JQ2 7X8
ID	FETCH-LOGICAL-c3910-eff0c569cb73238c47805cd0f6d303765fe67fc9404ed9cfad0a4abf4b6a21df3
IEDL.DBID	DRFUL
ISICitedReferencesCount	17
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000324919200005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0192-8651 1096-987X
IngestDate	Fri Jul 11 10:51:57 EDT 2025 Fri Jul 25 19:23:47 EDT 2025 Mon Jul 21 05:56:36 EDT 2025 Sat Nov 29 02:55:47 EST 2025 Tue Nov 18 22:25:14 EST 2025 Wed Jan 22 16:26:22 EST 2025 Tue Nov 11 03:32:31 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	28
Keywords	quantum chemistry heterogeneous computing linear scaling graphical processing units
Language	English
License	http://onlinelibrary.wiley.com/termsAndConditions#vor Copyright © 2013 Wiley Periodicals, Inc.
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c3910-eff0c569cb73238c47805cd0f6d303765fe67fc9404ed9cfad0a4abf4b6a21df3
Notes	Engineering and Physical Sciences Research Council - No. EP/I006613/1 ark:/67375/WNG-2F1QP0MM-C istex:9A8C26009D2B4FB2ED4982BCA6ED853C9766F436 ArticleID:JCC23410 Royal Society for a University Research Fellowship SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
PMID	24038140
PQID	1438179233
PQPubID	48816
PageCount	14
ParticipantIDs	proquest_miscellaneous_1438567924 proquest_journals_1438179233 pubmed_primary_24038140 crossref_primary_10_1002_jcc_23410 crossref_citationtrail_10_1002_jcc_23410 wiley_primary_10_1002_jcc_23410_JCC23410 istex_primary_ark_67375_WNG_2F1QP0MM_C
PublicationCentury	2000
PublicationDate	2013-10-30 30 October 2013 2013-Oct-30 20131030
PublicationDateYYYYMMDD	2013-10-30
PublicationDate_xml	– month: 10 year: 2013 text: 2013-10-30 day: 30
PublicationDecade	2010
PublicationPlace	United States
PublicationPlace_xml	– name: United States – name: New York
PublicationTitle	Journal of computational chemistry
PublicationTitleAlternate	J. Comput. Chem
PublicationYear	2013
Publisher	Blackwell Publishing Ltd Wiley Subscription Services, Inc
Publisher_xml	– name: Blackwell Publishing Ltd – name: Wiley Subscription Services, Inc
References	A. W. Götz, M. J. Williamson, D. Xu, D. Poole, S. Le Grand, R. C. Walker, J. Chem. Theory Comput. 2012, 8, 1542. J. E. Stone, D. J. Hardy, I. S. Ufimtsev, K. Schulten, J. Mol. Graph. Model. 2010, 29, 116. J. A. Anderson, C. D. Lorenz, A. Travesset, J. Comput. Phys. 2008, 227, 5342. M. J. Harvey, G. De Fabritiis, J. Chem. Theory Comput. 2009, 5, 2371. C. -K. Skylaris, A. A. Mostofi, P. D. Haynes, C. J. Pickard, M. C. Payne, Comput. Phys. Commun. 2001,3, 315-322. N. D. M. Hine, P. D. Haynes, A. A. Mostofi, C. -K. Skylaris, M. C. Payne, Comput. Phys. Commun. 2009, 180, 1041. X. -P. Li, R. W. Nunes, D. Vanderbilt, Phys. Rev. B 1993, 47, 10891. J. E. Stone, J. C. Phillips, P. L. Freddolino, D. J. Hardy, L. G. Trabuco, K. Schulten, J. Comput. Chem. 2007, 28, 2618. C. -K. Skylaris, A. A. Mostofi, P. D. Haynes, O. Diéguez, M. C. Payne, Phys. Rev. B 2002, 66, 035119. I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2009, 5, 2619. L. Dagum, R. Menon, IEEE Comput. Sci. Eng. 1998, 5, 46-55. W. Ma, S. Krishnamoorthy, O. Villa, K. Kowalski, J. Chem. Theory Comput. 2011, 7, 1316. C. -K. Skylaris, P. D. Haynes, A. A. Mostofi, M. C. Payne, J. Chem. Phys. 2005, 122, 084119. A. A. Mostofi, C. -K. Skylaris, P. D. Haynes, M. C. Payne, Comput. Phys. Commun. 2002, 147, 788. J. Nickolls, I. Buck, M. Garland, K. Skadron, Queue 2008, 6, 40. U. J. Kapasi, S. Rixner, W. J. Dally, B. Khailany, J. H. Ahn, P. Mattson, J. D. Owens, Computer 2003, 36, 54. K. A. Wilkinson, P. Sherwood, M. F. Guest, K. J. Naidoo, J. Comp. Chem. 2011, 32, 2313. P. D. Haynes, C. -K. Skylaris, A. A. Mostofi, M. C. Payne, J. Phys. Condens. Matter 2008, 20, 294207 L. Vogt, R. Olivares-Amaya, S. Kermes, Y. Shao, C. Amador-Bedolla, A. Aspuru-Guzik, J. Phys. Chem. A 2008, 112, 2049. M. Hutchinson, M. Widom, Comput. Phys. Commun. 2012, 183, 1422. E. Prodan, W. Kohn, Proc. Natl. Acad. Sci. USA 2005, 102, 11635. S. Le Grand, A. W. Götz, R. C. Walker, Comput. Phys. Commun. 2013, 184, 374. A. Asadchev, M. S. Gordon, J. Chem. Theory Comput. 2012, 8, 4166. J. E. Stone, D. Gohara, G. Shi, IEEE Des. Test Comput. 2010, 12, 66. A. A. Mostofi, P. D. Haynes, C. -K. Skylaris, M. C. Payne, J. Chem. Phys. 2003, 119, 8842. L. Genovese, M. Ospici, T. Deutsch, J. -F. Mehaut, A. Neelov, S. Goedecker, J. Chem. Phys. 2009, 131, 034103. I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2008, 4, 222. A. E. DePrince, J. R. Hammond, J. Chem. Theory Comput. 2011, 7, 1287. N. Luehr, I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2011, 2011, 949. M. J. Harvey, G. Giupponi, G. De Fabritiis, J. Chem. Theory Comput. 2009, 5, 1632. S. Goedecker, Rev. Mod. Phys. 1999, 71, 1085. S. J. Fox, C. Pittock, T. Fox, C. S. Tautermann, N. Malcolm, C. -K. Skylaris, J. Chem. Phys. 2011, 135, 224107. C. -K. Skylaris, P. D. Haynes, A. A. Mostofi, M. C. Payne, Phys. Stat. Sol. (b) 2006, 243, 973. K. Bhaskaran-Nair, W. Ma, S. Krishnamoorthy, O. Villa, H. J. J. van Dam, E. Apr, K. Kowalski, J. Chem. Theory Comput. 2013, 9, 1949. W. Kohn, Phys. Rev. Lett. 1996, 76, 3168. U. Essmann, L. Perera, M. L. Berkowitz, T. Darden, H. Lee, L. G. Pedersen, J. Chem. Phys. 1995, 103, 8577. I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2009, 5, 1004. D. R. Bowler, T. Miyazaki, Rep. Prog. Phys. 2012, 75, 036503. M. Woo, J. Neider, T. Davis, D. Shreiner, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Version 1.2, 3rd ed.; Addison-Wesley Longman Publishing: Boston, MA, 1999. A. Asadchev, V. Allada, J. Felder, B. M. Bode, M. S. Gordon, T. L. Windus, J. Chem. Theory Comput. 2010, 6, 696. J. A. Baker, J. D. Hirst, Mol. Inform. 2011, 30, 498. D. Baye, P. H. Heenen, J. Phys. A Math. Gen. 1986, 19, 2041-2060. M. J. Harvey, G. De Fabritiis, Wiley Interdiscip. Rev. Comput. Mol. Sci. 2012, 2, 734. J. Bolz, I. Farmer, E. Grinspun, P. Schröoder, ACM Trans. Graph. 2003, 22, 917. K. Fatahalian, J. Sugerman, P. Hanrahan, In Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Conference on Graphics Hardware, HWWS '04; ACM: New York, 2004; pp. 133-137. 2010; 12 2012; 183 1993; 47 2011; 135 2003; 119 2009; 180 2010 2003; 36 2011; 30 2011; 32 2008; 227 1986; 19 2008; 6 2004 2013; 184 2008; 4 2009; 131 1996; 76 2011; 7 2012; 75 2013; 9 1999 2007; 28 2011; 2011 2012; 2 2005; 122 2010; 29 2005; 102 2002; 147 2002; 66 2001; 3 1995; 103 2009; 5 2008; 20 2008; 112 1999; 71 1998; 5 2010; 6 2006; 243 2003; 22 2012; 8 e_1_2_8_28_1 Stone J. E. (e_1_2_8_7_1) 2010; 12 e_1_2_8_24_1 e_1_2_8_47_1 e_1_2_8_26_1 e_1_2_8_3_1 e_1_2_8_5_1 e_1_2_8_9_1 e_1_2_8_20_1 e_1_2_8_43_1 e_1_2_8_22_1 e_1_2_8_45_1 Skylaris C. ‐K. (e_1_2_8_49_1) 2001; 3 e_1_2_8_41_1 e_1_2_8_17_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_36_1 e_1_2_8_15_1 e_1_2_8_38_1 Luehr N. (e_1_2_8_51_1) 2011; 2011 Wolfe M. (e_1_2_8_11_1) 2010 e_1_2_8_32_1 e_1_2_8_34_1 e_1_2_8_30_1 e_1_2_8_29_1 e_1_2_8_25_1 e_1_2_8_46_1 e_1_2_8_27_1 e_1_2_8_48_1 Fatahalian K. (e_1_2_8_10_1) 2004 e_1_2_8_2_1 e_1_2_8_4_1 e_1_2_8_6_1 e_1_2_8_21_1 e_1_2_8_42_1 e_1_2_8_23_1 e_1_2_8_44_1 Woo M. (e_1_2_8_8_1) 1999 e_1_2_8_40_1 e_1_2_8_18_1 e_1_2_8_39_1 e_1_2_8_14_1 e_1_2_8_35_1 e_1_2_8_16_1 e_1_2_8_37_1 Kapasi U. J. (e_1_2_8_1_1) 2003; 36 e_1_2_8_31_1 e_1_2_8_12_1 e_1_2_8_33_1 e_1_2_8_50_1
References_xml	– reference: S. J. Fox, C. Pittock, T. Fox, C. S. Tautermann, N. Malcolm, C. -K. Skylaris, J. Chem. Phys. 2011, 135, 224107. – reference: P. D. Haynes, C. -K. Skylaris, A. A. Mostofi, M. C. Payne, J. Phys. Condens. Matter 2008, 20, 294207 – reference: A. Asadchev, V. Allada, J. Felder, B. M. Bode, M. S. Gordon, T. L. Windus, J. Chem. Theory Comput. 2010, 6, 696. – reference: I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2009, 5, 2619. – reference: L. Vogt, R. Olivares-Amaya, S. Kermes, Y. Shao, C. Amador-Bedolla, A. Aspuru-Guzik, J. Phys. Chem. A 2008, 112, 2049. – reference: J. A. Anderson, C. D. Lorenz, A. Travesset, J. Comput. Phys. 2008, 227, 5342. – reference: I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2008, 4, 222. – reference: C. -K. Skylaris, P. D. Haynes, A. A. Mostofi, M. C. Payne, J. Chem. Phys. 2005, 122, 084119. – reference: L. Dagum, R. Menon, IEEE Comput. Sci. Eng. 1998, 5, 46-55. – reference: U. Essmann, L. Perera, M. L. Berkowitz, T. Darden, H. Lee, L. G. Pedersen, J. Chem. Phys. 1995, 103, 8577. – reference: N. D. M. Hine, P. D. Haynes, A. A. Mostofi, C. -K. Skylaris, M. C. Payne, Comput. Phys. Commun. 2009, 180, 1041. – reference: J. Nickolls, I. Buck, M. Garland, K. Skadron, Queue 2008, 6, 40. – reference: L. Genovese, M. Ospici, T. Deutsch, J. -F. Mehaut, A. Neelov, S. Goedecker, J. Chem. Phys. 2009, 131, 034103. – reference: J. Bolz, I. Farmer, E. Grinspun, P. Schröoder, ACM Trans. Graph. 2003, 22, 917. – reference: K. Bhaskaran-Nair, W. Ma, S. Krishnamoorthy, O. Villa, H. J. J. van Dam, E. Apr, K. Kowalski, J. Chem. Theory Comput. 2013, 9, 1949. – reference: J. A. Baker, J. D. Hirst, Mol. Inform. 2011, 30, 498. – reference: M. J. Harvey, G. Giupponi, G. De Fabritiis, J. Chem. Theory Comput. 2009, 5, 1632. – reference: J. E. Stone, D. J. Hardy, I. S. Ufimtsev, K. Schulten, J. Mol. Graph. Model. 2010, 29, 116. – reference: W. Kohn, Phys. Rev. Lett. 1996, 76, 3168. – reference: A. Asadchev, M. S. Gordon, J. Chem. Theory Comput. 2012, 8, 4166. – reference: E. Prodan, W. Kohn, Proc. Natl. Acad. Sci. USA 2005, 102, 11635. – reference: A. W. Götz, M. J. Williamson, D. Xu, D. Poole, S. Le Grand, R. C. Walker, J. Chem. Theory Comput. 2012, 8, 1542. – reference: M. Woo, J. Neider, T. Davis, D. Shreiner, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Version 1.2, 3rd ed.; Addison-Wesley Longman Publishing: Boston, MA, 1999. – reference: I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2009, 5, 1004. – reference: M. Hutchinson, M. Widom, Comput. Phys. Commun. 2012, 183, 1422. – reference: K. A. Wilkinson, P. Sherwood, M. F. Guest, K. J. Naidoo, J. Comp. Chem. 2011, 32, 2313. – reference: K. Fatahalian, J. Sugerman, P. Hanrahan, In Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Conference on Graphics Hardware, HWWS '04; ACM: New York, 2004; pp. 133-137. – reference: A. E. DePrince, J. R. Hammond, J. Chem. Theory Comput. 2011, 7, 1287. – reference: C. -K. Skylaris, A. A. Mostofi, P. D. Haynes, O. Diéguez, M. C. Payne, Phys. Rev. B 2002, 66, 035119. – reference: J. E. Stone, J. C. Phillips, P. L. Freddolino, D. J. Hardy, L. G. Trabuco, K. Schulten, J. Comput. Chem. 2007, 28, 2618. – reference: S. Goedecker, Rev. Mod. Phys. 1999, 71, 1085. – reference: A. A. Mostofi, P. D. Haynes, C. -K. Skylaris, M. C. Payne, J. Chem. Phys. 2003, 119, 8842. – reference: U. J. Kapasi, S. Rixner, W. J. Dally, B. Khailany, J. H. Ahn, P. Mattson, J. D. Owens, Computer 2003, 36, 54. – reference: J. E. Stone, D. Gohara, G. Shi, IEEE Des. Test Comput. 2010, 12, 66. – reference: M. J. Harvey, G. De Fabritiis, J. Chem. Theory Comput. 2009, 5, 2371. – reference: W. Ma, S. Krishnamoorthy, O. Villa, K. Kowalski, J. Chem. Theory Comput. 2011, 7, 1316. – reference: S. Le Grand, A. W. Götz, R. C. Walker, Comput. Phys. Commun. 2013, 184, 374. – reference: C. -K. Skylaris, A. A. Mostofi, P. D. Haynes, C. J. Pickard, M. C. Payne, Comput. Phys. Commun. 2001,3, 315-322. – reference: A. A. Mostofi, C. -K. Skylaris, P. D. Haynes, M. C. Payne, Comput. Phys. Commun. 2002, 147, 788. – reference: C. -K. Skylaris, P. D. Haynes, A. A. Mostofi, M. C. Payne, Phys. Stat. Sol. (b) 2006, 243, 973. – reference: D. Baye, P. H. Heenen, J. Phys. A Math. Gen. 1986, 19, 2041-2060. – reference: N. Luehr, I. S. Ufimtsev, T. J. Martinez, J. Chem. Theory Comput. 2011, 2011, 949. – reference: X. -P. Li, R. W. Nunes, D. Vanderbilt, Phys. Rev. B 1993, 47, 10891. – reference: D. R. Bowler, T. Miyazaki, Rep. Prog. Phys. 2012, 75, 036503. – reference: M. J. Harvey, G. De Fabritiis, Wiley Interdiscip. Rev. Comput. Mol. Sci. 2012, 2, 734. – volume: 184 start-page: 374 year: 2013 publication-title: Comput. Phys. Commun. – volume: 8 start-page: 4166 year: 2012 publication-title: J. Chem. Theory Comput. – volume: 19 start-page: 2041 year: 1986 end-page: 2060 publication-title: J. Phys. A Math. Gen. – volume: 36 start-page: 54 year: 2003 publication-title: Computer – volume: 7 start-page: 1287 year: 2011 publication-title: J. Chem. Theory Comput. – volume: 20 start-page: 294207 year: 2008 publication-title: J. Phys. Condens. Matter – volume: 3 start-page: 315 year: 2001 end-page: 322 publication-title: Comput. Phys. Commun. – volume: 8 start-page: 1542 year: 2012 publication-title: J. Chem. Theory Comput. – volume: 147 start-page: 788 year: 2002 publication-title: Comput. Phys. Commun. – volume: 6 start-page: 40 year: 2008 publication-title: Queue – volume: 5 start-page: 2619 year: 2009 publication-title: J. Chem. Theory Comput. – volume: 122 start-page: 084119 year: 2005 publication-title: J. Chem. Phys. – volume: 5 start-page: 1004 year: 2009 publication-title: J. Chem. Theory Comput. – volume: 75 start-page: 036503 year: 2012 publication-title: Rep. Prog. Phys. – volume: 103 start-page: 8577 year: 1995 publication-title: J. Chem. Phys. – volume: 112 start-page: 2049 year: 2008 publication-title: J. Phys. Chem. A – volume: 22 start-page: 917 year: 2003 publication-title: ACM Trans. Graph. – volume: 2011 start-page: 949 year: 2011 publication-title: J. Chem. Theory Comput. – volume: 71 start-page: 1085 year: 1999 publication-title: Rev. Mod. Phys. – volume: 9 start-page: 1949 year: 2013 publication-title: J. Chem. Theory Comput. – volume: 28 start-page: 2618 year: 2007 publication-title: J. Comput. Chem. – volume: 119 start-page: 8842 year: 2003 publication-title: J. Chem. Phys. – volume: 7 start-page: 1316 year: 2011 publication-title: J. Chem. Theory Comput. – volume: 131 start-page: 034103 year: 2009 publication-title: J. Chem. Phys. – volume: 12 start-page: 66 year: 2010 publication-title: IEEE Des. Test Comput. – volume: 5 start-page: 46 year: 1998 end-page: 55 publication-title: IEEE Comput. Sci. Eng. – volume: 183 start-page: 1422 year: 2012 publication-title: Comput. Phys. Commun. – volume: 32 start-page: 2313 year: 2011 publication-title: J. Comp. Chem. – start-page: 133 year: 2004 end-page: 137 – volume: 227 start-page: 5342 year: 2008 publication-title: J. Comput. Phys. – volume: 6 start-page: 696 year: 2010 publication-title: J. Chem. Theory Comput. – volume: 180 start-page: 1041 year: 2009 publication-title: Comput. Phys. Commun. – start-page: 43 year: 2010 end-page: 50 – volume: 243 start-page: 973 year: 2006 publication-title: Phys. Stat. Sol. (b) – volume: 4 start-page: 222 year: 2008 publication-title: J. Chem. Theory Comput. – volume: 76 start-page: 3168 year: 1996 publication-title: Phys. Rev. Lett. – volume: 102 start-page: 11635 year: 2005 publication-title: Proc. Natl. Acad. Sci. USA – volume: 47 start-page: 10891 year: 1993 publication-title: Phys. Rev. B – volume: 2 start-page: 734 year: 2012 publication-title: Wiley Interdiscip. Rev. Comput. Mol. Sci. – volume: 5 start-page: 2371 year: 2009 publication-title: J. Chem. Theory Comput. – volume: 66 start-page: 035119 year: 2002 publication-title: Phys. Rev. B – volume: 135 start-page: 224107 year: 2011 publication-title: J. Chem. Phys. – volume: 5 start-page: 1632 year: 2009 publication-title: J. Chem. Theory Comput. – volume: 30 start-page: 498 year: 2011 publication-title: Mol. Inform. – volume: 29 start-page: 116 year: 2010 publication-title: J. Mol. Graph. Model. – year: 1999 – ident: e_1_2_8_32_1 doi: 10.1021/ct1007247 – ident: e_1_2_8_43_1 doi: 10.1063/1.1613633 – ident: e_1_2_8_28_1 doi: 10.1021/ct800526s – ident: e_1_2_8_33_1 doi: 10.1021/ct301130u – volume: 12 start-page: 66 year: 2010 ident: e_1_2_8_7_1 publication-title: IEEE Des. Test Comput. – ident: e_1_2_8_14_1 – ident: e_1_2_8_38_1 doi: 10.1103/RevModPhys.71.1085 – ident: e_1_2_8_31_1 doi: 10.1021/ct100584w – ident: e_1_2_8_9_1 doi: 10.1145/882262.882364 – volume: 36 start-page: 54 year: 2003 ident: e_1_2_8_1_1 publication-title: Computer doi: 10.1109/MC.2003.1220582 – ident: e_1_2_8_19_1 doi: 10.1002/jcc.20829 – start-page: 43 volume-title: Proceedings of the 3rd Workshop on General‐Purpose Computation on Graphics Processing Units, GPGPU '10 year: 2010 ident: e_1_2_8_11_1 doi: 10.1145/1735688.1735697 – ident: e_1_2_8_30_1 doi: 10.1021/jp0776762 – volume: 3 start-page: 315 year: 2001 ident: e_1_2_8_49_1 publication-title: Comput. Phys. Commun. doi: 10.1016/S0010-4655(01)00248-X – ident: e_1_2_8_39_1 doi: 10.1088/0034-4885/75/3/036503 – ident: e_1_2_8_44_1 doi: 10.1002/pssb.200541328 – ident: e_1_2_8_26_1 doi: 10.1021/ct9005079 – ident: e_1_2_8_4_1 doi: 10.1002/jcc.21815 – ident: e_1_2_8_15_1 – ident: e_1_2_8_12_1 – ident: e_1_2_8_17_1 doi: 10.1002/wcms.1101 – ident: e_1_2_8_18_1 doi: 10.1002/minf.201100042 – ident: e_1_2_8_13_1 doi: 10.1109/99.660313 – ident: e_1_2_8_16_1 doi: 10.1016/j.jmgm.2010.06.010 – ident: e_1_2_8_45_1 doi: 10.1016/j.cpc.2008.12.023 – ident: e_1_2_8_47_1 doi: 10.1103/PhysRevB.47.10891 – ident: e_1_2_8_6_1 – ident: e_1_2_8_50_1 doi: 10.1016/S0010-4655(02)00461-7 – ident: e_1_2_8_42_1 doi: 10.1103/PhysRevB.66.035119 – ident: e_1_2_8_3_1 doi: 10.1021/ct700268q – ident: e_1_2_8_22_1 doi: 10.1016/j.cpc.2012.09.022 – volume-title: OpenGL Programming Guide: The Official Guide to Learning OpenGL, Version 1.2 year: 1999 ident: e_1_2_8_8_1 – ident: e_1_2_8_37_1 doi: 10.1063/1.3665893 – ident: e_1_2_8_35_1 doi: 10.1063/1.3166140 – ident: e_1_2_8_40_1 doi: 10.1103/PhysRevLett.76.3168 – ident: e_1_2_8_48_1 doi: 10.1088/0953-8984/20/29/294207 – ident: e_1_2_8_5_1 doi: 10.1145/1365490.1365500 – ident: e_1_2_8_25_1 doi: 10.1021/ct900275y – start-page: 133 volume-title: Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Conference on Graphics Hardware, HWWS '04 year: 2004 ident: e_1_2_8_10_1 doi: 10.1145/1058129.1058148 – ident: e_1_2_8_29_1 doi: 10.1021/ct9003004 – ident: e_1_2_8_2_1 – ident: e_1_2_8_27_1 doi: 10.1021/ct300526w – ident: e_1_2_8_23_1 doi: 10.1016/j.jcp.2008.01.047 – volume: 2011 start-page: 949 year: 2011 ident: e_1_2_8_51_1 publication-title: J. Chem. Theory Comput. doi: 10.1021/ct100701w – ident: e_1_2_8_20_1 doi: 10.1063/1.470117 – ident: e_1_2_8_41_1 doi: 10.1073/pnas.0505436102 – ident: e_1_2_8_36_1 doi: 10.1063/1.1839852 – ident: e_1_2_8_46_1 doi: 10.1088/0305-4470/19/11/013 – ident: e_1_2_8_34_1 doi: 10.1016/j.cpc.2012.02.017 – ident: e_1_2_8_21_1 doi: 10.1021/ct200909j – ident: e_1_2_8_24_1 doi: 10.1021/ct9000685
SSID	ssj0003564
Score	2.1942449
Snippet	We present the first graphical processing unit (GPU) coprocessor‐enabled version of the Order‐N Electronic Total Energy Package (ONETEP) code for... We present the first graphical processing unit (GPU) coprocessor-enabled version of the Order-N Electronic Total Energy Package (ONETEP) code for...
SourceID	proquest pubmed crossref wiley istex
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	2446
SubjectTerms	Algorithms Fourier transforms graphical processing units heterogeneous computing Integrals linear scaling quantum chemistry Quantum theory Software
Title	Porting ONETEP to graphical processing unit-based coprocessors. 1. FFT box operations
URI	https://api.istex.fr/ark:/67375/WNG-2F1QP0MM-C/fulltext.pdf https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fjcc.23410 https://www.ncbi.nlm.nih.gov/pubmed/24038140 https://www.proquest.com/docview/1438179233 https://www.proquest.com/docview/1438567924
Volume	34
WOSCitedRecordID	wos000324919200005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVWIB databaseName: Wiley Online Library customDbUrl: eissn: 1096-987X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0003564 issn: 0192-8651 databaseCode: DRFUL dateStart: 19960101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1bb9MwFD4aLRK8MG6DsjEZhBAv6RLHsRPxhEIDQlspqGN9sxxfJC5qqqZFe-Qn8Bv3S2bHSdCkISHxFskninMu_r5c_B2AFwIrbIl3FCSKxAFJjSupOAuUkbHUuJRps8P7yzGbTtPFIpvtwOtuL4zXh-hfuLnKaNZrV-CirI_-iIZ-k3KM7Rpsn9eH2OYtGcDw7efi9LhfiOPEq0dZEhOkNIk6YaEQH_UnX4GjofPs-XVc8yp1bbCn2P2vWd-FOy3lRG98jtyDHb28D7fyrtPbAzhzv5NaCEMfp5P5ZIY2FWp0rF380MrvJHDDW1v-F79-O-BTSFbtSLWuxygao6KYo7I6R9VK-6yqH8JpMZnn74O24UIgY0sbAm1MKBOayZLFFsolcQ0PpAoNVRbpGE2MpszIjIREq0waoUJBRGlISQWOlIn3YLCslvoxIGqiksZSCaZLohjNtEjSWJo0MoZZljOCV53fuWzVyF1TjB_c6yhjbj3FG0-N4HlvuvISHNcZvWyC11uI9Xf3zxpL-Nn0HcdF9GkWnpzwfAQHXXR5W641dz3gI6ekaOf1rB-2UXBfT8RSV1tvk1BrREbwyGdFfzEnauikw-xdNcH_-zz5hzxvDp78u-k-3MauCYdDzPAABpv1Vj-Fm_Ln5mu9PoQbbJEetrl_CTplBIg
linkProvider	Wiley-Blackwell
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Ji9RAFH4M3cJ4cV9aRy1FxEt6kkqlkoAXiR1H7Y6t9DhzKyq1gAudpheZoz_B3-gvsV42GRhB8BaoF1J565dK1fcAnkqqqQPegRdpFnossRhSYeppq0JlaKmS-oT3p2lcFMnpaTrfgxfdWZiGH6JfcMPIqPM1BjguSB_-YQ39otSYuiTsPtiHzLlRNIDhq4_58bTPxGHU0Ec5FOMlPAo6ZiGfHvY3n6tHQ1Tt2UVg8zx2rYtPfvX_pn0NrrSgk7xsvOQ67JnlDdjPul5vN-EEN5S6IkbeF5PFZE62FamZrNGCZNWcJcDhnUsAv378xNKniarakWq9GZNgTPJ8QcrqjFQr0_jV5hYc55NFduS1LRc8FTrg4BlrfRXxVJVx6Iq5YtjyQGnfcu1qXcwja3hsVcp8ZnSqrNS-ZLK0rOSSBtqGt2GwrJbmLhBug5KHSsvYlEzHPDUySkJlk8Da2OGcETzvFC9Uy0eObTG-iYZJmQqnKVFragRPetFVQ8JxkdCz2nq9hFx_xV1rcSROiteC5sGHuT-biWwEB515RRuwG4Fd4APkUnTzetwPOyvg_xO5NNWukYm4E2IjuNO4Rf8wpDVE8jD3VrX1_z5P8TbL6ot7_y76CPaPFrOpmL4p3t2HyxRbcmD99A9gsF3vzAO4pL5vP2_WD9sQ-A2tvweQ
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3JbtRAEC1FGQRc2JcJARqEEBdP7N5sS1yQM2abmAFNSG4tuxeJRePRLFGO-YR8I19Ct9s2ihQkJG6Wuiy3q7rqPS_9CuBFiRW2xDsKmKIkoIlxKUXSQBlJpMaVTJod3l8ncVEkx8fpdAted3thvD5E_8LNZUZTr12C64Uye39UQ79LOcK2CNsH9gFlKbdpOdj_kh9O-kpMmJePsiwmSDiLOmWhEO_1J1_Ao4Fz7ellZPMid23AJ7_5f9O-BTda0one-FVyG7b0_A5cy7peb3fhyP1QakEMfSrGs_EUrWvUKFm7CKKF30vghje2APw6O3fQp5Cs25F6uRqhaITyfIaq-hTVC-3X1eoeHObjWfYuaFsuBJJY4hBoY0LJeCqrmFgwl9S1PJAqNFxZrIs5M5rHRqY0pFql0pQqLGlZGVrxEkfKkPuwPa_n-iEgbqKKE6nKWFdUxTzVJUuINElkTGx5zhBedY4XstUjd20xfgqvpIyF9ZRoPDWE573pwotwXGb0soleb1Euf7i_1mImjoq3AufR52l4cCCyIex24RVtwq6E6wIfOS1FO69n_bCNgvt-Us51vfE2jFsjOoQHfln0F3Oyhk48zN5VE_2_z1N8yLLmYOffTZ_C1el-Libvi4-P4Dp2HTkcfIa7sL1ebvRjuCJP1t9WyydtBvwGLd4HCw
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Porting+ONETEP+to+graphical+processing+unit-based+coprocessors.+1.+FFT+box+operations&rft.jtitle=Journal+of+computational+chemistry&rft.au=Wilkinson%2C+Karl&rft.au=Skylaris%2C+Chris-Kriton&rft.date=2013-10-30&rft.pub=Blackwell+Publishing+Ltd&rft.issn=0192-8651&rft.eissn=1096-987X&rft.volume=34&rft.issue=28&rft.spage=2446&rft.epage=2459&rft_id=info:doi/10.1002%2Fjcc.23410&rft.externalDBID=n%2Fa&rft.externalDocID=ark_67375_WNG_2F1QP0MM_C
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0192-8651&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0192-8651&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0192-8651&client=summon