A hardware Gaussian noise generator using the Box-Muller method and its error analysis

We present a hardware Gaussian noise generator based on the Box-Muller method that provides highly accurate noise samples. The noise generator can be used as a key component in a hardware-based simulation system, such as for exploring channel code behavior at very low bit error rates, as low as 10 -...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on computers Vol. 55; no. 6; pp. 659 - 671
Main Authors Lee, D.-U., Villasenor, J.D., Luk, W., Leong, P.H.W.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2006
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text
ISSN0018-9340
1557-9956
DOI10.1109/TC.2006.81

Cover

Abstract We present a hardware Gaussian noise generator based on the Box-Muller method that provides highly accurate noise samples. The noise generator can be used as a key component in a hardware-based simulation system, such as for exploring channel code behavior at very low bit error rates, as low as 10 -12 to 10 -13 . The main novelties of this work are accurate analytical error analysis and bit-width optimization for the elementary functions involved in the Box-Muller method. Two 16-bit noise samples are generated every clock cycle and, due to the accurate error analysis, every sample is analytically guaranteed to be accurate to one unit in the last place. An implementation on a Xilinx Virtex-4 XC4VLX100-12 FPGA occupies 1,452 slices, three block RAMs, and 12 DSP slices, and is capable of generating 750 million samples per second at a clock speed of 375 MHz. The performance can be improved by exploiting concurrent execution: 37 parallel instances of the noise generator at 95 MHz on a Xilinx Virtex-II Pro XC2VP100-7 FPGA generate seven billion samples per second and can run over 200 times faster than the output produced by software running on an Intel Pentium-4 3 GHz PC. The noise generator is currently being used at the Jet Propulsion Laboratory, NASA to evaluate the performance of low-density parity-check codes for deep-space communications
AbstractList The performance can be improved by exploiting concurrent execution: 37 parallel instances of the noise generator at 95 MHz on a Xilinx Virtex-II Pro XC2VP100-7 FPGA generate seven billion samples per second and can run over 200 times faster than the output produced by software running on an Intel Pentium-4 3 GHz PC.
We present a hardware Gaussian noise generator based on the Box-Muller method that provides highly accurate noise samples. The noise generator can be used as a key component in a hardware-based simulation system, such as for exploring channel code behavior at very low bit error rates, as low as 10 super(-12) to 10 super(-13). The main novelties of this work are accurate analytical error analysis and bit-width optimization for the elementary functions involved in the Box-Muller method. Two 16-bit noise samples are generated every clock cycle and, due to the accurate error analysis, every sample is analytically guaranteed to be accurate to one unit in the last place. An implementation on a Xilinx Virtex-4 XC4VLX100-12 FPGA occupies 1,452 slices, three block RAMs, and 12 DSP slices, and is capable of generating 750 million samples per second at a clock speed of 375 MHz. The performance can be improved by exploiting concurrent execution: 37 parallel instances of the noise generator at 95 MHz on a Xilinx Virtex-II Pro XC2VP100-7 FPGA generate seven billion samples per second and can run over 200 times faster than the output produced by software running on an Intel Pentium-4 3 GHz PC. The noise generator is currently being used at the Jet Propulsion Laboratory, NASA to evaluate the performance of low-density parity-check codes for deep-space communications
We present a hardware Gaussian noise generator based on the Box-Muller method that provides highly accurate noise samples. The noise generator can be used as a key component in a hardware-based simulation system, such as for exploring channel code behavior at very low bit error rates, as low as 10 -12 to 10 -13 . The main novelties of this work are accurate analytical error analysis and bit-width optimization for the elementary functions involved in the Box-Muller method. Two 16-bit noise samples are generated every clock cycle and, due to the accurate error analysis, every sample is analytically guaranteed to be accurate to one unit in the last place. An implementation on a Xilinx Virtex-4 XC4VLX100-12 FPGA occupies 1,452 slices, three block RAMs, and 12 DSP slices, and is capable of generating 750 million samples per second at a clock speed of 375 MHz. The performance can be improved by exploiting concurrent execution: 37 parallel instances of the noise generator at 95 MHz on a Xilinx Virtex-II Pro XC2VP100-7 FPGA generate seven billion samples per second and can run over 200 times faster than the output produced by software running on an Intel Pentium-4 3 GHz PC. The noise generator is currently being used at the Jet Propulsion Laboratory, NASA to evaluate the performance of low-density parity-check codes for deep-space communications
We present a hardware Gaussian noise generator based on the Box-Muller method that provides highly accurate noise samples. The noise generator can be used as a key component in a hardware-based simulation system, such as for exploring channel code behavior at very low bit error rates, as low as 10{-12} to 10{-13}. The main novelties of this work are accurate analytical error analysis and bit-width optimization for the elementary functions involved in the Box-Muller method. Two 16-bit noise samples are generated every clock cycle and, due to the accurate error analysis, every sample is analytically guaranteed to be accurate to one unit in the last place. An implementation on a Xilinx Virtex-4 XC4VLX100-12 FPGA occupies 1,452 slices, three block RAMs, and 12 DSP slices, and is capable of generating 750 million samples per second at a clock speed of 375 MHz. The performance can be improved by exploiting concurrent execution: 37 parallel instances of the noise generator at 95 MHz on a Xilinx Virtex-II Pro XC2VP100-7 FPGA generate seven billion samples per second and can run over 200 times faster than the output produced by software running on an Intel Pentium--4 3 GHz PC. The noise generator is currently being used at the Jet Propulsion Laboratory, NASA to evaluate the performance of low-density parity-check codes for deep-space communications.
Author Lee, D.-U.
Leong, P.H.W.
Villasenor, J.D.
Luk, W.
Author_xml – sequence: 1
  givenname: D.-U.
  surname: Lee
  fullname: Lee, D.-U.
  organization: Dept. of Electr. Eng., California Univ., Los Angeles, CA
– sequence: 2
  givenname: J.D.
  surname: Villasenor
  fullname: Villasenor, J.D.
  organization: Dept. of Electr. Eng., California Univ., Los Angeles, CA
– sequence: 3
  givenname: W.
  surname: Luk
  fullname: Luk, W.
– sequence: 4
  givenname: P.H.W.
  surname: Leong
  fullname: Leong, P.H.W.
BookMark eNp90cFrFDEUBvAgLbhtvXj1EjwoCLO-JJOZ5NguWgsVL6vX4U3mTTdlNqlJBu1_31lWEIp4epff--C974ydhBiIsdcC1kKA_bjdrCVAszbiBVsJrdvKWt2csBWAMJVVNbxkZznfw4Ik2BX7ccl3mIZfmIhf45yzx8BD9Jn4HQVKWGLic_bhjpcd8av4u_o6TxMlvqeyiwPHMHBfMqeUFokBp8fs8wU7HXHK9OrPPGffP3_abr5Ut9-ubzaXt5WroS0VEta9IFVrR6521BjXIEkYeznWgE1tsEUaHJBF0xstnFK96knSOEo9OHXO3h9zH1L8OVMu3d5nR9OEgeKcO2OsMq1t5CLf_VdKA6BVaxf49hm8j3Na7lrSGi1atbxyQR-OyKWYc6Kxe0h-j-mxE9Admui2m-7QRGcOGJ5h5wsWH0NJ6Kd_r7w5rngi-pvdSGO1Vk-Py5aM
CODEN ITCOB4
CitedBy_id crossref_primary_10_3390_app13169402
crossref_primary_10_1145_1857927_1857929
crossref_primary_10_1364_OE_491554
crossref_primary_10_1016_j_compeleceng_2022_108305
crossref_primary_10_7305_automatika_2014_01_582
crossref_primary_10_1049_iet_cdt_20060188
crossref_primary_10_1142_S021812660700368X
crossref_primary_10_1109_TCSII_2012_2204119
crossref_primary_10_1109_TVLSI_2014_2322573
crossref_primary_10_1007_s41365_021_00851_9
crossref_primary_10_3756_artsci_12_48
crossref_primary_10_1007_s10836_017_5696_3
crossref_primary_10_1155_2012_675130
crossref_primary_10_1109_MAES_2020_2997415
crossref_primary_10_1140_epje_s10189_023_00281_y
crossref_primary_10_3390_su13126628
crossref_primary_10_1109_ACCESS_2023_3289432
crossref_primary_10_1109_TC_2015_2401015
crossref_primary_10_1088_1674_1137_ac7d44
crossref_primary_10_1109_TCSI_2017_2656250
crossref_primary_10_1109_JETCAS_2024_3389660
crossref_primary_10_1145_1371579_1371584
crossref_primary_10_9746_sicetr_48_907
crossref_primary_10_3390_en16093717
crossref_primary_10_1109_TCSI_2016_2553318
crossref_primary_10_3724_SP_J_1016_2011_00165
crossref_primary_10_1016_j_ifacol_2018_11_701
crossref_primary_10_1103_PhysRevA_100_012316
crossref_primary_10_1364_OE_25_029189
crossref_primary_10_1109_TVLSI_2008_917552
crossref_primary_10_1145_2629607
crossref_primary_10_1109_TVLSI_2007_900748
crossref_primary_10_1109_TVLSI_2013_2276010
crossref_primary_10_1049_iet_cta_2010_0736
crossref_primary_10_3390_fractalfract7080600
crossref_primary_10_1145_2980052
crossref_primary_10_1109_TSP_2009_2029726
crossref_primary_10_1142_S0218126623501633
crossref_primary_10_1007_s10100_020_00687_5
crossref_primary_10_1109_TVLSI_2013_2262103
crossref_primary_10_1016_j_aeue_2024_155538
crossref_primary_10_1007_s11265_006_0014_9
crossref_primary_10_1088_1755_1315_29_1_012006
crossref_primary_10_5370_KIEE_2012_61_3_401
crossref_primary_10_1364_OE_27_019650
crossref_primary_10_1109_TC_2007_1013
crossref_primary_10_1109_JSSC_2023_3283186
crossref_primary_10_1016_j_ces_2023_118947
crossref_primary_10_3724_SP_J_1187_2010_00414
crossref_primary_10_3390_e25111530
Cites_doi 10.1109/ICC.1993.397441
10.18637/jss.v005.i08
10.1109/92.273153
10.1109/12.295858
10.1214/aoms/1177706645
10.1109/SIPS.2004.1363067
10.1109/FPGA.2003.1227241
10.1117/12.452034
10.1109/TVLSI.2005.853615
10.1109/TC.2004.106
10.1023/A:1021937002981
10.1111/1467-9965.00028
10.1109/FPL.2005.1515734
10.1145/1478786.1478840
10.1090/S0025-5718-96-00696-5
10.1002/mats.1997.040060213
10.1145/945511.945517
10.1109/12.736435
10.1090/S0025-5718-1965-0184406-1
10.1109/TIT.1962.1057683
10.1145/225545.225554
10.1007/978-1-4757-2646-6
10.1109/DAC.2005.193931
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2006
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2006
DBID 97E
RIA
RIE
AAYXX
CITATION
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
F28
FR3
DOI 10.1109/TC.2006.81
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005–Present
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
ANTE: Abstracts in New Technology & Engineering
Engineering Research Database
DatabaseTitle CrossRef
Technology Research Database
Computer and Information Systems Abstracts – Academic
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
Engineering Research Database
ANTE: Abstracts in New Technology & Engineering
DatabaseTitleList Technology Research Database
Technology Research Database

Computer and Information Systems Abstracts
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Computer Science
EISSN 1557-9956
EndPage 671
ExternalDocumentID 2340502071
10_1109_TC_2006_81
1628955
Genre orig-research
GroupedDBID --Z
-DZ
-~X
.55
.DC
0R~
29I
3EH
3O-
4.4
5GY
5VS
6IK
85S
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABFSI
ABQJQ
ABVLG
ACGFO
ACIWK
ACNCT
AENEX
AETEA
AETIX
AGQYO
AGSQL
AHBIQ
AI.
AIBXA
AKJIK
AKQYR
ALLEH
ALMA_UNASSIGNED_HOLDINGS
ASUFR
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
DU5
E.L
EBS
EJD
HZ~
H~9
IAAWW
IBMZZ
ICLAB
IEDLZ
IFIPE
IFJZH
IPLJI
JAVBF
LAI
M43
MS~
MVM
O9-
OCL
P2P
PQQKQ
RIA
RIE
RNI
RNS
RXW
RZB
TAE
TN5
TWZ
UHB
UKR
UPT
VH1
X7M
XJT
XOL
XZL
YXB
YYQ
YZZ
ZCG
AAYXX
CITATION
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
RIG
F28
FR3
ID FETCH-LOGICAL-c407t-aea4b1e345cec4ce68c6ae20fb2f40a648a7aedc0e9a8b851c33b3be2eff25dc3
IEDL.DBID RIE
ISSN 0018-9340
IngestDate Sun Sep 28 07:47:29 EDT 2025
Thu Oct 02 11:12:02 EDT 2025
Mon Jun 30 06:31:31 EDT 2025
Wed Oct 01 06:42:45 EDT 2025
Thu Apr 24 22:55:37 EDT 2025
Wed Aug 27 02:49:03 EDT 2025
IsPeerReviewed true
IsScholarly true
Issue 6
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c407t-aea4b1e345cec4ce68c6ae20fb2f40a648a7aedc0e9a8b851c33b3be2eff25dc3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
PQID 865173001
PQPubID 23500
PageCount 13
ParticipantIDs proquest_miscellaneous_889387962
proquest_miscellaneous_28005379
proquest_journals_865173001
crossref_primary_10_1109_TC_2006_81
ieee_primary_1628955
crossref_citationtrail_10_1109_TC_2006_81
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2006-06-01
PublicationDateYYYYMMDD 2006-06-01
PublicationDate_xml – month: 06
  year: 2006
  text: 2006-06-01
  day: 01
PublicationDecade 2000
PublicationPlace New York
PublicationPlace_xml – name: New York
PublicationTitle IEEE transactions on computers
PublicationTitleAbbrev TC
PublicationYear 2006
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref13
ref15
ref14
ref11
ref10
ref2
Knuth (ref6) 1997; 2
ref1
ref16
ref18
(ref17) 2005
(ref12) 2002
Wallace (ref29) 2003
ref24
ref23
ref25
ref20
ref22
ref21
ref28
ref27
ref8
ref7
ref9
ref4
ref3
ref5
Marsaglia (ref19) 1997
de Figueiredo (ref26) 1997
References_xml – volume-title: Diehard: A Battery of Tests of Randomness
  year: 1997
  ident: ref19
– volume: 2
  volume-title: Seminumerical Algorithms
  year: 1997
  ident: ref6
– year: 1997
  ident: ref26
  article-title: Self-Validated Numerical Methods and Applications
  publication-title: Brazilian Math. Colloquium Monograph, IMPA, Brazil
– ident: ref4
  doi: 10.1109/ICC.1993.397441
– ident: ref7
  doi: 10.18637/jss.v005.i08
– ident: ref27
  doi: 10.1109/92.273153
– ident: ref22
  doi: 10.1109/12.295858
– ident: ref10
  doi: 10.1214/aoms/1177706645
– volume-title: Additive White Gaussian Noise (AWGN) Core v1.0, Xilinx Inc.
  year: 2002
  ident: ref12
– ident: ref13
  doi: 10.1109/SIPS.2004.1363067
– ident: ref5
  doi: 10.1109/FPGA.2003.1227241
– ident: ref28
  doi: 10.1117/12.452034
– ident: ref14
  doi: 10.1109/TVLSI.2005.853615
– ident: ref15
  doi: 10.1109/TC.2004.106
– ident: ref11
  doi: 10.1023/A:1021937002981
– ident: ref3
  doi: 10.1111/1467-9965.00028
– ident: ref16
  doi: 10.1109/FPL.2005.1515734
– ident: ref24
  doi: 10.1145/1478786.1478840
– ident: ref20
  doi: 10.1090/S0025-5718-96-00696-5
– ident: ref2
  doi: 10.1002/mats.1997.040060213
– ident: ref8
  doi: 10.1145/945511.945517
– ident: ref21
  doi: 10.1109/12.736435
– ident: ref18
  doi: 10.1090/S0025-5718-1965-0184406-1
– ident: ref1
  doi: 10.1109/TIT.1962.1057683
– volume-title: Xilinx System Generator User Guide v7.1, Xilinx Inc.
  year: 2005
  ident: ref17
– ident: ref9
  doi: 10.1145/225545.225554
– year: 2003
  ident: ref29
  article-title: MDMC Software—Random Number Generators
– ident: ref23
  doi: 10.1007/978-1-4757-2646-6
– ident: ref25
  doi: 10.1109/DAC.2005.193931
SSID ssj0006209
Score 2.2220628
Snippet We present a hardware Gaussian noise generator based on the Box-Muller method that provides highly accurate noise samples. The noise generator can be used as a...
The performance can be improved by exploiting concurrent execution: 37 parallel instances of the noise generator at 95 MHz on a Xilinx Virtex-II Pro XC2VP100-7...
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 659
SubjectTerms Algorithms implemented in hardware
Approximation methods
Clocks
Codes
computer arithmetic
Computer simulation
elementary function approximation
Error analysis
Field programmable gate arrays
Gaussian processes
Mathematical analysis
Mathematical models
minimax approximation and algorithms
Noise
Noise generators
optimization
Optimization methods
Random number generation
simulation
Studies
Title A hardware Gaussian noise generator using the Box-Muller method and its error analysis
URI https://ieeexplore.ieee.org/document/1628955
https://www.proquest.com/docview/865173001
https://www.proquest.com/docview/28005379
https://www.proquest.com/docview/889387962
Volume 55
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVIEE
  databaseName: IEEE Electronic Library (IEL)
  customDbUrl:
  eissn: 1557-9956
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0006209
  issn: 0018-9340
  databaseCode: RIE
  dateStart: 19680101
  isFulltext: true
  titleUrlDefault: https://ieeexplore.ieee.org/
  providerName: IEEE
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9QwEB61PcGBQgtiaQFLcEEi28SvdY7tilIhLact6i2ynXFVFSUoD1H119eOkwVKkbhFylixYs94xjPzfQDvrUaGRpdJLpxJeInM20EuE6TSBMpVEyHzV1_l2Tn_ciEutuDjphcGEYfiM5yHxyGXX9a2D1dlR5n04YEQ27C9UDL2am2srpzKOTKvwIynIxRpluZH62VMOqjsj8NnYFP5ywQP58rpLqymGcVykut535m5vb0H1vi_U34KT0YHkxzHHfEMtrDag92JvIGMurwHj39DItyHb8cktF_91A2Sz7pvQ2slqeqrFsnlAEztQ3MSauQvifcYyUl9k6wCcHdDIgU10VVJrrqWYNN4ST1CnTyH89NP6-VZMlIuJNZHdl2iUXOTIePCouUWpbJSI02doY6nWnKlFxpLm2KulfHemmXMMIMUnaOitOwF7FR1hS-BCGapQyqYcd4wuFRZx3LMfTTuLepC5jP4MK1FYUc88kCL8b0Y4pI0L9bLQJIpC5XN4N1G9kdE4XhQaj8swC-J-O9ncDAtcTEqaFsoKbIA1e8Hvd289ZoV0iW6wrpvC6oGsBs_UfIPCeWdPbXIJX318JcP4FG8sQmXNoew0zU9vvY-TGfeDJv3DpeR8b8
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9QwEB6VcoAeWmhB3RaoJbggkW3i1zrHsqIs0O1pi3qLbGdSVVRJlYdA_HrsOFleReIWKWPFij3jGc_M9wG8shoZGp1HqShMxHNkzg5yGSGVxlOumgCZvzyXiwv-8VJcbsCbdS8MIvbFZzj1j30uP69s56_KjhPpwgMh7sF9wTkXoVtrbXflWNCROBVmPB7ASJM4PV7NQ9pBJb8dPz2fyl9GuD9ZTndgOc4pFJR8mXatmdrvf8A1_u-kH8H24GKSk7AnHsMGlruwM9I3kEGbd2HrFyzCPfh8QnwD1lddI3mvu8Y3V5Kyum6QXPXQ1C44J75K_oo4n5G8rb5FSw_dXZNAQk10mZPrtiFY105SD2AnT-Di9N1qvogG0oXIutiujTRqbhJkXFi03KJUVmqkcWFowWMtudIzjbmNMdXKOH_NMmaYQYpFQUVu2VPYLKsS94EIZmmBVDBTONNQxMoWLMXUxePOps5kOoHX41pkdkAk98QYN1kfmcRptpp7mkyZqWQCL9eytwGH406pPb8APyXCv5_A4bjE2aCiTaakSDxYvxt0tH7rdMsnTHSJVddkVPVwN26i5B8Syrl7apZKenD3l4_gwWK1PMvOPpx_OoSH4f7GX-E8g8227vC582ha86LfyD8AXx71DA
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=A+hardware+Gaussian+noise+generator+using+the+Box-Muller+method+and+its+error+analysis&rft.jtitle=IEEE+transactions+on+computers&rft.au=Lee%2C+D.-U.&rft.au=Villasenor%2C+J.D.&rft.au=Luk%2C+W.&rft.au=Leong%2C+P.H.W.&rft.date=2006-06-01&rft.issn=0018-9340&rft.volume=55&rft.issue=6&rft.spage=659&rft.epage=671&rft_id=info:doi/10.1109%2FTC.2006.81&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TC_2006_81
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0018-9340&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0018-9340&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0018-9340&client=summon