Physical Description • • • • • Combination of less sweptback wing (better low-speed properties, greater flap effectiveness) and delta wing (better stall characteristics) Leading edge can be straight or curved Must always have a sharp leading edge Small aspect ratio High sweep angle http://www.globalsecurity.org/military/systems/aircraft/f-16-pics.htm 3/26/2004 3
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 Data Hazards  Let’s concentrate on the DADD and the instructions that follow it All RAW Pipelined MIPS CPU Design : Version 1 1 2 200 204 208 20C 210 214 218 21C LD DADD DSUB XOR SLT OR SD BEQZ R1, 500(R0) R2, R3, R4 R5, R6, R2 R8, R9, R2 R11, R12, R2 14, R15, R2 R2, 600(R0) R2, 5 Why do we stall the DSUB in the ID stage ? CS 6133 IF 1 4 5 6 IF ID EX MEM WB IF ID EX MEM WB IF ID Stall Stall IF Stall Stall Stall Stall Stall WB ? We stall the DSUB for 3 clock periods and create MEM ? a 3-clock period bubble that EX ? moves up the pipeline ID 3 ? v ? ? ? v v ? ? v v v ? v v v v v v 7 Stall Stall Stall Stall Stall 8 9 10 EX MEM WB ID EX MEM IF ID EX Stall IF ID Stall Stall IF Stall Stall Stall v v v v v v v v v v v v v XOR is fetched and idling in the IF stage Haldun Hadimioglu MIPS Versions 0 & 1 222
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 Data Hazards  Let’s concentrate on the DADD and the instructions that follow it We stalled the DSUB in the ID stage since it reads its operands in ID as we designed in Version 1)  The DSUB reads its operands R2 and R6 in the ID stage  This is clock period 4 1 2 All RAW Pipelined MIPS CPU Design : Version 1  200 204 208 20C 210 214 218 21C LD DADD DSUB XOR SLT OR SD BEQZ     R1, 500(R0) R2, R3, R4 R5, R6, R2 R8, R9, R2 R11, R12, R2 14, R15, R2 R2, 600(R0) R2, 5 3 1 4 5 6 IF ID EX MEM WB IF ID EX MEM WB IF ID Stall Stall IF Stall Stall Stall Stall Stall 7 8 9 10 Stall EX MEM WB Stall ID EX MEM Stall IF ID EX Stall Stall IF ID Stall Stall Stall IF Stall Stall Stall When will the DADD write to R2 ? In clock period 6 ! When will R2 actually get the new value ? In the beginning of the 7th clock period ! CS 6133 Haldun Hadimioglu MIPS Versions 0 & 1 223
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CPE 631 AM Examples  L.D F4, 0(R2) Stalls arising from RAW hazards IF MUL.D F0, F4, F6 ADD.D F2, F0, F8 S.D 0(R2), F2  ID EX Mem WB IF ID stall M1 IF stall M2 M3 M4 M5 M6 M7 Mem WB ID stall stall stall stall stall stall A1 A2 IF ID EX stall stall stall Mem stall stall stall stall stall stall A3 A4 Mem WB Three instructions that want to perform a write back to the FP register file simultaneously MUL.D F0, F4, F6 ... ... ADD.D F2, F4, F6 ... ... L.D F2, 0(R2) 24/03/19 IF ID M1 M2 M3 M4 M5 IF ID EX Mem WB IF ID EX Mem WB IF ID A1 A2 IF ID IF EX Mem WB ID EX Mem WB IF ID EX Mem WB UAH-CPE631 M6 M7 Mem WB A3 A4 Mem WB 20
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CPE 631 AM Examples  L.D F4, 0(R2) Stalls arising from RAW hazards IF MUL.D F0, F4, F6 ADD.D F2, F0, F8 S.D 0(R2), F2  ID EX Mem WB IF ID stall M1 IF stall ID IF M2 M3 M4 M5 M6 M7 Mem WB stall stall stall stall stall stall A1 A2 A3 A4 stall stall stall stall stall stall ID EX stall stall Mem WB stall Mem Three instructions that want to perform a write back to the FP register file simultaneously MUL.D F0, F4, F6 ... ... ADD.D F2, F4, F6 ... ... L.D F2, 0(R2) 24/03/19 IF ID M1 M2 M3 M4 M5 IF ID EX Mem WB IF ID EX Mem WB IF ID A1 A2 IF ID IF EX ID IF UAH-CPE631 M6 M7 Mem WB A3 A4 Mem WB Mem WB EX Mem WB ID EX Mem WB 20
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Examples Stalls arising from RAW hazards  L.D F4, 0(R2) IF MUL.D F0, F4, F6 ADD.D F2, F0, F8 S.D 0(R2), F2  ID EX Mem WB IF ID stall M1 IF stall ID stall stall stall stall stall stall A1 A2 IF stall stall stall stall stall stall ID EX ... LaCASA M3 M4 M5 M6 M7 Mem WB A3 A4 Mem WB stall stall stall Mem Three instructions that want to perform a write back to the FP register file simultaneously MUL.D F0, F4, F6 ... AM M2 ADD.D F2, F4, F6 ... ... L.D F2, 0(R2) IF ID M1 M2 M3 M4 M5 IF ID EX IF ID EX Mem WB IF ID A1 A2 IF ID IF EX ID IF M6 M7 Mem WB A3 A4 Mem WB Mem WB Mem WB EX Mem WB ID EX Mem WB 54
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References • • • • • • • • • Background image: http://www.dfrc.nasa.gov/gallery/photo/F18HARV/Medium/EC89-0096-149.jpg Animated GIF: http://globalsecurity.org/military/systems/aircraft/f-18pics.htm Huenecke, Klaus. Modern Aircraft Design. Maryland: Naval Institute Press, 1987. Whitford, Ray. Fundamentals of Fighter Design. England: Airlife Publishing, 2000. Bertin, John. Aerodynamics for Engineers. New Jersey: Prentice Hall, 2002. Filippone, High Speed Aerodynamics. 24 Mar. 2004. Wing. 24 Mar. 2004. Seeley, Brian. Local Flow Control I. Aircraft Research Report. 24 Mar. 2004. F-16 Fighting Falcon. 24 Mar. 2004. 3/26/2004 12
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VOMmean on WINE150hl(FA,FS,TS,AL) 0 1 1 4 2 4 3 5 4 3 5 8 6 7 7 1 8 7 _________[0 9 2 . 10) 42 low 0 high CLUS_1.1.1.1.1.1 _________[0 . 19) 56 low 10 5 [10,16) 15 low 12 high CLUS 1.1.1.1.1.2 [19,22) 1 low 12 high 11 4 But no algorithm would pick 19 as a cut! ___12 _____[0 . 13) 56 low 5 1 low 12 high But no alg would pick a 13 cut! 13 7 [13,16) 14 3 _________[0 15 3 . 16) 57 low 12 high CLUS 1.1.1.1.1 35 high CLUS 1.1.1.1.2 17 2 [16,31) 0 low 18 5 19 4 20 3 21 1 22 4 23 4 24 5 25 1 26 2 27 1 29 2 30 1 31 1 _________[0 . 31) 57 low 47 high CLUS_1.1.1.1.1 32 1 28 high CLUS 1.1.1.1.2 34 1 [31,58) 0 low 36 1 37 3 38 1 39 2 40 1 43 6 44 4 46 2 47 1 48 1 50 1 52 1 _________[0 .58) 57 low 75 high CLUS_1.1.1.1 56 1 5 high CLUS 1.1.1.2 60 1 [58,70) 0 low 63 1 65 2 _________[0 .70) 57 low 80 high CLUS_1.1.1 67 1 [70,78) 0 low 2 high CLUS 1.1.2 72 1 _________[0 .78) 57 low 82 high CLUS_1.1 74 1 82 1 7 high CLUS1.2 83 1 [78,94) 0 low 85 1 86 1 87 2 _________[0.94) 57 low 89 high CLUS_1 88 1 99 1 0 low 4 high CLUS_2 105 1 113 1 119 1 d=VOMMEAN DPP on WINE_150_HL_(FA,FSO2,TSO2,ALCOHOL). Some agglomeration required: CLUS1.1.1.1.1.1 is LOW_Quality F[0,10], else HIGH Quality F[13,119] with 15 LOW error. Classification accuracy = 90% (if it had been cut 13, 99.3% accuracy!) 7 1 8 4 STDs=(1.9,9,23,1.2) 9 4 maxSTD=23 for 10 5 11 4 d=e TS on WN150hl(FA,FS,TS,AL 12 7 13 7 14 8 _________[0 CLUS 1.1.1.1.1.1 15 2 . 16) 42 low 12 high CLUS 1.1.1.1.1.2 16 5 [16,22) 15 low 17 4 18 5 . 19 7 20 3 _________[0 . 22) 57 low 12 high CLUS_1.1.1.1.1 21 3 32 high CLUS 1.1.1.1.2 23 2 [22,33) 0 low 24 9 25 3 26 1 27 4 28 4 29 5 30 1 31 2 _________[0 . 33) 57 low 44 high CLUS_1.1.1.1.1 32 1 31 high CLUS 1.1.1.1.2 34 2 [33,60) 0 low 35 1 36 1 37 1 39 1 41 1 42 3 43 1 44 2 45 1 47 6 48 4 49 2 50 1 51 1 53 1 55 1 _________[0 .60) 57 low 75 high CLUS_1.1.1.1 59 1 5 high CLUS 1.1.1.2 63 1 [60,72) 0 low 65 1 67 2 _________[0.72) 57 low 89 high CLUS1.1.1 69 1 74 1 [72,80] high CLUS1.1 CLUS1.1.2 _________[0.80) 57 low 892 high 75 1 84 1 7 high CLUS1.2 85 1 [80,95] 86 1 87 1 88 2 _________[0.95) 57 low 89 high CLUS1 89 1 100 1 4 high CLUS2 106 1 113 1 119 1 Identical cuts and accuracy! Tells us that d=eTotal_SO2 is responsible for all separation. WINE
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Reasoning Capabilities Buildfile: build.xml init: compile: Finding Transitive Closures (RDFS reasoning) dist: [jar] Building jar: /home/aks1/software/eclipse/workspace/ontojena/dist/lib/ontojena.jar Inferred Triples vehicle run: [java] MODEL OK [java] Resource: http://ontosem.org/#fire-engine Land-vehicle [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#fire-engine) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#all) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#physical-object) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#inanimate) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#wheeled-vehicle) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#engine-propelled-vehicle) Engine-propelled--vehicle Wheeled--vehicle [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#wheeled-engine-vehicle) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#artifact) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#object) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#land-vehicle) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#vehicle) [java] - (http://ontosem.org/#fire-engine rdfs:subClassOf http://ontosem.org/#truck) Wheeled-engine-vehicle [java] - (http://ontosem.org/#fire-engine rdfs:label ' "a truck with equipment for fighting fires"') [java] - (http://ontosem.org/#fire-engine rdf:type owl:Class) [java] fire-engine recognized as subclas of vehicle BUILD SUCCESSFUL Total time: 10 seconds real 0m11.144s user 0m9.530s sys 0m0.190s [[email protected] ontojena]$ Truck Fire-engine
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Different only in base-URI . _:g103 . _:g104 _:g103 . _:g104 . _:g105 . _:g105 . _:g105 . . _:g103 . _:g104 _:g103 . _:g104 . _:g105 . _:g105 . _:g105 . Introduction ᵒ Approach ᵒ Evaluation ᵒ Conclusion 11
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 Data Hazards  How will we eliminate the remaining two stall cycles ?  We will use forwarding also known as bypassing to do that  All RAW Pipelined MIPS CPU Design : Version 1  This means we have additional hardware to eliminate the stalls  The additional hardware will be new wires also MUX2 and MUX3 of the datapath will be larger 200 204 208 20C 210 214 218 21C To visualize how we can do this, let’s look at the Version 1 state diagram and the datapath for the DADD instruction LD DADD DSUB XOR SLT OR SD BEQZ R1, 500(R0) R2, R3, R4 R5, R6, R2 R8, R9, R2 R11, R12, R2 14, R15, R2 R2, 600(R0) R2, 5 1 2 3 4 5 6 IF ID EX MEM WB IF ID EX MEM WB IF ID Stall Stall IF Stall Stall Stall Stall Stall 7 EX ID IF Stall Stall 8 9 MEM WB EX MEM ID EX IF ID Stall IF Stall Stall 10 ID IF The new value of R2 is calculated in the EX stage in the 4th clock period for the DADD CS 6133 Haldun Hadimioglu MIPS Versions 0 & 1 241
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• Pastoralist: http://www.newint.org/issue378/pics/life-3.jpg • Camels: http://www.thisfabtrek.com/journey/africa/mauritania/20061106-nouakchott/camels-waterhole-4.jpg • Netsilik: http://www.dreamspeakers.org/2005/images/films/through_these_eyes.jpg • Inupiat: http://images.myareaguide.com/aps/op/inup.jpg • Inupiat sled: http://assets.espn.go.com/i/eticket/20061009/photos/eticket_u_histfam_310.jpg • Bushmen: http://www.gonomad.com/lodgings/0611/namgallery-images/bushman-familyb.jpg • Bushmen hunters: http://www.gudigwa.com/images/zoom/gudigwa-bushmen-hunting.jpg • Mbuti: http://kim.uing.net/files/post_file_3980.jpg • Andaman: http://www.andaman.org/BOOK/chapter13/pla13-5.jpg • Lakota: http://www.old-picture.com/old-west/pictures/Lakota-Sioux.jpg • Bororo: http://www.gutenberg.org/files/22483/22483-h/images/ill1-232a.jpg • Blackfoot: http://www.topfoto.co.uk/gallery/AlternativeHousing/images/prevs/photri1018798.jpg • Ariaal Warrior: http://photography.nationalgeographic.com/staticfiles/NGS/Shared/StaticFiles/Photography/Images/POD/a/ariaal-wa rrior-525467-sw.jpg • Chukchee: http://polarhusky.com/logistics/chukotka/people/chukchi.attachment/logisticschukotkapeoplechukchi020/LogisticsC hukotkaPeopleChukchi020.jpg • Kurds: http://i.infoplease.com/images/home/kurds-sheep.jpg • Pastoralists and camels: http://mediaglobal.org/admin/wp-content/uploads/2007/07/pastoralists.camels.jpg • Pastoralists: http://www.mursi.org/news-items/meeting-of-pastoralists-in-south-omo-zone-planned-for-8-12-november/image_m ini • Masaai: http://www.kitumusote.org/sites/kitumusote.org/files/images/history%20of%20maasai%20page%201.img_assist_cu stom.JPG • Saami: http://upload.wikimedia.org/wikipedia/commons/thumb/8/87/Saami_Family_1900.jpg/800px-Saami_Family_1900.jp g • Akan: http://crawfurd.dk/illu/weekly/akanking.jpg • Banyoro: http://www.ugpulse.com/images/articles/daily/20060921_100_8.jpg • Garifuna: http://www.allseasonsbelize.com/images/allgemein/garifuna.jpg • Shipibo: http://www.shamanic.net/pictures/Peru2007/carlos.jpg • Tikopia: http://www.tallshipstales.de/90s/imgs/EricMatson/boys-of-tikopia.jpg • Tzeltal: http://farm2.static.flickr.com/1092/1082248917_0e9805da6e.jpg • Yanomami: http://www.giemmegi.org/images/festa-yanomami-6.jpg • Amhara: http://en.kindernothilfe.org/en/Rubrik/Countries/Africa/Ethiopia/_Better+Future+for+children__Project.html • Bengali: http://picasaweb.google.com/dleclercq/TripMiddleEastAndTheBalkans/photo#5147508446831035218 • Thai: http://www.dkimages.com/discover/previews/806/50081622.JPG • Monguor: http://www.joshuaproject.net/profiles/photos/p114229.jpg • Santhal: http://farm1.static.flickr.com/20/71832446_4854285fe0_m.jpg • Lepcha: http://www.joshuaproject.net/profiles/photos/p105723.jpg • Shluh: http://farm1.static.flickr.com/37/92620708_6928efedf0.jpg • Sinhalese: http://www.joshuaproject.net/profiles/photos/p109305.jpg • Ifugao: http://www.madnomad.com/gregg/img/cordill_01.jpg • Dogon: http://saharanvibe.blogspot.com/2007/06/dogon-people-of-bandiangara.html Graphics Cited This lecture discusses how people get their food. Of all the cultural traits, this is the most important as it conditions virtually all other social institutions.
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Referencias                         http://en.wikipedia.org/wiki/TLCAN http://es.wikipedia.org/wiki/Tratado_de_Libre_Comercio_de_Am%C3%A9rica_del_Norte http://www.nwlaborpress.org/2003/12-19-03TLCAN.html http://www.fair.org/index.php?page=1396 http://www.prensalatina.com.mx/article.asp?ID={5CE21DEF-9E6F-4F94-B016-F97DF4F1EDD 2} http://sdpjalisco.senderodelpeje.com/2008/11/06/productores-de-maiz-exigen-mejores-precios-a -sus-cultivos/ http://www.organicconsumers.org/espanol/080905_maiz.htm http://www.TLCAN-sec-alena.org/DefaultSite/index_e.aspx?ArticleID=299 http://www.cec.org/pubs_info_resources/law_treat_agree/naaec/index.cfm?varlan=english http://www.naalc.org/naalc.htm http://www.nadbank.org/about/about_origins.html http://www.cocef.org/background.htm http://www.sice.oas.org/trade/TLCAN/TLCANtce.asp http://www.fvdrc.com/ http://es.wikipedia.org/wiki/Tratado_de_Libre_Comercio_de_Am%C3%A9rica_del_Norte http://en.wikipedia.org/wiki/North_American_Free_Trade_Agreement http://useconomy.about.com/od/tradepolicy/p/TLCAN_History.htm http://www.citizen.org/trade/TLCAN/ http://www.fpif.org/briefs/vol4/v4n26TLCAN.html http://www.siliconv.com/trade/tradepapers/environmental.html http://emaychair.dal.ca/ http://sesc.zlir.com/sustainability-center-student-forum-wed-feb-6th-at-7pm/ http://www.heritage.org/research/tradeandeconomicfreedom/bg1480.cfm http://www.smh.com.au/news/opinion/earth-needs-a-climate-of-change/2005/07/17/112153886 2977.html
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Data Hazards  We will draw short lines in the WB and ID stages to indicate that the RAW hazard has been resolved by the write-in-first-half-read-in-the-second-half feature  Writing to a GPR in the first half – reading the same GPR register in the second half of the same clock period All RAW Pipelined MIPS CPU Design : Version 1  200 204 208 20C 210 214 218 21C Let’s see the new execution flow LD DADD DSUB XOR SLT OR SD BEQZ R1, 500(R0) R2, R3, R4 R5, R6, R2 R8, R9, R2 R11, R12, R2 14, R15, R2 R2, 600(R0) R2, 5 We stall the DSUB for 2 clock periods and create a 2-clock period bubble that moves up the pipeline WB MEM CS 6133 EX ID IF 1 2 3 4 5 6 IF ID EX MEM WB IF ID EX MEM WB IF ID Stall Stall IF Stall Stall Stall Stall Stall ? ? ? ? v ? ? ? v v ? ? v v v ? v v v v Haldun Hadimioglu v v 7 EX ID IF Stall Stall 8 9 MEM WB EX MEM ID EX IF ID Stall IF Stall Stall v v v v v v v v v v v v MIPS Versions 0 & 1 10 ID IF v v v v ? 237
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Motor Controls Actions Left Forward Left Reverse Left PWM Left Motion Low Low Low Low High High High Low Low High High Low Low High Low High Low High Low High Low High High High Coasting Coasting Coasting Reverse Coasting Forward Coasting Active Braking Right Forward Right Reverse Right PWM Low Low Low Low High High High Low Low High High Low Low High Low High Low High Low High Low High High High Right Motion Coasting Coasting Coasting Reverse Coasting Forward Coasting Active Braking 13
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VOMmean w F=(DPP-MN)/4 Concrete4150(C, W, FA, Ag) 0 1 1 1 5 1 6 1 7 1 _________[0,9) 8 4 9 1 [9,14) 10 1 11 2 12 1 13 5 14 1 [14,18) 15 3 16 3 17 4 18 1 [18,23) 19 3 20 9 21 4 22 3 23 7 24 2 [23,31) 25 4 26 8 27 7 28 7 29 10 30 3 31 1 [31,36) 32 3 33 6 34 4 35 5 37 2 [36,39) 38 2 40 1 [39,52) 42 3 43 1 44 1 45 1 46 4 ______ 49 1 56 1 [52,90) 58 1 61 1 65 1 66 1 69 1 71 1 77 1 80 1 83 1 _________[0.90) 86 1 100 1 [90,113) 103 1 105 1 108 2 112 1 e4 accuracy rate = 104/150= 69% 2 Low 1 Low 5 Medium 3 Medium 5 High 5 High CLUS_1.1.1.1.1.1.1.1.1 CLUS_1.1.1.1.1.1.1.1.2 5 Low 2 Medium 4 High 6 Low 1 Medium 13 High CLUS_1.1.1.1.1.1.2 25 Low 4 Medium 19 High CLUS_1.1.1.1.1.2 3 Low 7 Medium 11 High CLUS_1.1.1.1.2 1 Low 1 Medium 2 High 0 Low 12 Medium 1 High 0 Low 11 Medium CLUS_1.1.1.1.1.1.1.2 . 0 High CLUS_1.1.1.2 CLUS_1.1.2 CLUS_1.2 43 Low 46 Medium 55 High CLUS_1 0 Low 6 Medium 0 High CLUS_2 d=e4 Conc4150 ________=0 0 17 ________=1 1 11 ________=3 3 12 ________=6 6 35 _______ ________=13 13 25 _______ 22 25 =22 24 8 =24 44 7 ________=44 67 ________=67 4 89 2 ________=89 91 4 13 Lo 2 Lo 12 Lo 13 Lo 3 Lo 0 Lo 0 Lo 0 Lo 0 Lo 0 Lo 4 Med 9 Med 0 Med 5 Med 3 Med 6 Med 8 Med 7 Med 4 Med 4 Med 0 4 STD=(101,28,99,81) d=e1 Conc4150 6 3 7 2 8 Low 7 Medium 0 High CLUS_1.1.1.1.1.2 12 10 [9,16) 13 2 14 3 CLUS_1.1.1.1.2 18 9 [16,31) 18 Low 11 Medium 0 High 20 4 22 5 23 3 24 5 27 3 1 Low 3 Medium 3 High CLUS_1.1.1.2 31 3 [31,39) . 36 4 5 Low 5 Medium 7 High CLUS_1.1.2 41 2 [39,52) 42 1 43 4 44 3 46 3 48 2 ______ 49 2 55 13 4 Low 17 Medium 38High CLUS_1.2 58 8 [52,80) 60 6 Entirely inconclusive using e ! 62 5 1 65 4 71 16 72 4 ________[0.80) 43Low 46Medium 55High CLUS_1 74 3 7 High CLUS_2 82 4 [80,101) 0 Low 7 Medium 83 7 97 2 100 1 VOM MN 0 Hi 0 Hi 0 Hi 17 Hi 19 Hi 19 Hi 0 Hi 0 Hi 0 Hi 0 Hi CLUS_11 CLUS_10 CLUS_9 CLUS_8 CLUS_7 . CLUS_6 . CLUS_5 CLUS_3 CLUS_1 CLUS_2 d=e3 Conc4150 0 15 3 2 ________ 5 4 17 3 19 8 21 1 29 3 ________ 41 28 46 3 47 8 48 3 52 4 ________ 53 15 58 3 62 4 63 4 64 1 65 7 67 3 69 4 72 3 73 12 75 2 78 5 83 1 100 4 2,4 [0.9) [9,32) 3 Low 1 Low 16 Medium 8 Medium 2 High CLUS_1.1 6 High CLUS_1.2 [0.32) 4 Low 24 Medium 8 High CLUS_1 [32,101) 39 Low 28 Medium 47 High CLUS_2 [32,55) 21 Low 12 Medium 28 High CLUS_2.1 [55,101) 1 Low 8 Medium 6 High CLUS_2.2 0 2 3 4 ________[0,5) 3 Lo 1 Med 2 Hi CLUS_2 8 4 ________=8 0 Lo 1 Med 3 Hi CLUS_3 10 2 ________=10 0 Lo 2 Med 0 Hi CLUS_4 12 8 ________[10,14) 1 Lo 4 Med 9 Hi CLUS_5 13 4 15 4 16 14 17 3 18 1 19 3 ________[14,21) 9 Lo 9 Med 15 Hi CLUS_6 20 8 22 15 ________[21,25) 3 Lo 1 Med 15 Hi CLUS_7 24 4 ________[25,28) 5 Lo 1 Med 3 Hi CLUS_8 27 9 29 3 e2 accuracy= 30 6 31 3 Inconclusive on e2! 93/150=62% 32 3 33 7 34 4 d=e2 ________[28,36) 14 Lo 12 Med 8 Hi CLUS_9 35 8 0 Hi CLUS_10 5 [36.40) 7 Lo 1 Med Conc4150 37 38 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 18 19 20 21 29 30 31 32 34 35 36 62 64 93 121 125 2 5 6 12 2 1 6 6 1 4 12 11 5 3 2 9 10 4 1 4 9 4 9 4 1 2 5 4 2 4 2,4 =0 2L 0M 0H C14 =1 1L 4M 0H C13 [2,4) 11L 6M 1H C12 =4 0L 2M 0H C11 [5,9) 14L 0M 0H C10 [9,11) 3L 0 M 13H C9 =11 =12 =13 [15,25) 5L 5L 0L 2L 2 M 4H 0 M 0H 3 M 0H 4 M 19H C8 C7 C6 C5 [25,33) 0L 0 M 18H C4 [33,50) 0L 14 M 0H C3 [50,93) 0L 7 M 0H C2 [93,m) 0L 10M 0H C1 Accuracy= 127/150=85% CONCRETE
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Seismic attribute-assisted interpretation of incised valley fill geometries: A case study of Anadarko Basin Red Fork interval. Yoscel Suarez*, Chesapeake Energy and The University of Oklahoma, USA Kurt J. Marfurt, The University of Oklahoma, USA Mark Falk, Chesapeake Energy, USA Al Warner , Chesapeake Energy, USA Seismic Attribute Generation Edge Detection Relative Acoustic Impedance The Relative Acoustic Impedance (RAI) is a simplified inversion. This attribute is widely used for lithology discrimination and as a thickness variation indicator. Since the RAI enhances impedance contrast boundaries, it may help delimit different facies within an incised valley-fill complex. Figure 15 shows the better delineation of the different valley-fill episodes. The impedance amplitude variations within the system may be correlated to sand/shale ratios. Higher values of RAI seem to be related to sandier intervals (black arrow). Coherence According to Chopra and Marfurt (2007) coherence is a measure of similarity between waveforms or traces. Peyton et al. (1998) showed the value of this edge detection attribute to identify channel boundaries in the Red Fork level. Figure 11 shows the results of the modern coherence algorithm and the interpretation. The modern coherence algorithm is slightly superior. It shows additional features (blue arrows), and enhances the edge of Phase II (pink arrow). It also shows that the current outlines of Phase II could be modified in the encircled areas. Figure 15. Relative Acoustic Impedance (RAI) at the Red Fork level. Figure 11. Modern coherency horizon slice at the Red Fork level Figure 12. Other modern edge-detector attributes: a) Sobel coherence. b) Energy ratio coherence Energy Weighted Coherent Amplitude Gradients Chopra and Marfurt (2007), by using a wedge model, demonstrate that waveform difference detection algorithms are insensitive to waveform changes below tuning frequencies. In this study the energy ratio coherence, defined by the coherent energy normalized by the total energy of the traces within the calculation window, and the Sobel coherence, which is a measure of relative changes in amplitude were used. Figure 12 shows a horizon slice of the energy ratio coherence and the Sobel coherence at the Red Fork level. The results from these two energy weighted routines are very similar to the coherence attribute, however the level of detail of the coherency algorithm is greater in the encircled areas. Even though both algorithms show similar features, the Sobel coherence seems to be more affected by the acquisition footprint than does the energy ratio coherence. Seismic Attribute Blending Peak Frequency and Peak Amplitude Displays Liu and Marfurt (2007) show that by combining the peak frequency and peak amplitude volumes extracted from the spectral decomposition analysis, the interpreter can identify highly tuned intervals. Low peak frequency values correlate with thicker intervals and high peak frequencies with thinner features. Figures 16 (a,b) show the peak frequency and peak amplitude volumes respectively. Figure 16(c) shows the combination of both displays, which simplifies the interpretation of multiple volumes of data. Figure 16(d) shows the blended image with the overlain geological interpretation. This combination iof attributes shows a better definition of the Phases boundaries especially the Phase II in the NW corner of the survey, in between the two valley branches. The changes in facies within the Phase V are evident in the southernmost green arrow. The differentiation between the Phase III and Phase V is sharper (northernmost green arrow). Outside of the incised valley system the lithology relationship with frequency is still unclear. The dashed orange lines show the proposed changes to the Phase II outline. Curvature Although successful in delineating channels in Mesozoic rocks in Alberta, Canada (Chopra and Marfurt, 2008), for this study, volumetric curvature does not provide images of additional interpretational value. While the Red Fork channel boundaries can be delineated using this attribute (Figure 13), the results shown by the coherence and spectral decomposition are superior. In this situation the acquisition footprint negatively impacts the lateral resolution quality of the attribute. Blue arrows indicate channel edges. Figure 13. Other modern edge-detector attributes: a) Sobel coherence. b) Energy ratio coherence Figure 16. Peak Frequency and Peak Amplitude analysis at the Red Fork level. (a) Peak Frequency volume, red corresponds to higher frequencies. (b) Peak Amplitude volume, white corresponds to higher peak amplitude values. (c) Peak frequency and peak amplitude blended volume. The co-rendered image shows valley-fill boundaries. (d) co-rrendered image with interpretation Spectral Decomposition Matching pursuit spectral decomposition was used to generate individual frequency volumes as well as peak amplitude and peak frequency datasets. Castagna et al. (2003) discuss the value of using matching pursuit spectral decomposition and how we can associate different “tuning frequencies” to different reservoir properties like fluid content, thickness and/or lithology. Figure 14 shows a matching pursuit 36 Hz spectral component at the Red Fork level. The level of detail using matching pursuit spectral decomposition is superior to that provided by the DFT Figure 14. 36 Hz matching pursuit spectral decomposition. Note the enhanced level of detail offered by the matching pursuit spectral decomposition. a) without geological interpretation b) with geological interpretation This study has identified correlations between attribute expressions of Red Fork channels that can be applied to underexploited exploration areas in the Mid-continent, and to fluvial deltaic channels in Paleozoic rocks in general. When it comes to answer the key questions discussed at the beginning of this paper, we learned that the coherence and energy weighted attributes help improve the resolution of subtle features like small channels and channel levees. They also help differentiate the cutbank from the gradational inner bank. It is also evident from this study that even though there have been some improvements in the coherence routines, the differences between current algorithms with the ones applied by Peyton et al. in 1998 are minimal. Additionally, detailed channel geomorphology and lithology discrimination were possible by introducing the spectral decomposition and relative acoustic impedance attributes in the analysis. On one hand, the use of spectral decomposition helped define different facies within the channel system and increased the resolution of channel boundaries. On the other hand, the variations in the RAI values were found to be correlative to lithology infill, for instance higher values of RAI show direct relationship to shalier intervals within the channel complex. One of the key findings of this study is the great value that blended images of attributes bring to the interpreter. Such technology was not available ten years ago. But today, by combining multiple attributes, fluvial facies delineation is possible when co-rendering edge detection attributes with lithology indicators. It is important to mention that the signal/noise ratio of the data is a key factor that will determine the resolution and quality of the seismic attribute response. In this study, curvature did not provide images of additional interpretational value. These unsatisfactory results may be related to acquisition footprint contamination. Therefore, footprint removal methods will be performed in an attempt to enhance signal-tonoise ratio. Acknowledgments We thank Chesapeake Energy for their support in this research effort. We give special thanks to Larry Lunardi, Carroll Shearer, Mike Horn, Mike Lovell and Travis Wilson for their valuable contribution and feedback. And to my closest friends Carlos Santacruz and Luisa Aurrecoechea for cheering me up at all times. Amplitude Variability Semblance of the Relative Acoustic Impedance Chopra and Marfurt (2007) define semblance as “the ratio of the energy of the average trace to the average energy of all the traces along a specified dip.” Since RAI has sharper facies boundaries the semblance computed from RAI should be crisper than semblance computed from the conventional seismic. Figure 17 shows the value of combining these attributes. Outside of the channel complex the lithology relationship with frequency is still unclear(red arrow). The yellow arrow points to a potential fluvial channel outside of the incised valley-system. The dashed orange lines show the proposed changes to the Phase II outline. Conclusions Figure 17 a) the Semblance of the RAI and b) RAI and RAI semblance blended image. The combination of both attributes helps delineate Relative Acoustic Impedance boundaries.
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Work Breakdown Schedule Aaron 145 hrs Matt 148 hrs 1.1 Review General Air Foil Theory 6 hrs 1.1 Review General Air Foil Theory 6 hrs 1.2 Preliminary Senior Design Coordinator Meetings 2 hrs 1.2 Preliminary Senior Design Coordinator Meetings 2 hrs 1.3 Examine Existing RC Planes 12 hrs 1.3 Examine Existing RC Planes 12 hrs 1.4.1 Select Competition Class 10 hrs 1.4.1 Select Competition Class 10 hrs 10 hrs 1.4.2 Review Selected Class Requirements 10 hrs 2.1.1 Review Existing Wing Designs 8 hrs 2.2.1 Existing Technology Review 9 hrs 2.1.2 Select Basic Wing Layout 9 hrs 2.2.2 Theoretical Propeller Design 9 hrs 2.1.3 Theoretical Design of Wing 18 hrs 2.2.3 Computer Aided Propeller Analysis 9 hrs 2.1.4 Computer Aided Wing Analysis 14 hrs 2.2.4 Physical Modeling 9 hrs 2.1.5 Physical Modeling 10 hrs 2.3.1 Aerodynamic Review 6 hrs 3.1 Combine Wing, Propeller, Fuselage Models 2 hrs 2.3.2 Theoretical Fuselage Design 8 hrs 3.2 Wind Tunnel Testing 2 hrs 2.3.3 Computer Aided Fuselage Design 6 hrs 3.3 Analyze Results 1 hr 2.3.4 Physical Modeling 4 hrs 4.1.1 Project Proposal 4 hrs 3.1 Combine Wing, Propeller, Fuselage Models 2 hrs 4.1.2 Semester Report 14 hrs 3.2 Wind Tunnel Testing 2 hrs 4.2.1 Project Proposal 4 hrs 3.3 Analyze Results 1 hr 4.2.2 Semester Report Brett 19 hrs 148 hrs 4.1.1 Project Proposal 4 hrs 4.1.2 Semester Report 14 hrs 1.1 Review General Air Foil Theory 6 hrs 4.2.1 Project Proposal 6 hrs 1.2 Preliminary Senior Design Coordinator Meetings 2 hrs 4.2.2 Semester Report 19 hrs 1.3 Examine Existing RC Planes 12 hrs Tzvee 145 hrs 1.4.1 Select Competition Class 10 hrs 1.1 Review General Air Foil Theory 6 hrs 1.4.2 Review Selected Class Requirements 10 hrs 1.2 Preliminary Senior Design Coordinator Meetings 2 hrs 2.2.1 Existing Technology Review 9 hrs 1.3 Examine Existing RC Planes 12 hrs 2.2.2 Theoretical Propeller Design 9 hrs 1.4.1 Select Competition Class 10 hrs 2.2.3 Computer Aided Propeller Analysis 9 hrs 1.4.2 Review Selected Class Requirements 10 hrs 2.2.4 Physical Modeling 9 hrs 1.5 Establish Requirements Matrix 4 hrs 2.3.1 Aerodynamic Review 6 hrs 2.1.1 Review Existing Wing Designs 8 hrs 2.1.2 Select Basic Wing Layout 9 hrs 2.3.2 Theoretical Fuselage Design 8 hrs 2.1.3 Theoretical Design of Wing 18 hrs 2.3.3 Computer Aided Fuselage Design 6 hrs 2.1.4 Computer Aided Wing Analysis 14 hrs 2.3.4 Physical Modeling 4 hrs 2.1.5 Physical Modeling 10 hrs 3.1 Combine Wing, Propeller, Fuselage Models 2 hrs 3.1 Combine Wing, Propeller, Fuselage Models 2 hrs 3.2 Wind Tunnel Testing 2 hrs 3.2 Wind Tunnel Testing 2 hrs 3.3 Analyze Results 1 hr 3.3 Analyze Results 1 hr 4.1.1 Project Proposal 4 hrs 4.1.1 Project Proposal 4 hrs 4.1.2 Semester Report 14 hrs 4.1.2 Semester Report 14 hrs 4.2.1 Project Proposal 6 hrs 4.2.1 Project Proposal 0 hrs 4.2.2 Semester Report 19 hrs 4.2.2 Semester Report 19 hrs 1.4.2 Review Selected Class Requirements
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 Data Hazards  Let’s concentrate on the DADD and the instructions that follow it What if DSUB does not have a RAW hazard but XOR has ? 1 2 All RAW Pipelined MIPS CPU Design : Version 1  200 204 208 20C 210 214 218 21C LD DADD DSUB XOR SLT OR SD BEQZ R1, 500(R0) R2, R3, R4 R5, R6, R7 R8, R9, R2 R11, R12, R2 14, R15, R2 R2, 600(R0) R2, 5 We stall the XOR for 2 clock periods and create a 2-clock period bubble that moves up the pipeline WB MEM CS 6133 EX ID IF 3 1 4 5 6 IF ID EX MEM WB IF ID EX MEM WB IF ID EX MEM IF ID Stall IF Stall Stall ? ? ? ? v ? ? ? v v ? ? v v v ? v v v v Haldun Hadimioglu v v v v v v v 7 WB Stall Stall Stall Stall 8 EX ID IF Stall Stall 9 MEM WB EX MEM ID EX IF ID Stall IF v v v v 10 v v v v v v v v ? MIPS Versions 0 & 1 229
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