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A Z!@02=5=85 Cluster OpenMP* A 4@C38<8 A8AB5<0<8( F ` p  0pB   `_ж_жD?"``pB   `_ж_жD?"`p p0  3 r~_ж_ж ?"`   *0B@0BK =0 @07@01>B:C0    3 r_ж_ж ?" f >@>3>"0    3 rP_ж_ж ?" `"p f 5H52>"0 *   3 rԉ_ж_ж ?"  z$@>872>48B5;L=>ABL0    3 r0_ж_ж ?"T'; f 87:0O"0    3 r_ж_ж ?"T; hKA>:0O"0    f썝_ж_жGHK?" p@ JCluster OpenMP 0    f_ж_жGH_4?"p P  oMPI*, Socket pgming0    3 rW#_ж_ж?"o  l450;L=>$ 0    S ~|_ж_жGHJ?"$  ^$EJB*, SOAP*, ASP.NET*, CORBA*, DCOM*%0 %  <,V Q!Copyright 2004 Intel Corporation"" P  Z ?"6@ NNN?N7 N* Third party trademarks and names are the property of their respective owner.O0(2O H  0޽h ??0 33___PPT10i.V`+D=' `= @B +  0 7/p(  p  p BX ?0F V@>872>48B5;L=>ABL Cluster OpenMP* ?@>3@0<<( ^ p 0  0  082=>5 ?@8<5=5=85 Cluster OpenMP A:>@55 2A53> 40AB ?;>ECN ?@>872>48B5;L=>ABL 0B@0BK =0 ?>;CG5=85 E>@>H59 ?@>872>48B5;L=>AB8 A>?>AB028<K A 70B@0B0<8 =0 ?@>3@0<<8@>20=85 A MPI*, => ?@>F5AA C;CGH5=8O ?@>872>48B5;L=>AB8 ?@>I5, B0: :0: <>65B 1KBL ?>AB5?5==K< 0718209B5 @0745;O5<K5 40==K5 =0 =57028A8<K5 1;>:8 A5 >A=>2=K5 2KG8A;5=8O ?@>872>48B5 A private 40==K<8 8=8<878@C9B5 A8=E@>=870F8N.ZZ+^M2& p < &R Q!Copyright 2004 Intel Corporation"" P p Z ?"6@ NNN?N7 N* Third party trademarks and names are the property of their respective owner.O0(2O H p 0޽h ? 3___PPT10i.`2+D=' `= @B +  0 -(  r  S ># ` `}  # r  S h?#`m ` #   <pV Q!Copyright 2004 Intel Corporation"" P  ZA# ?"6@ NNN?N7 N* Third party trademarks and names are the property of their respective owner.O0(2O   BG#VPP r: Intel ,  Thread Checker , and  Thread Profiler are registered trademarks of Intel Corporation or its subsidiaries in the United States or other countries.0 H  0޽h ? 33___PPT10i.`t]+D=' `= @B +  0 $A(  $r $ S k# ` `}  # r $ S k#` ` #  $ <dq#V Q!Copyright 2004 Intel Corporation"" P $ Z0n# ?"6@ NNN?N7 N* Third party trademarks and names are the property of their respective owner.O0(2O H $ 0޽h ? 33___PPT10i.@]O+D=' `= @B +  0  A(   r  S p]# ` `}  # r  S H^#` ` #   <C#V Q!Copyright 2004 Intel Corporation"" P  ZLb# ?"6@ NNN?N7 N* Third party trademarks and names are the property of their respective owner.O0(2O H  0޽h ? 33___PPT10i.@dz-+D=' `= @B +d 0 `d(     T#gֳgֳ ? :>45;L ?0<OB8 Cluster OpenMP*(  T*gֳgֳ ?  h 0745;O5<K5 (sharable) 40==K5 @0A?>;030NBAO 2 A?5F80;L=>9 ?0<OB8, :>B>@>9 C?@02;O5B Distributed Virtual Shared Memory (DVSM) >445@68205BAO A;010O :>=A8AB5=B=>ABL ?0<OB8 (weak consistency) 2 A>>B25BAB288 A <>45;LN ?0<OB8 OpenMP* 7<5=5=8O @0745;O5<KE 40==KE A;820NBAO 2 B>G:0E A8=E@>=870F88 (flush >?5@0F88) (4U4  6)  ? H  0޽h ? 380___PPT10..0= 0  @ #(     ` *gֳgֳ ?AC 5!Distributed Virtual Shared MemoryR  s *   <*GHKe    F0 RB  s *DpRB  s *Dp@RB  s *D RB  s *D RB  s *D RB  s *D` @  <*80 E shared data 0   <*,  PMulti-threaded program0 l 0   #0  ,$D 0T `   # `  Z  s *̙`  Z  s *̙`` 0 Z  s *̙ ` P Z  s *̙`    B*0   >DVSM0z p0  p0,$D 0N P   P   <!* P  @Node 00  <%*` 0 P  @Node 10  <h)* PP  BNode n-1 0   <-* P  @Node n0  <0*  q  ;...0`2  B4*Ԕpp0 MNetwork or Switch 0ZB  s *DԔ P ZB  s *DԔP @ZB  B s *DԔ P ZB !B s *DԔP  " <8:*&R Q!Copyright 2004 Intel Corporation"" H  0޽h ? 3___PPT10. lc{+tHD~' `= @B D9' = @BA?%,( < +O%,( < +D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*#%(+L 0 `(     ` ^*gֳgֳ ?AC l(@8=F8? @01>BK DVSM (F p0  p0N P   P   <`* P  @Node 00  <d*` 0 P  @Node 10   <h* PP  BNode n-1 0    <e* P  @Node n0   <\o*  q  ;...0`2   B,s*Ԕpp0 MNetwork or Switch 0ZB   s *DԔ P ZB  s *DԔP @ZB B s *DԔ P ZB B s *DԔP   <pw*0 OShared data A,B,C,D,E0  <{*  :Load A Store B Barrier Load & >0ff  <*0 OShared data A,B,C,D,E0  <~*  :Load A Store E Barrier Load & >0ff  <*0 P OShared data A,B,C,D,E0  <* P  :Load A Store D Barrier Load & >0ff  <*0`0  OShared data A,B,C,D,E0  <*`0  yLoad A Store C Barrier Load ...> 0f f*  B8Q*B ,$ 0 .Seg faults  fetch data 0f  B̢* ,$ 0 sExch Wr Notices0$ *  B* ,$ 0 .Seg faults  fetch data 0f  <d*&R Q!Copyright 2004 Intel Corporation"" P  Z* ?"6@ NNN?N7 N* Third party trademarks and names are the property of their respective owner.O0(2O H  0޽h ? 3___PPT10. qg+f7D' `= @B D' = @BA?%,( < +O%,( < +DA' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(DA' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(DA' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(++0+0 ++0+0 ++0+0 +* 0 D<.0(     `8*gֳgֳ ?`0 ,Lazy Release ConsistencyLB  c $D}` ` sF    |<  <* @ ;A0  <T*  ;C0   <* @ ;B0LB  c $D}0 0 LB  c $D}  <* >Node 00   <* p  >Node 10   <8* p >Node 20 sF    J   <* @ ;A0  <d*  ;C0  <@* @ ;B0sF    J   <* @ ;A0  <*  ;C0  < * @ ;B0z    ,$D 0   6*f  +Write A[1] Twin A Write C[1] Twin C BarrierV,0 f f  <*V  }Write B[2] Twin B BarrierF0 f  </V  +Write A[2] Twin A Write B[1] Twin B BarrierV,0 f fIz ` l    ,$D 0ZB B s *D  ZB B s *D  ZB  s *D@@ p ZB  s *Df@     <8 /@`   MWrite notices(1B) 0f ! <P/ /  PWrite notices(2A,2B) 0f " </@ bp  YWrite notices(0A,2A,1B,2B,0C) 0f # <t/J l  YWrite notices(0A,2A,1B,2B,0C) 0f $ <x/  ,$ 0 \Read A[1] Page Fault,0  fLz P ` %  9,$D 0ZB &B s *Df@ pZB ' s *Df@ @ ( < /P yp KDiff request(A) 0f ) <%/ @ KDiff request(A) 0fZB * s *DfZB +B s *Df` , <)/p0 ^Diffs(A) 0 f - <./ppe0 ^Diffs(A) 0 f . <3/ V ,$ 0 D Re-read A[1] 0 LB / c $D} 0 <-/&R Q!Copyright 2004 Intel Corporation"" H  0޽h ? 3  ___PPT10 . Pq+DL ' `= @B D ' = @BA?%,( < +O%,( < +D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*%(DA' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*$%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*%%(DA' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*.%(+p+0+$0 ++0+.0 +,  0 C;,(  ,r , S # ` `}  # r , S #` ` #  , <#V Q!Copyright 2004 Intel Corporation""  , BL# p8 Intel ,  Thread Checker and  Thread Profiler are registered trademarks of Intel Corporation or its subsidiaries in the United States or other countries.0 H , 0޽h ? 33___PPT10i.$q+D=' `= @B +z  0 !(  x  c $dm ` `}  m x  c $` ` m   <mV Q!Copyright 2004 Intel Corporation""   B m p8 Intel ,  Thread Checker and  Thread Profiler are registered trademarks of Intel Corporation or its subsidiaries in the United States or other countries.0 :  3 A `kH  0޽h ? 33___PPT10i.$q+D=' `= @B +`y 0 wxoxuxx(  z  T\d/gֳgֳ ? !B0B8AB8:0 87<5=5=8O 8AE>4=KE :>4>2 ?@8 ?>@B8@>20=88 4;O Cluster OpenMP*II$.( Mv 74 x #"RFff  Bo/ ?44 R  @`  B(q/ ?44 R  @`  B/ ? 4 R  @`   B܈/ ?  4 R  @`   B/ ?X  4 R  @`   BT/ ?(X 4 R  @`   BH/ ?(4 R  @`   B6___PPT9 F78((" "  B(/ ?/4F>6___PPT9 F12((" "  B/ ? /F>6___PPT9 H2200((" "  B/ ? / F>6___PPT9 F25((" "  B/ ?X / F>6___PPT9 IFortran& " "   B/ ?(/X F>6___PPT9 EQCD& " "  B/ ?/(F>6___PPT9 M 310.wupwise& "  "  BD/ ?4p /F>6___PPT9 F24((" "   B/ ?p 4/F>6___PPT9 E1((" "  B/ ? p /F>6___PPT9 G400((" "   B/ ? p /F>6___PPT9 E1((" "  B/ ?X p  /F>6___PPT9 IFortran& " "  B/ ?(p X /F>6___PPT9 PShallow water & " "  Bp/ ?p (/F>6___PPT9 J312.swim& "  "   B@/ ?4 p F>6___PPT9 E3((" "   Bt/ ? 4p F>6___PPT9 E1((" "  B/ ?  p F>6___PPT9 G500((" "   B/ ? p F>6___PPT9 E1((" "  B/ ?X  p F>6___PPT9 IFortran& " "   Bp/ ?( X p F>6___PPT9 RMultigrid solver& " " ! B/ ? (p F>6___PPT9 K 314.mgrid& "  " " Bt/ ?4  F>6___PPT9 F44((" "  # B/ ? 4 F>6___PPT9 E1((" " $ B/ ?   F>6___PPT9 H1500((" "  % B0 ?  F>6___PPT9 E1((" "  & B0 ?X  F>6___PPT9 CC& " "@ ' Bd0 ?( X F>6___PPT9 xEarthquake modelling& " "  ( B$ 0 ? ( F>6___PPT9 L 320.equake& "  " ) Bl0 ?43  F>6___PPT9 F74((" "  * B0 ?3 4 F>6___PPT9 E8((" " + B0 ? 3  F>6___PPT9 I15300((" " , B0 ? 3  F>6___PPT9 F39((" " - B0 ?X 3  F>6___PPT9 IFortran& " " . B!0 ?(3 X F>6___PPT9 PFluid dynamics& " " / B 0 ?3 ( F>6___PPT9 L 318.galgel& "  "  0 B)0 ?4t 3 F>6___PPT9 E2((" "  1 B,-0 ?t 43 F>6___PPT9 E1((" " 2 B'0 ? t 3 F>6___PPT9 H1500((" "  3 BT40 ? t 3 F>6___PPT9 E1((" " 4 BH80 ?X t  3 F>6___PPT9 IFortran& " " 5 B030 ?(t X 3 F>6___PPT9 SGenetic algorithm& " " 6 B?0 ?t (3 F>6___PPT9 L 326.gafort& "  "  7 B >0 ?4 t F>6___PPT9 E0((" "  8 BF0 ? 4t F>6___PPT9 E0((" " 9 B0K0 ?  t F>6___PPT9 I60000((" " : B`I0 ? t F>6___PPT9 G101((" " ; BtR0 ?X  t F>6___PPT9 IFortran& " " < BP0 ?( X t F>6___PPT9 RCrash simulation& " " = BY0 ? (t F>6___PPT9 K 328.fma3d& "  " > B]0 ?4 F>6___PPT9 G138((" "  ? Ba0 ?4 F>6___PPT9 E1((" " @ B`0 ?  F>6___PPT9 H1300((" "  A Bh0 ?   F>6___PPT9 E1((" "  B B4m0 ?X  F>6___PPT9 CC& " " C Bdk0 ?(X F>6___PPT9 SImage recognition& " " D Bt0 ?( F>6___PPT9 I330.art& " " E B s0 ?47F>6___PPT9 G101((" "  F Bd|0 ?74F>6___PPT9 E1((" " G B40 ? 7F>6___PPT9 H7500((" "  H B0 ? 7 F>6___PPT9 E1((" " I Bԇ0 ?X 7 F>6___PPT9 IFortran& " " J B0 ?(7X F>6___PPT9 O Air pollution& " " K B0 ?7(F>6___PPT9 K 324.apsi & "  "  L B0 ?4x7F>6___PPT9 E0((" "  M Bt0 ?x47F>6___PPT9 E0((" " N B0 ? x7F>6___PPT9 H4000((" " O B0 ? x 7F>6___PPT9 F20((" " P BT0 ?X x 7F>6___PPT9 IFortran& " " Q B$0 ?(xX 7F>6___PPT9 PFluid dynamics& " " R B0 ?x(7F>6___PPT9 K 316.applu& "  " S B<0 ?4xF>6___PPT9 F29((" "  T Bl0 ?4xF>6___PPT9 E5((" " U BD0 ? xF>6___PPT9 I13500((" " V B0 ?  xF>6___PPT9 F31((" "  W B0 ?X  xF>6___PPT9 DC & " " X B0 ?(X xF>6___PPT9 SChemistry/Biology& " " Y B,0 ?(xF>6___PPT9 J332.ammp& "  " Z B0 ?4F>6___PPT9 F36((" " [ B|0 ?4F>6___PPT9 F12((" " \ B0 ? F>6___PPT9 I35100((" " ] B0 ?  F>6___PPT9 G145((" "  ^ B0 ?X  F>6___PPT9 EC++& " " _ B0 ?(X F>6___PPT9 JGraphics& "  " ` B00 ?(F>6___PPT9 N AMR renderer& "  " a B0 ?4; T  @` b B0 ?;4 T  @` c B0 ? ; T  @` d B2 ? ;  T  @` e B 2 ?X ;  T  @` f B|2 ?(;X  T  @` g B 2 ?;( T  @` h B2 ?4|;F>6___PPT9 ILines((" " i B&2 ?|4;F>6___PPT9 IFiles((" " j B*2 ? |;F>6___PPT9 ILines((" " k B()2 ? | ;F>6___PPT9 IFiles((" " l Bl22 ?X | ;F>6___PPT9 JLanguage& "  " m B02 ?(|X ;F>6___PPT9 RApplication area& " " n B92 ?|(;F>6___PPT9 FCode& " " o B\=2 ?7|F>6___PPT9 LModified( ("  " p B8A2 ? 7|F>6___PPT9 WUnmodified (OpenMP)((" " q BL2 ?X 7 | T  @` r B|U2 ?(7X | T  @` s B|^2 ?7(| T  @`NB t S  77NB u S  44NB v S  74NB w S  74H  0޽h ? 3___PPT10i..@+D=' `= @B +  0 ' 4(  4r 4 S l52 ` `}  2  40 ZA  ?AA ?`0   2 4 <d-2V Q!Copyright 2004 Intel Corporation""  4 BP+2F   Itanium is a registered trademark of Intel Corporation or its subsidiaries in the United States or other countries.v0v H 4 0޽h ? 33___PPT10i.0y+D=' `= @B + 0 y@(    T2gֳgֳ ? /Rendering code on 128 nodes  T2gֳgֳ ?p  NIPF scaling speedup 479 rows.    `gֳgֳA ? ?0|   <<#W 4045=85 ?@>872>48B5;L=>AB8 4;O 64 ?>B>:>2, 2>7<>6=>, >1CA;>2;5=> =54>AB0B>G=K< @07<5@>< 7040G8 (a0_  (=H  0޽h ? 380___PPT10..   0 <(  <r < S D ` `}   r < S ` `   < <ؿV Q!Copyright 2004 Intel Corporation""  < B    Itanium is a registered trademark of Intel Corporation or its subsidiaries in the United States or other countries.v0v H < 0޽h ? 33___PPT10i.։+D=' `= @B +0+# 0 **@*(  X  C    /)  S / 0  / B)'2.1 The OpenMP execution model An OpenMP program executes according to a fork-join model. This means that an OpenMP program begins execution as a single thread, called the master thread, and when a parallel directive is encountered by that thread, execution forks and a region of code is executed in parallel by a team of threads. When the parallel region is finished, the threads in that team join again at an implicit barrier, and the master thread is the only thread that continues execution. This fork-join structure continues in a nested way, if necessary. If a parallel region is currently active and any thread in the team that is executing the parallel region encounters another parallel directive, execution forks again, another team of threads is formed, and those threads execute the new parallel region, then join at its end. OpenMP provides a menu of synchronization constructs: critical sections for mutual exclusion, barriers to hold threads until all in a given team have arrived, atomic constructs to confer atomicity on individual operations, reduction operations, and a way of ordering code sections within a parallel loop. These synchronization operations make it possible to implement most of the desired forms of cooperation between threads. 2.2. The OpenMP Memory Model OpenMP provides a memory for storing variables that is shared by all threads. Each thread reads and writes the shared memory directly, but the memory consistency is relaxed because writes to memory are allowed to overlap other computation. Likewise, under certain circumstances, reads from memory are allowed to be satisfied from a local copy of memory, called the thread s temporary view. Each thread can also create thread-private variables that may not be accessed by any other thread. Every variable used in a parallel region has an original variable by the same name outside the parallel region. A reference inside the parallel construct to a variable, determined to be shared by the parallel directive, is a reference to that variable s original variable. A reference inside the parallel construct to a variable, determined to be private by the parallel directive, is a reference to a variable of the same type and size as the original variable that is private to the thread. The relaxed memory consistency of OpenMP is similar to weak ordering [2,3,4] memory consistency, with the OpenMP flush operation serving as a memory synchronization operation. All reads and writes are unordered and may be overlapped with respect to each other (except those that must be ordered due to data dependence relations or the semantics of the base language). A read or write of a variable is ordered with respect to an OpenMP flush operation for that variable, however. 1: A = 1 . . . 2: Flush(A) A write to the shared variable A may complete as soon as point 1, and as late as point 2. The ordering of memory operations with respect to the flush operation must be obeyed by both the compiler and the machine. In Figure 1 above, the compiler is prohibited from reversing the order of the write to A and the flush(A). In the execution of the program fragment in Figure 1, the value written by the assignment statement at point 1 could complete immediately, but it is also allowed for execution to continue before the write completes. The write is not required to be firmly lodged in memory, available to all other threads, until execution reaches point 2. Future memory operations involving A would not be allowed to start until after the flush(A) completes. The fact that OpenMP allows execution to continue while the write to A is still not complete allows the overlap of a memory write with computation (the  &  in Figure 1). Further, if a read of A occurs within the  &  computation, the OpenMP implementation is allowed to satisfy that read out of some cheap local storage, referred to in the OpenMP version 2.5 specification as the thread s  temporary view , without going all the way to memory. The asynchronous writes, along with the ability to do cheap reads in certain circumstances, make it possible to hide memory latency within an OpenMP program. In order to communicate a value from one thread to another in OpenMP, the value must go through the memory, written by the sending thread, and read by the receiving thread. In addition, a flush operation must be executed on both the sending and receiving threads. Operations must be done in exactly the following order: The value is written to a variable in memory by the sending thread The variable is flushed by the sending thread The variable is flushed by the receiving thread The value is read from the variable by the receiving thread. A flush operation for all visible variables is implied at all barriers, all lock operations, and at entry to and exit from all parallel regions, within an OpenMP program. An atomic construct implies a flush operation for the location involved, both before and after the atomic operation. V P\P@P 9`j -"GZ@ Z!H  0޽h ? 3380___PPT10.0 p~Z<+$ 0 **L*(  ^  S    ")  c $D" 0  " B)'2.1 The OpenMP execution model An OpenMP program executes according to a fork-join model. This means that an OpenMP program begins execution as a single thread, called the master thread, and when a parallel directive is encountered by that thread, execution forks and a region of code is executed in parallel by a team of threads. When the parallel region is finished, the threads in that team join again at an implicit barrier, and the master thread is the only thread that continues execution. This fork-join structure continues in a nested way, if necessary. If a parallel region is currently active and any thread in the team that is executing the parallel region encounters another parallel directive, execution forks again, another team of threads is formed, and those threads execute the new parallel region, then join at its end. OpenMP provides a menu of synchronization constructs: critical sections for mutual exclusion, barriers to hold threads until all in a given team have arrived, atomic constructs to confer atomicity on individual operations, reduction operations, and a way of ordering code sections within a parallel loop. These synchronization operations make it possible to implement most of the desired forms of cooperation between threads. 2.2. The OpenMP Memory Model OpenMP provides a memory for storing variables that is shared by all threads. Each thread reads and writes the shared memory directly, but the memory consistency is relaxed because writes to memory are allowed to overlap other computation. Likewise, under certain circumstances, reads from memory are allowed to be satisfied from a local copy of memory, called the thread s temporary view. Each thread can also create thread-private variables that may not be accessed by any other thread. Every variable used in a parallel region has an original variable by the same name outside the parallel region. A reference inside the parallel construct to a variable, determined to be shared by the parallel directive, is a reference to that variable s original variable. A reference inside the parallel construct to a variable, determined to be private by the parallel directive, is a reference to a variable of the same type and size as the original variable that is private to the thread. The relaxed memory consistency of OpenMP is similar to weak ordering [2,3,4] memory consistency, with the OpenMP flush operation serving as a memory synchronization operation. All reads and writes are unordered and may be overlapped with respect to each other (except those that must be ordered due to data dependence relations or the semantics of the base language). A read or write of a variable is ordered with respect to an OpenMP flush operation for that variable, however. 1: A = 1 . . . 2: Flush(A) A write to the shared variable A may complete as soon as point 1, and as late as point 2. The ordering of memory operations with respect to the flush operation must be obeyed by both the compiler and the machine. In Figure 1 above, the compiler is prohibited from reversing the order of the write to A and the flush(A). In the execution of the program fragment in Figure 1, the value written by the assignment statement at point 1 could complete immediately, but it is also allowed for execution to continue before the write completes. The write is not required to be firmly lodged in memory, available to all other threads, until execution reaches point 2. Future memory operations involving A would not be allowed to start until after the flush(A) completes. The fact that OpenMP allows execution to continue while the write to A is still not complete allows the overlap of a memory write with computation (the  &  in Figure 1). Further, if a read of A occurs within the  &  computation, the OpenMP implementation is allowed to satisfy that read out of some cheap local storage, referred to in the OpenMP version 2.5 specification as the thread s  temporary view , without going all the way to memory. The asynchronous writes, along with the ability to do cheap reads in certain circumstances, make it possible to hide memory latency within an OpenMP program. In order to communicate a value from one thread to another in OpenMP, the value must go through the memory, written by the sending thread, and read by the receiving thread. In addition, a flush operation must be executed on both the sending and receiving threads. Operations must be done in exactly the following order: The value is written to a variable in memory by the sending thread The variable is flushed by the sending thread The variable is flushed by the receiving thread The value is read from the variable by the receiving thread. A flush operation for all visible variables is implied at all barriers, all lock operations, and at entry to and exit from all parallel regions, within an OpenMP program. An atomic construct implies a flush operation for the location involved, both before and after the atomic operation. V P\P@P 9`j -"GZ@ Z!H  0޽h ? 3380___PPT10.0 p~Z<+% 0 **L*(  ^  S    1)  c $1 0  1 B)'2.1 The OpenMP execution model An OpenMP program executes according to a fork-join model. This means that an OpenMP program begins execution as a single thread, called the master thread, and when a parallel directive is encountered by that thread, execution forks and a region of code is executed in parallel by a team of threads. When the parallel region is finished, the threads in that team join again at an implicit barrier, and the master thread is the only thread that continues execution. This fork-join structure continues in a nested way, if necessary. If a parallel region is currently active and any thread in the team that is executing the parallel region encounters another parallel directive, execution forks again, another team of threads is formed, and those threads execute the new parallel region, then join at its end. OpenMP provides a menu of synchronization constructs: critical sections for mutual exclusion, barriers to hold threads until all in a given team have arrived, atomic constructs to confer atomicity on individual operations, reduction operations, and a way of ordering code sections within a parallel loop. These synchronization operations make it possible to implement most of the desired forms of cooperation between threads. 2.2. The OpenMP Memory Model OpenMP provides a memory for storing variables that is shared by all threads. Each thread reads and writes the shared memory directly, but the memory consistency is relaxed because writes to memory are allowed to overlap other computation. Likewise, under certain circumstances, reads from memory are allowed to be satisfied from a local copy of memory, called the thread s temporary view. Each thread can also create thread-private variables that may not be accessed by any other thread. Every variable used in a parallel region has an original variable by the same name outside the parallel region. A reference inside the parallel construct to a variable, determined to be shared by the parallel directive, is a reference to that variable s original variable. A reference inside the parallel construct to a variable, determined to be private by the parallel directive, is a reference to a variable of the same type and size as the original variable that is private to the thread. The relaxed memory consistency of OpenMP is similar to weak ordering [2,3,4] memory consistency, with the OpenMP flush operation serving as a memory synchronization operation. All reads and writes are unordered and may be overlapped with respect to each other (except those that must be ordered due to data dependence relations or the semantics of the base language). A read or write of a variable is ordered with respect to an OpenMP flush operation for that variable, however. 1: A = 1 . . . 2: Flush(A) A write to the shared variable A may complete as soon as point 1, and as late as point 2. The ordering of memory operations with respect to the flush operation must be obeyed by both the compiler and the machine. In Figure 1 above, the compiler is prohibited from reversing the order of the write to A and the flush(A). In the execution of the program fragment in Figure 1, the value written by the assignment statement at point 1 could complete immediately, but it is also allowed for execution to continue before the write completes. The write is not required to be firmly lodged in memory, available to all other threads, until execution reaches point 2. Future memory operations involving A would not be allowed to start until after the flush(A) completes. The fact that OpenMP allows execution to continue while the write to A is still not complete allows the overlap of a memory write with computation (the  &  in Figure 1). Further, if a read of A occurs within the  &  computation, the OpenMP implementation is allowed to satisfy that read out of some cheap local storage, referred to in the OpenMP version 2.5 specification as the thread s  temporary view , without going all the way to memory. The asynchronous writes, along with the ability to do cheap reads in certain circumstances, make it possible to hide memory latency within an OpenMP program. In order to communicate a value from one thread to another in OpenMP, the value must go through the memory, written by the sending thread, and read by the receiving thread. In addition, a flush operation must be executed on both the sending and receiving threads. Operations must be done in exactly the following order: The value is written to a variable in memory by the sending thread The variable is flushed by the sending thread The variable is flushed by the receiving thread The value is read from the variable by the receiving thread. A flush operation for all visible variables is implied at all barriers, all lock operations, and at entry to and exit from all parallel regions, within an OpenMP program. An atomic construct implies a flush operation for the location involved, both before and after the atomic operation. V P\P@P 9`j -"GZ@ Z!H  0޽h ? 3380___PPT10.0 p~Z? 0 O(  X  C    :  S 0: 0  : Q!A flush operation for all visible variables is implied at all barriers, all lock operations, and at entry to and exit from all parallel regions, within an OpenMP program. An atomic construct implies a flush operation for the location involved, both before and after the atomic operation.  H  0޽h ? 3380___PPT10.7 м0 0 &(  X  C    :  S w: 0  : (3.2 The DSM mechanism The task of keeping sharable variables consistent across distributed nodes is handled by the Cluster OMP run-time library. Sharable variables are grouped together on certain pages in memory. The basic mechanism relies on protecting memory pages with an mprotect system call. When a particular page is not fully up-to-date, the page is protected against reading and writing. Then, when the program reads from the page, a segmentation fault occurs, and a SIGSEGV is delivered to the Cluster OMP software, which requests updates from all nodes that have modified the page since it was last brought up to date. The updates from each modifying node are applied to the page, the page protection against reading is removed, and the instruction is restarted. This time, the instruction finds the memory accessible, and the read completes successfully. At this point, the page is still protected against writing, so that the Cluster OMP software can trap any modification to the page. When the next write to the page happens, again a segmentation fault occurs and is delivered to Cluster OMP. Since the page is being modified, Cluster OMP first makes a copy of the page (called a  twin ), and then removes all protection from the page. The twin makes it possible to later determine all changes that have been made to the page by noticing the differences between the twin (original pristine copy) and the page at that moment. At the next synchronization operation, the node will receive notice of all the pages that other nodes have modified, causing all of those pages to be protected against reading and writing again. After the twin is made, further reads and writes on the page, prior to the next synchronization, happen without engaging the Cluster OMP software at all. This makes all of these reads and writes extremely cheap compared to the cost of those that cause the page to be brought up to date and cause the twin to be made. So, the higher the ratio of cheap memory accesses to expensive accesses, the better the program will perform. Again, the use of the cheap memory accesses is allowed by the relaxed memory consistency of the OpenMP memory model. The local memory of a node serves as the  temporary view for each thread. "Z  &H  0޽h ? 3380___PPT10. ox=`TŶsw7@\@:J$y`I6d%dcvCY{{yʳbxO îXϞΙwلMgΜ9ΙrxwpavkkٴTAvpk(_Zżg*෉2VWF BX^CZ$=귒M٫+\-e)K7^̦Di$`2fBHR$ )xb_\P  W1a[4~d(_~*u@o9 +{n.i`?c=%KH`ibe2. do6p .\Op.\Bp}Gyc pnJ+7`pC 7 ppn$Q7a eƂs+7xpMdN7Tp;4p7\#W lpsk; |p n!E\eP K1^OVb˨ /Fpǂk n9V|Dp';j",3l Xk ç;iւ;w 9ww.w]Rpw]Zpmw nwMnw [vpw]w}6'=Ap{#඀{TcVpm{Sipπ{s ^v{k^7mp{Np{܇B~? 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