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Parallel Programming in MPI part 2

Parallel Programming in MPI part 2. 1. Today's Topic. ノンブロッキング通信 Non-Blocking Communication 通信の完了を待つ間に他の処理を行う Execute other instructions while waiting for the completion of a communication. 集団通信関数の実装 Implementation of collective communications

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Parallel Programming in MPI part 2

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  1. Parallel Programming in MPIpart 2 1

  2. Today's Topic ノンブロッキング通信Non-Blocking Communication 通信の完了を待つ間に他の処理を行うExecute other instructions while waiting for the completion of a communication. 集団通信関数の実装 Implementation of collective communications MPIプログラムの時間計測Measuring execution time of MPI programs デッドロック Deadlock

  3. Today's Topic ノンブロッキング通信Non-Blocking Communication 通信の完了を待つ間に他の処理を行うExecute other instructions while waiting for the completion of a communication. 集団通信関数の実装 Implementation of collective communications MPIプログラムの時間計測Measuring execution time of MPI programs デッドロック Deadlock

  4. ノンブロッキング通信関数 Non-blocking communication functions • ノンブロッキング = ある命令の完了を待たずに次の命令に移るNon-blocking = Do not wait for the completion of an instruction and proceed to the next instruction • Example) MPI_Irecv& MPI_Wait Blocking Non-Blocking MPI_Recv MPI_Irecv Proceed to the next instruction without waiting for the data next instructions Wait for the arrival of data data data MPI_Wait next instructions

  5. MPI_Irecv Usage: int MPI_Irecv(void *b, int c, MPI_Datatype d, int src, int t, MPI_Comm comm, MPI_Request *r); • Non-Blocking Receive • Parameters:start address for storing received data,number of elements, data type,rank of the source, tag (= 0, in most cases), communicator (= MPI_COMM_WORLD, in most cases),request • request: 通信要求 Communication Request • この通信の完了を待つ際に用いるUsed for Waiting completion of this communication • Example)MPI_Requestreq; ...MPI_Irecv(a, 100, MPI_INT, 0, 0, MPI_COMM_WORLD, &req); ...MPI_Wait(&req, &status); 5 5

  6. MPI_Isend Usage: int MPI_Isend(void *b, int c, MPI_Datatype d, int dest,int t, MPI_Comm comm, MPI_Request *r); • Non-Blocking Send • Parameters:start address for sending data,number of elements, data type,rank of the destination, tag (= 0, in most cases), communicator (= MPI_COMM_WORLD, in most cases),request • Example)MPI_Requestreq; ...MPI_Isend(a, 100, MPI_INT, 1, 0, MPI_COMM_WORLD, &req); ...MPI_Wait(&req, &status); 6 6

  7. Non-Blocking Send? • Blocking send (MPI_Send):送信データが別の場所にコピーされるのを待つ Wait for the data to be copied to somewhere else. • ネットワークにデータを送出し終わるか、一時的にデータのコピーを作成するまで。Until completion of the data to be transferred to the network or, until completion of the data to be copied to a temporal memory. • Non-Blocking send (MPI_Recv):待たない

  8. Notice: ノンブロッキング通信中はデータが不定Data is not sure in non-blocking communications • MPI_Irecv: • 受信データの格納場所と指定した変数の値は MPI_Waitまで不定Value of the variable specified for receiving data is not fixed before MPI_Wait A arriveddata MPI_Irecvto A 10 ... ~ = A ... A 50 Value of A at herecan be 10 or 50 50 MPI_Wait Value of A is 50 ~ = A

  9. Notice: ノンブロッキング通信中はデータが不定Data is not sure in non-blocking communications • MPI_Isend: • 送信データを格納した変数を MPI_Waitより前に書き換えると、実際に送信される値は不定If the variable that stored the data to be sent is modified before MPI_Wait, the value to be actually sent is unpredictable. A MPI_Isend A Modifying value of A here causes incorrect communication 10 data sent ... A = 50 ... A 10 or 50 50 MPI_Wait You can modify value of A at here without any problem A = 100

  10. MPI_Wait Usage: int MPI_Wait(MPI_Request *req, MPI_Status *stat); • ノンブロッキング通信（MPI_Isend、MPI_Irecv）の完了を待つ。Wait for the completion of MPI_Isend or MPI_Irecv • 送信データの書き換えや受信データの参照が行えるMake sure that sending data can be modified,or receiving data can be referred. • Parameters:request, status • status:MPI_Irecv完了時に受信データの statusを格納The status of the received data is stored at the completion of MPI_Irecv

  11. MPI_Waitall Usage: int MPI_Waitall(int c, MPI_Request *requests, MPI_Status *statuses); • 指定した数のノンブロッキング通信の完了を待つWait for the completion of specified number of non-blocking communications • Parameters:count, requests, statuses • count:ノンブロッキング通信の数The number of non-blocking communications • requests, statuses:少なくとも count個の要素を持つ MPI_Requestと MPI_Statusの配列Arrays of MPI_Request or MPI_Status that consists at least 'count' number of elements.

  12. Today's Topic ノンブロッキング通信Non-Blocking Communication 通信の完了を待つ間に他の処理を行うExecute other instructions while waiting for the completion of a communication. 集団通信関数の実装 Implementation of collective communications MPIプログラムの時間計測Measuring execution time of MPI programs デッドロック Deadlock

  13. 集団通信関数の中身Inside ofthe functions of collective communications • 通常，集団通信関数は，MPI_Send, MPI_Recv, MPI_Isend, MPI_Irecv等の一対一通信で実装されるUsually, functions of collective communications are implemented by using message passing functions.

  14. Inside of MPI_Bcast int MPI_Bcast(char *a, int c, MPI_Datatype d, int root, MPI_Comm comm) { int i, myid, procs; MPI_Status st; MPI_Comm_rank(comm, &myid); MPI_Comm_rank(comm, &procs); if (myid == root){ for (i = 0; i < procs) if (i != root) MPI_Send(a, c, d, i, 0, comm); } else{ MPI_Recv(a, c, d, root, 0, comm, &st); } return 0; } • One of the most simple implementations

  15. Another implementation: With MPI_Isend int MPI_Bcast(char *a, int c, MPI_Datatype d, int root, MPI_Comm comm) { int i, myid, procs, cntr; MPI_Status st, *stats; MPI_Request *reqs; MPI_Comm_rank(comm, &myid); MPI_Comm_rank(comm, &procs); if (myid == root){ stats = (MPI_Status *)malloc(sizeof(MPI_Status)*procs); reqs = (MPI_Request *)malloc(sizeof(MPI_Request)*procs); cntr = 0; for (i = 0; i < procs) if (i != root) MPI_Isend(a, c, d, i, 0, comm, &(reqs[cntr++])); MPI_Waitall(procs-1, reqs, stats); free(stats); free(reqs); } else{ MPI_Recv(a, c, d, root, 0, comm, &st); } return 0; }

  16. Another implementation: Binomial Tree int MPI_Bcast(char *a, int c, MPI_Datatype d, int root, MPI_Comm comm) { int i, myid, procs; MPI_Status st; int mask, relative_rank, src, dst; int tag = 1, success = 0; MPI_Comm_rank(comm, &myid); MPI_Comm_rank(comm, &procs); relative_rank = myid - root; if (relative_rank < 0) relative_rank += procs; mask = 1; while (mask < num_procs){ if (relative_rank & mask){ src = myid - mask; if (src < 0) src += procs; MPI_Recv(a, c, d, src, 0, comm, &st); break; } mask <<= 1; } mask >>= 1; while (mask > 0){ if (relative_rank + mask < procs){ dst = myid + mask; if (dst >= procs) dst -= procs; MPI_Send (a, c, d, dst, 0, comm); } mask >>= 1; } return 0; }

  17. Flow of Binomial Tree • Use 'mask' to determine when and how to Send/Recv Rank 0 Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Rank 6 Rank 7 mask = 1 mask = 1 mask = 1 mask = 1 mask = 1 mask = 1 mask = 1 mask = 1 mask = 2 mask = 2 mask = 2 mask = 2 Recv from 6 Recv from 4 Recv from 0 Recv from 2 mask = 4 mask = 4 Recv from 4 Recv from 0 Recv from 0 mask = 4 Send to 4 mask = 2 Send to 6 mask = 2 mask = 1 mask = 1 Send to 2 Send to 5 Send to 7 mask = 1 Send to 3 mask = 1 Send to 1

  18. Today's Topic ノンブロッキング通信Non-Blocking Communication 通信の完了を待つ間に他の処理を行うExecute other instructions while waiting for the completion of a communication. 集団通信関数の実装 Implementation of collective communications MPIプログラムの時間計測Measuring execution time of MPI programs デッドロック Deadlock

  19. MPIプログラムの時間計測 Measure the time of MPI programs MPI_Wtime 現在時間（秒）を実数で返す関数 Returns the current time in seconds. Example) ... double t1, t2; ... t1 = MPI_Wtime(); 　　処理 t2 = MPI_Wtime(); printf("Elapsed time: %e sec.\n", t2 – t1); Measuretime here

  20. 並列プログラムにおける時間計測の問題Problem on measuring time in parallel programs Rank 0 Rank 1 t1 = MPI_Wtime(); Rank 2 Read t1 = MPI_Wtime(); Measuretime here Read t1 = MPI_Wtime(); Receive Send Receive Read t1 = MPI_Wtime(); Send t1 = MPI_Wtime(); t1 = MPI_Wtime(); プロセス毎に違う時間を測定：　どの時間が本当の所要時間か?Each process measures different time. Which time is the time we want? 20

  21. 集団通信 MPI_Barrierを使った解決策 Use MPI_Barrier Rank 0 MPI_Barrier Rank 1 MPI_Barrier Rank 2 MPI_Barrier t1 = MPI_Wtime(); Receive Receive Read Measuretime here Read Send MPI_Barrier Read Send MPI_Barrier MPI_Barrier t1 = MPI_Wtime(); • 時間計測前にMPI_Barrierで同期 Synchronize processes before each measurement • For measuring total execution time. 21

  22. より細かい解析 Detailed analysis • Average • MPI_Reduce can be used to achieve the average: • MAX and MIN • Use MPI_Gather to gather all of the results to Rank 0. • Let Rank 0 to find MAX and MIN double t1, t2, t, total; t1 = MPI_Wtime(); ... t2 = MPI_Wtime(); t = t2 – t1; MPI_Reduce(&t, &total, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD); if (myrank == 0) printf("Ave. elapsed: %e sec.\n", total/procs);

  23. 最大(Max)、平均(Ave)、最小(Min)の関係 Relationships among Max, Ave and Min • プロセス毎の負荷（仕事量）のばらつき検証に利用 Can be used for checking the load-balance. Time includes Computation Time and Communication Time

  24. 通信時間の計測 Measuring time for communications double t1, t2, t3, t4 comm=0; t3 = MPI_Wtime(); for (i = 0; i < N; i++){computation t1 = MPI_Wtime();communication t2 = MPI_Wtime(); comm += t2 – t1; computation t1 = MPI_Wtime();communication t2 = MPI_Wtime(); comm += t2 – t1; } t4 = MPI_Wtime();

  25. Analyze computation time • Computation time = Total time - Communication time • Or, just measure the computation time • 計算時間のばらつき　＝　負荷の不均衡の度合いBalance of computation time shows balance of the amount of computation • 注意:　通信時間には、負荷の不均衡によって生じた待ち時間が含まれるので、単純な評価は難しい Communication time is difficult to analyze since it consists waiting time caused by load-imbalance. ==> Balance computation first.

  26. Today's Topic ノンブロッキング通信Non-Blocking Communication 通信の完了を待つ間に他の処理を行うExecute other instructions while waiting for the completion of a communication. 集団通信関数の実装 Implementation of collective communications MPIプログラムの時間計測Measuring execution time of MPI programs デッドロック Deadlock

  27. Deadlock 何らかの理由で、プログラムを進行させることができなくなった状態A status of a program in which it cannot proceed by some reasons. MPIプログラムでデッドロックが発生しやすい場所：Places you need to be careful for deadlocks:1. MPI_Recv, MPI_Wait, MPI_Waitall 2. Collective communications 　全部のプロセスが同じ集団通信関数を実行するまで先に進めないA program cannot proceed until all processes call the same collective communication function Wrong case: One solution: use MPI_Irecv if (myid == 0){ MPI_Recv from rank 1 MPI_Send to rank 1 } if (myid == 1){ MPI_Recv from rank 0 MPI_Send to rank 0 } if (myid == 0){ MPI_Irecv from rank 1 MPI_Send to rank 1 MPI_Wait } if (myid == 1){ MPI_Irecv from rank 0 MPI_Send to rank 0 MPI_Wait }

  28. Summary • 並列プログラムの作成には，　計算の分割，データの分割，通信が必要Parallel programs need distribution of computation, distribution of data and communications. • 並列化で必ず高速化できるとは限らないParallelization does not always speed up programs. • 並列化出来ないプログラムがあるThere are non-parallelizable programs • 並列プログラムではデッドロックに注意Be careful about deadlocks.

  29. Report) Make Reduce function by yourself • 次のページのプログラムの my_reduce関数の中身を追加してプログラムを完成させるFill the inside of 'my_reduce' function in the programshown in the next slide • my_reduce: MPI_Reduceの簡略版 Simplified version of MPI_Reduce • 整数の総和のみ. ルートランクは 0限定．コミュニケータは MPI_COMM_WORLDCalculates total sum of integer numbers. The root rank is always 0.The communicator is always MPI_COMM_WORLD. • アルゴリズムは好きなものを考えてよいAny algorithm is OK.

  30. #include <stdio.h> #include <stdlib.h> #include "mpi.h" #define N 20 int my_reduce(int *a, int *b, int c) { return 0; } int main(int argc, char *argv[]) { int i, myid, procs; int a[N], b[N]; MPI_Init(&argc, &argv); MPI_Comm_rank(MPI_COMM_WORLD, &myid); MPI_Comm_size(MPI_COMM_WORLD, &procs); for (i = 0; i < N; i++){ a[i] = i; b[i] = 0; } my_reduce(a, b, N); if (myid == 0) for (i = 0; i < N; i++) printf("b[%d] = %d , correct answer = %d\n", i, b[i], i*procs); MPI_Finalize(); return 0; } complete here by yourself

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