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search.json

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     "href": "src/exercice.html#exercice",
     "title": "Conclusion",
     "section": "Exercice",
-    "text": "Exercice\nOn veut paralléliser l’exemple suivant avec Rmpi que j’ai trouvé ici\n# File name: loop_rowSums.r\n\nmy.loop <- 20\nm.dim <- list(nrow = 200000, ncol = 10)\nm <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol)\nret <- 0\n\nstart <- Sys.time()\nfor(k in 1 : my.loop){\n  ret <- ret + sum(rowSums(m))\n}\ncat(ret, \"\\n\")\nSys.time() - start\n\nVoici la version MPMD venant de la même source, essayer d’en faire une version SPMD et comparer les performances.\n\nPouvez-vous réduire le nombre de messages ?\nVotre code est-il plus conçis ?\n\n# File name: rmpi_rowSums.r\n\nloop.fun <- function(){\n  ##\n  # Modify from loop_rowSums.r\n  ##\n  m.dim <- list(nrow = 200000, ncol = 10)\n  m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol)\n\n  ret <- sum(rowSums(m))\n}\n\ncall.mpi.master <- function(){\n  library(Rmpi)\n  mpi.spawn.Rslaves(nslaves= 4, needlog = FALSE)\n  mpi.bcast.Robj2slave(call.mpi.slave)\n  mpi.bcast.cmd(call.mpi.slave())\n  mpi.bcast.Robj(loop.fun)\n\n  my.size <- mpi.universe.size()\n  my.loop <- 20 \n  my.split <- data.frame(loop = 1 : my.loop,\n                         rank = sort(c(rep(1 : my.size, my.loop %/% my.size),\n                                if(my.loop %% my.size > 0)\n                                (my.size : 2)[1 : (my.loop %% my.size)])))\n\n  for(i in 1 : my.size){\n    mpi.send.Robj(my.split$loop[my.split$rank == i], dest = i, tag = 1)\n  }\n\n  ret <- 0\n  for(i in 1 : my.size){\n    ret <- ret + mpi.recv(integer(1), type = 1, source = i, tag = 2)\n  }\n  ret\n}\n\ncall.mpi.slave <- function(){\n  loop.fun <- eval(mpi.bcast.Robj())\n  my.loop <- mpi.recv.Robj(source = 0, tag = 1)\n\n  ret <- 0\n  for(i in my.loop){\n    ret <- ret + loop.fun()\n  }\n  mpi.send(as.integer(ret), type = 1, dest = 0, tag = 2)\n}\n\nstart <- Sys.time()\ncall.mpi.master()\nSys.time() - start"
+    "text": "Exercice\nOn veut paralléliser l’exemple suivant avec Rmpi que j’ai trouvé ici\n# File name: loop_rowSums.r\n\nmy.loop <- 20\nm.dim <- list(nrow = 200000, ncol = 10)\nm <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol)\nret <- 0\n\nstart <- Sys.time()\nfor(k in 1 : my.loop){\n  ret <- ret + sum(rowSums(m))\n}\ncat(ret, \"\\n\")\nSys.time() - start\n\nVoici la version MPMD venant de la même source, essayer d’en faire une version SPMD et comparer les performances.\n\nPouvez-vous réduire le nombre de messages ?\nVotre code est-il plus conçis ?\n\n# File name: rmpi_rowSums.r\n\nloop.fun <- function(){\n  m.dim <- list(nrow = 200000, ncol = 10)\n  m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol)\n\n  ret <- sum(rowSums(m))\n}\n\ncall.mpi.master <- function(){\n  library(Rmpi)\n  mpi.spawn.Rslaves(nslaves= 4, needlog = FALSE)\n  mpi.bcast.Robj2slave(call.mpi.slave)\n  mpi.bcast.cmd(call.mpi.slave())\n  mpi.bcast.Robj(loop.fun)\n\n  my.size <- mpi.universe.size()\n  my.loop <- 20 \n  my.split <- data.frame(loop = 1 : my.loop,\n                         rank = sort(c(rep(1 : my.size, my.loop %/% my.size),\n                                if(my.loop %% my.size > 0)\n                                (my.size : 2)[1 : (my.loop %% my.size)])))\n\n  for(i in 1 : my.size){\n    mpi.send.Robj(my.split$loop[my.split$rank == i], dest = i, tag = 1)\n  }\n\n  ret <- 0\n  for(i in 1 : my.size){\n    ret <- ret + mpi.recv(integer(1), type = 1, source = i, tag = 2)\n  }\n  ret\n}\n\ncall.mpi.slave <- function(){\n  loop.fun <- eval(mpi.bcast.Robj())\n  my.loop <- mpi.recv.Robj(source = 0, tag = 1)\n\n  ret <- 0\n  for(i in my.loop){\n    ret <- ret + loop.fun()\n  }\n  mpi.send(as.integer(ret), type = 1, dest = 0, tag = 2)\n}\n\nstart <- Sys.time()\ncall.mpi.master()\nSys.time() - start"
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     "href": "src/exercice.html#solution",
     "title": "Conclusion",
     "section": "Solution",
-    "text": "Solution\nlibrary(Rmpi)\n\nloop.fun <- function(){\n  m.dim <- list(nrow = 200000, ncol = 10)\n  m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol)\n  ret <- sum(rowSums(m))\n}\n\nmy.rank <- mpi.comm.rank(comm=0)\nmy.size <- mpi.comm.size(comm=0)\n\nmy.loop <- 20 \nmy.split <- .splitIndices(my.loop, my.size)\n\nmy.loop <- unlist(my.split[my.rank+1])\n\nret <- 0\nfor(i in my.loop){\n    ret <- ret + loop.fun()\n}\n\nres <- mpi.reduce(as.integer(ret), type = 1, op = \"sum\", dest = 0, comm = 0)\n \nif (my.rank == 0 ) { cat(\"\\n\", res, \"\\n\") }\n\ninvisible(mpi.barrier(comm=0))\ninvisible(mpi.finalize())"
+    "text": "Solution\nlibrary(Rmpi)\n\nloop.fun <- function(){\n  m.dim <- list(nrow = 200000, ncol = 10)\n  m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol)\n  ret <- sum(rowSums(m))\n}\n\nmy.rank <- mpi.comm.rank(comm=0)\nmy.size <- mpi.comm.size(comm=0)\n\nmy.loop <- 20 \nmy.split <- .splitIndices(my.loop, my.size)\nmy.loop <- unlist(my.split[my.rank+1])\n\nret <- 0\nfor(i in my.loop){\n    ret <- ret + loop.fun()\n}\n\nres <- mpi.reduce(as.integer(ret), type = 1, op = \"sum\", dest = 0, comm = 0)\n \nif (my.rank == 0 ) { cat(\"\\n res = \", res, \"\\n\") }\n\ninvisible(mpi.barrier(comm=0))\ninvisible(mpi.finalize())"
   },
   {
     "objectID": "src/index.html",

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