/*public static void Read_matrix(int[] local_mat, int n, int procid, int numproc, Intracommunicator comm)
* {
* int i, j;
* int[] temp_mat = new int[40];
* int num;
* if (procid == 0)
* {
*
* for (i = 0; i < n; i++)
* for (j = 0; j < n; j++)
* {
* num = i * n + j;
* temp_mat[num] = Convert.ToInt32(Console.ReadLine());
* }
* comm.Scatter<int>(temp_mat);
* //free(temp_mat);
* }
* else
* {
* comm.Scatter<int>(temp_mat);
* }
*
* }*/
public static void Print_matrix(int[] local_mat, int n, int procid, int numproc, Intracommunicator comm)
{
int i, j;
int[] temp_mat = new int[40];
if (procid == 0)
{
temp_mat = comm.Gather <int>(n, 0);
for (i = 0; i < n; i++)
{
for (j = 0; j < n; j++)
{
if (temp_mat[i * n + j] == INF)
{
Console.WriteLine("inf ");
}
else
{
Console.WriteLine(temp_mat[i * n + j]);
}
}
Console.WriteLine("\n");
}
temp_mat = null;
}
else
{
temp_mat = comm.Gather <int>(numproc, 0);
}
}
public static void FloydWarshall(int[,] graph, int verticesCount, int rank, int ntasks, Intracommunicator comm)
{
int[,] distance = new int[verticesCount, verticesCount];
for (int i = rank; i < verticesCount; i += ntasks)
{
for (int j = 0; j < verticesCount; ++j)
{
distance[i, j] = graph[i, j];
}
}
for (int k = 0; k < verticesCount; ++k)
{
for (int i = rank; i < verticesCount; i += ntasks)
{
for (int j = 0; j < verticesCount; ++j)
{
if (distance[i, k] + distance[k, j] < distance[i, j])
{
distance[i, j] = distance[i, k] + distance[k, j];
}
}
}
}
comm.Gather <int[, ]>(distance, 0);
Print(distance, verticesCount, rank);
}
public static int[] SimpleParallel(Intracommunicator communicator, int[] p1, int[] p2)
{
var perProcess = p1.Length / communicator.Size;
var start = communicator.Rank * perProcess;
if (communicator.Rank == communicator.Size - 1)
{
perProcess += p1.Length % communicator.Size;
}
var result = new int[p1.Length + p2.Length - 1];
for (var offset = 0; offset < perProcess; offset++)
{
var i = start + offset;
for (var j = 0; j < p2.Length; j++)
{
result[i + j] += p1[i] * p2[j];
}
}
var results = communicator.Gather(result, 0);
if (communicator.Rank == 0)
{
return(results.Aggregate(new int[p1.Length + p2.Length - 1], Add).ToArray());
}
return(null);
}
public static void FloydWarshall(int[,] graph, int verticesCount, int procid, int numproc, Intracommunicator comm)
{
int[,] distance = new int[verticesCount, verticesCount];
int size = 4 / numproc;
int start = procid * size;
int finish = (procid + 1) * size;
//Console.WriteLine("here");
// Console.WriteLine("procid = "+procid);
for (k = 0; k < verticesCount; k++)
{
Communicator.world.Barrier();
for (int i = start; i < finish; ++i)
{
for (int j = 0; j < verticesCount; ++j)
{
//Console.WriteLine("line "+i+" for procid "+procid);
//Console.WriteLine("procid = " + procid);
distance[i, j] = graph[i, j];
//Console.WriteLine("graph[" + i + ", " + j + "] = " + graph[i, j]);
}
}
}
for (k = 0; k < verticesCount; k++)
{
for (int i = start; i < finish; ++i)
{
for (int j = 0; j < verticesCount; ++j)
{
if (distance[i, k] + distance[k, j] < distance[i, j])
{
distance[i, j] = distance[i, k] + distance[k, j];
}
//Console.WriteLine("min distance["+i+", "+j+"] = "+ distance[i, j]);
}
}
}
comm.Gather <int[, ]>(distance, 0);
Print(distance, verticesCount, procid);
}
/// <summary>
/// Calculates the catchment result counts for each catchment coordinator.
/// This is required so that the coordinator knows how many results to expect from
/// each process in the GatherFlattened call that accumulates the gridded results.
/// </summary>
private void CalculateCatchmentResultCounts()
{
if (IsSlave)
{
Log.DebugFormat("Rank {0}: Calculating catchment result counts", WorldRank);
// Count how many cells I have for each catchment
Dictionary <string, int> myResultsPerCatchment = new Dictionary <string, int>(MyWork.Catchments.Count);
foreach (CellDefinition cell in MyWork.Cells)
{
if (myResultsPerCatchment.ContainsKey(cell.CatchmentId))
{
myResultsPerCatchment[cell.CatchmentId]++;
}
else
{
myResultsPerCatchment.Add(cell.CatchmentId, 1);
}
}
// Gather all the individual result counts into the coordinators
foreach (CatchmentDefinition catchment in MyWork.Catchments)
{
Intracommunicator comm = communicatorsByCatchmentId[catchment.Id];
int[] resultsPerRank = comm.Gather(myResultsPerCatchment[catchment.Id], 0);
if (comm.Rank == 0)
{
// Count how many catchments this process is coordinating
CatchmentCoordinatorCount++;
// Lazy creation of the dictionary. We don't know if the current
// process needs one of these or not until this point
if (CatchmentResultCountPerCatchmentCommunicator == null)
{
CatchmentResultCountPerCatchmentCommunicator = new Dictionary <string, int[]>(comm.Size);
}
// Store the result counts
CatchmentResultCountPerCatchmentCommunicator.Add(catchment.Id, resultsPerRank);
}
}
}
}
static void Main(string[] args)
{
using (new MPI.Environment(ref args))
{
Intracommunicator comm = Communicator.world;
Random rand = new Random();
int[] randomNums = comm.Gather(rand.Next(1, 1001), 0);
if (comm.Rank == 0)
{
Array.Sort(randomNums);
foreach (int num in randomNums)
{
Console.WriteLine(num);
}
}
}
}
public static float[,] Reconstruct(Intracommunicator comm, DistributedData.LocalDataset local, GriddingConstants c, int maxCycle, float lambda, float alpha, int iterPerCycle = 1000, bool usePathDeconvolution = false)
{
var watchTotal = new Stopwatch();
var watchForward = new Stopwatch();
var watchBackward = new Stopwatch();
var watchDeconv = new Stopwatch();
watchTotal.Start();
var metadata = Partitioner.CreatePartition(c, local.UVW, local.Frequencies);
var patchSize = CalculateLocalImageSection(comm.Rank, comm.Size, c.GridSize, c.GridSize);
var totalSize = new Rectangle(0, 0, c.GridSize, c.GridSize);
//calculate psf and prepare for correlation in the Fourier space
var psf = CalculatePSF(comm, c, metadata, local.UVW, local.Flags, local.Frequencies);
Complex[,] PsfCorrelation = null;
var maxSidelobe = PSF.CalcMaxSidelobe(psf);
lambda = (float)(lambda * PSF.CalcMaxLipschitz(psf));
StreamWriter writer = null;
if (comm.Rank == 0)
{
FitsIO.Write(psf, "psf.fits");
Console.WriteLine("done PSF gridding ");
PsfCorrelation = PSF.CalcPaddedFourierCorrelation(psf, totalSize);
writer = new StreamWriter(comm.Size + "runtimestats.txt");
}
var deconvovler = new MPIGreedyCD(comm, totalSize, patchSize, psf);
var residualVis = local.Visibilities;
var xLocal = new float[patchSize.YEnd - patchSize.Y, patchSize.XEnd - patchSize.X];
for (int cycle = 0; cycle < maxCycle; cycle++)
{
if (comm.Rank == 0)
{
Console.WriteLine("cycle " + cycle);
}
var dirtyImage = ForwardCalculateB(comm, c, metadata, residualVis, local.UVW, local.Frequencies, PsfCorrelation, psf, maxSidelobe, watchForward);
var bLocal = GetImgSection(dirtyImage.Image, patchSize);
MPIGreedyCD.Statistics lastRun;
if (usePathDeconvolution)
{
var currentLambda = Math.Max(1.0f / alpha * dirtyImage.MaxSidelobeLevel, lambda);
lastRun = deconvovler.DeconvolvePath(xLocal, bLocal, currentLambda, 4.0f, alpha, 5, iterPerCycle, 2e-5f);
}
else
{
lastRun = deconvovler.Deconvolve(xLocal, bLocal, lambda, alpha, iterPerCycle, 1e-5f);
}
if (comm.Rank == 0)
{
WriteToFile(cycle, lastRun, writer);
if (lastRun.Converged)
{
Console.WriteLine("-----------------------------CONVERGED!!!!------------------------");
}
else
{
Console.WriteLine("-------------------------------not converged----------------------");
}
}
comm.Barrier();
if (comm.Rank == 0)
{
watchDeconv.Stop();
}
float[][,] totalX = null;
comm.Gather(xLocal, 0, ref totalX);
Complex[,] modelGrid = null;
if (comm.Rank == 0)
{
watchBackward.Start();
var x = new float[c.GridSize, c.GridSize];
StitchImage(totalX, x, comm.Size);
FitsIO.Write(x, "xImage_" + cycle + ".fits");
FFT.Shift(x);
modelGrid = FFT.Forward(x);
}
comm.Broadcast(ref modelGrid, 0);
var modelVis = IDG.DeGrid(c, metadata, modelGrid, local.UVW, local.Frequencies);
residualVis = Visibilities.Substract(local.Visibilities, modelVis, local.Flags);
}
writer.Close();
float[][,] gatherX = null;
comm.Gather(xLocal, 0, ref gatherX);
float[,] reconstructed = null;
if (comm.Rank == 0)
{
reconstructed = new float[c.GridSize, c.GridSize];;
StitchImage(gatherX, reconstructed, comm.Size);
}
return(reconstructed);
}
public Tools.Collections.SerializableDictionary <string, MpiTimeSeries>[] Gather(Tools.Collections.SerializableDictionary <string, MpiTimeSeries> serializableDictionary, int root, int sender)
{
return(communicator.Gather(serializableDictionary, root));
}
