///-------------------------------------------------------------------------------------------------
/// <summary> Map partition. </summary>
///
/// <remarks> Chris Rossbach ([email protected]), 8/7/2012. </remarks>
///
/// <param name="partition"> The partition. </param>
///-------------------------------------------------------------------------------------------------
public static void MapPartition(
object oPartition
)
{
KMeansMapPartition partition = oPartition as KMeansMapPartition;
while (!m_bMapPhasesComplete)
{
partition.m_newCenters = KMeansCalculator.CreateCenterAccumulatorList(partition.m_nCenters, partition.m_nRank);
partition.m_newGroupCounts = KMeansCalculator.CreateGroupCountList(partition.m_nCenters, partition.m_nRank);
partition.m_fDelta = 0.0f;
partition.m_evtMapWorkAvailable.WaitOne();
if (!m_bMapPhasesComplete)
{
for (int i = partition.m_nStartIndex; i < partition.m_nPartitionSize; i++)
{
Vector vec = partition.m_vectors.ElementAt(i);
int nIndex = FindNearestCenter(vec, partition.m_oldCenters);
if (partition.m_clusterIds.ElementAt(i) != nIndex)
{
partition.m_fDelta += 1.0f;
}
partition.m_clusterIds[i] = nIndex;
partition.m_newCenters[nIndex] += vec;
partition.m_newGroupCounts[nIndex] += 1;
}
partition.m_barrier.SignalAndWait();
}
}
}
SelectInitialCenters(
IEnumerable <Vector> attributes,
int nMinClusters,
int nRandomSeed
)
{
return(KMeansCalculator.SelectRandomCenters(attributes, nMinClusters, nRandomSeed));
}
///-------------------------------------------------------------------------------------------------
/// <summary> Updates the centers. </summary>
///
/// <remarks> Chris Rossbach ([email protected]), 8/7/2012. </remarks>
///
/// <param name="update"> The update. </param>
///-------------------------------------------------------------------------------------------------
public static void UpdateCenters(
object oUpdate
)
{
KMeansUpdateCenters update = oUpdate as KMeansUpdateCenters;
update.m_nIterations = 0;
while (!m_bUpdatePhasesComplete)
{
update.m_sharedCenters = KMeansCalculator.CreateCenterAccumulatorList(update.m_nCenters, update.m_nRank);
update.m_sharedGroupCounts = KMeansCalculator.CreateGroupCountList(update.m_nCenters, update.m_nRank);
update.m_fDelta = 0.0f;
update.m_evtMapWorkComplete.WaitOne();
if (m_bVerbose)
{
Console.WriteLine("update...");
}
for (int w = 0; w < update.m_workers.Count(); w++)
{
KMeansMapPartition worker = update.m_workers[w];
update.m_fDelta += worker.m_fDelta;
for (int i = 0; i < update.m_nCenters; i++)
{
update.m_sharedCenters[i] += worker.m_newCenters[i];
update.m_sharedGroupCounts[i] += worker.m_newGroupCounts[i];
}
}
for (int i = 0; i < update.m_nCenters; i++)
{
update.m_sharedCenters[i] /= update.m_sharedGroupCounts[i];
}
update.m_fDelta /= update.m_nPoints;
update.m_nIterations++;
if (update.m_nIterations < update.m_options.m_nMaxIterations &&
update.m_fDelta >= update.m_options.m_fConvergenceThreshold)
{
for (int w = 0; w < update.m_workers.Count(); w++)
{
update.m_workers[w].m_oldCenters = update.m_sharedCenters;
}
update.m_evtMapWorkComplete.Reset();
update.m_evtMapWorkAvailable.Set();
}
else
{
m_bMapPhasesComplete = true;
m_bUpdatePhasesComplete = true;
update.m_evtMapWorkAvailable.Set(); // shouldn't be needed, but harmless
return;
}
}
}
///-------------------------------------------------------------------------------------------------
/// <summary> Main entry-point for this application. </summary>
///
/// <remarks> crossbac, 8/6/2013. </remarks>
///
/// <param name="args"> Array of command-line argument strings. </param>
///-------------------------------------------------------------------------------------------------
static void Main(string[] args)
{
KMeansOptions options = KMeansOptions.getOptions(args);
if (options == null)
{
return;
}
if (options.m_bGenerateData)
{
GenerateRandomInput(options.m_strFileName,
options.m_nGenerateElems,
options.m_nGenerateDims);
return;
}
Vector[] attributes =
options.m_bBinaryInput ?
KMeansCalculator.ReadBinaryInput(options.m_strFileName) :
KMeansCalculator.ReadTextInput(options.m_strFileName);
ComparePerformance(options, attributes);
}
///-------------------------------------------------------------------------------------------------
/// <summary> Compare performance of several implementations. </summary>
///
/// <remarks> Chris Rossbach ([email protected]), 8/7/2012. </remarks>
///
/// <param name="options"> Options for controlling the operation. </param>
/// <param name="attributes"> The attributes. </param>
///-------------------------------------------------------------------------------------------------
static void ComparePerformance(
KMeansOptions options,
IEnumerable <Vector> attributes
)
{
List <String> runnableVersions = SelectVersionsToCompare(options);
Dictionary <String, Sample[]> perfdata = new Dictionary <string, Sample[]>();
Dictionary <String, Performance> stats = new Dictionary <string, Performance>();
foreach (String version in runnableVersions)
{
Sample[] vdata = new Sample[options.m_nTotalRuns];
for (int i = 0; i < options.m_nTotalRuns; i++)
{
vdata[i] = new Sample();
}
perfdata[version] = vdata;
}
IEnumerable <Vector> goldcenters =
SelectInitialCenters(attributes,
options.m_nClusters,
options.m_nRandomSeed);
for (int i = 0; i < options.m_nTotalRuns; i++)
{
long lReferenceImplTime = 0;
IEnumerable <Vector> refnewcenters = null;
if (options.m_bCheckResult)
{
Vector[] refcenters = DuplicateCenters(goldcenters);
ReferenceKMeans refkmeans = new ReferenceKMeans();
refnewcenters = refkmeans.Compute(attributes, refcenters, options.m_nMaxIterations, true);
lReferenceImplTime = refkmeans.RuntimeMilliseconds;
}
foreach (String sVersion in runnableVersions)
{
bool bAvoidLazyEval = true;
int nMaxParallelism = 1;
int[] rClusterIds = null;
Vector[] newcenters = DuplicateCenters(goldcenters);
KMeansCalculator kmeans = SelectImplementation(options, sVersion, out nMaxParallelism, out bAvoidLazyEval);
int nIterations = kmeans.execute(options, attributes, ref newcenters, out rClusterIds, nMaxParallelism, bAvoidLazyEval);
Sample isample = perfdata[sVersion][i];
isample.m_impltime = kmeans.RuntimeMilliseconds;
isample.m_success = true;
isample.m_reftime = 0;
if (options.m_bCheckResult)
{
isample.m_reftime = lReferenceImplTime;
isample.m_success = KMeansCalculator.CheckResult(options,
newcenters,
refnewcenters,
options.m_bVerbose,
options.m_bVerbose);
if (!isample.m_success)
{
Console.WriteLine("FAILED");
return;
}
}
}
}
Console.WriteLine("SUCCEEDED");
foreach (String v in perfdata.Keys)
{
Sample[] samples = perfdata[v];
Performance perf = new Performance(samples);
Console.WriteLine("{0,-15}: {1}, avg={2}", v, perf.RawRuntimes(), perf.m_impltime.ToString("f1"));
}
}
