An example of the use of the RCB algorithm to partition coordinate data.
#include <Tpetra_Map.hpp>
#include <vector>
#include <cstdlib>
using std::vector;
int main(
int argc,
char *argv[])
{
#ifdef HAVE_ZOLTAN2_MPI
MPI_Init(&argc, &argv);
int rank, nprocs;
MPI_Comm_size(MPI_COMM_WORLD, &nprocs);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
#else
int rank=0, nprocs=1;
#endif
typedef Tpetra::Map<> Map_t;
typedef Map_t::local_ordinal_type localId_t;
typedef Map_t::global_ordinal_type globalId_t;
typedef double scalar_t;
typedef inputAdapter_t::part_t part_t;
size_t localCount = 40;
int dim = 3;
scalar_t *coords = new scalar_t [dim * localCount];
scalar_t *x = coords;
scalar_t *y = x + localCount;
scalar_t *z = y + localCount;
srand(rank);
scalar_t scalingFactor = 10.0 / RAND_MAX;
for (size_t i=0; i < localCount*dim; i++){
coords[i] = scalar_t(rand()) * scalingFactor;
}
globalId_t *globalIds = new globalId_t [localCount];
globalId_t offset = rank * localCount;
for (size_t i=0; i < localCount; i++)
globalIds[i] = offset++;
double tolerance = 1.1;
if (rank == 0)
std::cout << "Imbalance tolerance is " << tolerance << std::endl;
Teuchos::ParameterList params("test params");
params.set("debug_level", "basic_status");
params.set("debug_procs", "0");
params.set("error_check_level", "debug_mode_assertions");
params.set("compute_metrics", "true");
params.set("algorithm", "rcb");
params.set("imbalance_tolerance", tolerance );
params.set("num_global_parts", nprocs);
params.set("bisection_num_test_cuts", 1);
inputAdapter_t ia1(localCount, globalIds, x, y, z, 1, 1, 1);
if (rank == 0)
if (rank == 0){
if (imb <= tolerance)
std::cout << "pass: " << imb << std::endl;
else
std::cout << "fail: " << imb << std::endl;
std::cout << std::endl;
}
scalar_t *
weights =
new scalar_t [localCount];
for (size_t i=0; i < localCount; i++){
weights[i] = 1.0 + scalar_t(rank) / scalar_t(nprocs);
}
vector<const scalar_t *>coordVec(2);
vector<int> coordStrides(2);
coordVec[0] = x; coordStrides[0] = 1;
coordVec[1] = y; coordStrides[1] = 1;
vector<const scalar_t *>weightVec(1);
vector<int> weightStrides(1);
weightVec[0] =
weights; weightStrides[0] = 1;
inputAdapter_t ia2(
localCount, globalIds,
coordVec, coordStrides,
weightVec, weightStrides);
if (rank == 0)
if (rank == 0){
if (imb <= tolerance)
std::cout << "pass: " << imb << std::endl;
else
std::cout << "fail: " << imb << std::endl;
std::cout << std::endl;
}
if (localCount > 0){
weights = NULL;
}
params.set("partitioning_objective", "multicriteria_minimize_total_weight");
weights = new scalar_t [localCount*3];
srand(rank);
for (size_t i=0; i < localCount*3; i+=3){
weights[i] = 1.0 + rank / nprocs;
weights[i+1] = rank<nprocs/2 ? 1 : 2;
weights[i+2] = rand()/RAND_MAX +.5;
}
weightVec.resize(3);
weightStrides.resize(3);
weightVec[0] =
weights; weightStrides[0] = 3;
weightVec[1] = weights+1; weightStrides[1] = 3;
weightVec[2] = weights+2; weightStrides[2] = 3;
inputAdapter_t ia3(
localCount, globalIds,
coordVec, coordStrides,
weightVec, weightStrides);
if (rank == 0)
if (rank == 0){
if (imb <= tolerance)
std::cout << "pass: " << imb << std::endl;
else
std::cout << "fail: " << imb << std::endl;
std::cout << std::endl;
}
bool dataHasChanged = false;
params.set("partitioning_objective", "multicriteria_minimize_maximum_weight");
problem3->
solve(dataHasChanged);
if (rank == 0){
if (imb <= tolerance)
std::cout << "pass: " << imb << std::endl;
else
std::cout << "fail: " << imb << std::endl;
std::cout << std::endl;
}
params.set("partitioning_objective", "multicriteria_balance_total_maximum");
problem3->
solve(dataHasChanged);
if (rank == 0){
if (imb <= tolerance)
std::cout << "pass: " << imb << std::endl;
else
std::cout << "fail: " << imb << std::endl;
std::cout << std::endl;
}
if (localCount > 0){
weights = NULL;
}
params.set("num_global_parts", nprocs*2);
part_t partIds[2];
scalar_t partSizes[2];
partIds[0] = rank*2; partSizes[0] = 0;
partIds[1] = rank*2+1; partSizes[1] = 1;
dataHasChanged = false;
problem1->
solve(dataHasChanged);
int numInEmptyParts = 0;
for (size_t i=0; i < localCount; i++){
if (partAssignments[i] % 2 == 0)
numInEmptyParts++;
}
if (rank == 0)
std::cout << "Request that " << nprocs << " parts be empty." <<std::endl;
if (rank == 0)
if (rank == 0){
if (imb <= tolerance)
std::cout << "pass: " << imb << std::endl;
else
std::cout << "fail: " << imb << std::endl;
std::cout << std::endl;
}
if (coords)
delete [] coords;
if (globalIds)
delete [] globalIds;
delete problem1;
delete problem2;
delete problem3;
#ifdef HAVE_ZOLTAN2_MPI
MPI_Finalize();
#endif
if (rank == 0)
std::cout << "PASS" << std::endl;
}