diff --git a/P2/Makefile b/P2/Makefile
index d058a23da3f801021071719b9c1d67f825f8eeba..20bb0c2a2bcb6325dfc027f50187f978531b6e2b 100644
--- a/P2/Makefile
+++ b/P2/Makefile
@@ -1,7 +1,7 @@
CXX = mpic++
CXXFLAGS = -std=c++17 -Wall -Wextra -O0 -g
-TARGET = profile
-OBJ = matrix.o distributedmatrix.o profile.o mlp_sgd_distributed.o globals.o
+TARGET = distributedtests
+OBJ = matrix.o distributedmatrix.o distributedtests.o mlp_sgd_distributed.o globals.o
HEADERS = abstractmatrix.hpp matrix.hpp distributedmatrix.hpp globals.hpp
NVTX_INC = -I/usr/local/cuda/include
NVTX_LIB = -L/usr/local/cuda/lib64 -lnvToolsExt
@@ -20,8 +20,8 @@ matrix.o: matrix.cpp matrix.hpp abstractmatrix.hpp
distributedmatrix.o: distributedmatrix.cpp distributedmatrix.hpp matrix.hpp abstractmatrix.hpp
$(CXX) $(CXXFLAGS) -c distributedmatrix.cpp
-profile.o: profile.cpp distributedmatrix.hpp matrix.hpp abstractmatrix.hpp
- $(CXX) $(CXXFLAGS) -c profile.cpp
+distributedtests.o: distributedtests.cpp distributedmatrix.hpp matrix.hpp abstractmatrix.hpp
+ $(CXX) $(CXXFLAGS) -c distributedtests.cpp
mlp_sgd_distributed.o: mlp_sgd_distributed.cpp globals.hpp abstractmatrix.hpp matrix.hpp distributedmatrix.hpp
$(CXX) $(CXXFLAGS) -c mlp_sgd_distributed.cpp
diff --git a/P2/distributedtests.cpp b/P2/distributedtests.cpp
index 959fec27ed364aa6baf26f0e9fd98b7ca1489b6d..e111541003d8895dac75438b90828113a2be1257 100644
--- a/P2/distributedtests.cpp
+++ b/P2/distributedtests.cpp
@@ -31,372 +31,21 @@ bool matricesEqual(const Matrix& a, const Matrix& b, double epsilon = 1e-10) {
return true;
}
-// Test constructor and basic properties
-void testConstructorAndBasics() {
- int rank;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
-
- // Create a test matrix
- Matrix testMatrix(3, 4);
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 4; j++) {
- testMatrix.set(i, j, i * 10 + j);
- }
- }
-
- // Create distributed matrix
- int numProcs;
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
- DistributedMatrix distMatrix(testMatrix, numProcs);
- // Check dimensions
- assert(distMatrix.numRows() == 3);
- assert(distMatrix.numCols() == 4);
-
- // Gather and check equality with original
- Matrix gathered = distMatrix.gather();
- assert(matricesEqual(gathered, testMatrix));
-
- if (rank == 0) {
- std::cout << "Constructor and basic properties test passed!" << std::endl;
- }
-}
-
-// Test column distribution
-void testColumnDistribution() {
- int rank, numProcs;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
-
- // Create a test matrix with more columns to better test distribution
- int cols = numProcs * 2 + 1; // Ensure some remainder for testing
- Matrix testMatrix(3, cols);
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < cols; j++) {
- testMatrix.set(i, j, i * 100 + j);
- }
- }
-
- // Create distributed matrix
- DistributedMatrix distMatrix(testMatrix, numProcs);
-
- // Check local data dimensions
- const Matrix& localData = distMatrix.getLocalData();
-
- // Calculate expected column distribution
- int baseCols = cols / numProcs;
- int remainder = cols % numProcs;
- int expectedLocalCols = baseCols + (rank < remainder ? 1 : 0);
-
- assert(localData.numRows() == 3);
- assert(localData.numCols() == expectedLocalCols);
-
- // Check global/local column index conversion
- for (int j = 0; j < localData.numCols(); j++) {
- int globalJ = distMatrix.globalColIndex(j);
- assert(distMatrix.localColIndex(globalJ) == j);
- assert(distMatrix.ownerProcess(globalJ) == rank);
- }
-
- if (rank == 0) {
- std::cout << "Column distribution test passed!" << std::endl;
- }
-}
-
-// Test gather function
-void testGather() {
- int rank;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
-
- // Create a test matrix
- Matrix testMatrix(4, 6);
- for (int i = 0; i < 4; i++) {
- for (int j = 0; j < 6; j++) {
- testMatrix.set(i, j, i * 10 + j);
- }
- }
-
- // Create distributed matrix
- int numProcs;
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
- DistributedMatrix distMatrix(testMatrix, numProcs);
-
- // Gather and check equality with original
- Matrix gathered = distMatrix.gather();
- assert(matricesEqual(gathered, testMatrix));
-
- if (rank == 0) {
- std::cout << "Gather function test passed!" << std::endl;
- }
-}
-
-// Test the get and set functions (may throw exceptions)
-void testGetAndSet() {
- int rank, numProcs;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
-
- // Skip this test if only one process
- if (numProcs == 1) {
- if (rank == 0) {
- std::cout << "Get/Set test skipped (requires multiple processes)" << std::endl;
- }
- return;
- }
-
- // Create a test matrix
- Matrix testMatrix(2, numProcs);
- for (int i = 0; i < 2; i++) {
- for (int j = 0; j < numProcs; j++) {
- testMatrix.set(i, j, i * numProcs + j);
- }
- }
-
- // Create distributed matrix - each process gets exactly one column
- DistributedMatrix distMatrix(testMatrix, numProcs);
-
- // Test local access - should work
- bool localAccessWorks = true;
- try {
- double val = distMatrix.get(1, rank);
- assert(approxEqual(val, 1 * numProcs + rank));
-
- distMatrix.set(1, rank, 99.0);
- val = distMatrix.get(1, rank);
- assert(approxEqual(val, 99.0));
- } catch (std::exception& e) {
- localAccessWorks = false;
- }
- assert(localAccessWorks);
-
- // Test remote access - should throw
- if (numProcs > 1) {
- bool remoteAccessFails = false;
- int remoteRank = (rank + 1) % numProcs;
- try {
- (void)distMatrix.get(1, remoteRank);
- } catch (std::exception& e) {
- remoteAccessFails = true;
- }
- assert(remoteAccessFails);
-
- remoteAccessFails = false;
- try {
- distMatrix.set(1, remoteRank, 100.0);
- } catch (std::exception& e) {
- remoteAccessFails = true;
- }
- assert(remoteAccessFails);
- }
-
- if (rank == 0) {
- std::cout << "Get/Set function test passed!" << std::endl;
- }
-}
-
-// Test copy constructor
-void testCopyConstructor() {
- int rank;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
-
- // Create a test matrix
- Matrix testMatrix(3, 5);
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 5; j++) {
- testMatrix.set(i, j, i * 5 + j);
- }
- }
-
- // Create distributed matrix
- int numProcs;
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
- DistributedMatrix original(testMatrix, numProcs);
-
- // Create a copy
- DistributedMatrix copy(original);
-
- // Check basic properties
- assert(copy.numRows() == original.numRows());
- assert(copy.numCols() == original.numCols());
-
- // Check local data
- const Matrix& originalLocal = original.getLocalData();
- const Matrix& copyLocal = copy.getLocalData();
- assert(matricesEqual(originalLocal, copyLocal));
-
- // Modify copy and check independence
- auto doubleFunc = [](double x) { return 2 * x; };
- DistributedMatrix modifiedCopy = copy.apply(doubleFunc);
-
- Matrix originalGathered = original.gather();
- Matrix modifiedGathered = modifiedCopy.gather();
- assert(!matricesEqual(originalGathered, modifiedGathered));
-
- if (rank == 0) {
- std::cout << "Copy constructor test passed!" << std::endl;
- }
-}
-
-// Test apply function
-void testApply() {
- int rank;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
-
- // Create a test matrix
- Matrix testMatrix(2, 5);
- for (int i = 0; i < 2; i++) {
- for (int j = 0; j < 5; j++) {
- testMatrix.set(i, j, i + j);
- }
- }
-
- // Create distributed matrix
- int numProcs;
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
- DistributedMatrix distMatrix(testMatrix, numProcs);
-
- // Apply a function to square each element
- auto squareFunc = [](double x) { return x * x; };
- DistributedMatrix squaredMatrix = distMatrix.apply(squareFunc);
-
- // Create expected result
- Matrix expectedMatrix = testMatrix.apply(squareFunc);
-
- // Gather and check
- Matrix gathered = squaredMatrix.gather();
- assert(matricesEqual(gathered, expectedMatrix));
-
- if (rank == 0) {
- std::cout << "Apply function test passed!" << std::endl;
- }
-}
-
-// Test applyBinary function
-void testApplyBinary() {
- int rank;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
-
- // Create test matrices
- Matrix testMatrix1(3, 4);
- Matrix testMatrix2(3, 4);
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 4; j++) {
- testMatrix1.set(i, j, i + j);
- testMatrix2.set(i, j, i * j);
- }
- }
-
- // Create distributed matrices
- int numProcs;
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
- DistributedMatrix distMatrix1(testMatrix1, numProcs);
- DistributedMatrix distMatrix2(testMatrix2, numProcs);
-
- // Apply binary function (add)
- auto addFunc = [](double a, double b) { return a + b; };
- DistributedMatrix resultMatrix = DistributedMatrix::applyBinary(distMatrix1, distMatrix2, addFunc);
-
- // Create expected result
- Matrix expectedMatrix(3, 4);
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 4; j++) {
- expectedMatrix.set(i, j, testMatrix1.get(i, j) + testMatrix2.get(i, j));
- }
- }
-
- // Gather and check
- Matrix gathered = resultMatrix.gather();
- assert(matricesEqual(gathered, expectedMatrix));
-
- if (rank == 0) {
- std::cout << "ApplyBinary function test passed!" << std::endl;
- }
-}
-
-void testSum() {
- int rank;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
-
- // Create test matrix
- Matrix matrixFull(3, 5);
- double total = 0.0;
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 5; j++) {
- matrixFull.set(i, j, i * 5 + j + 1);
- total += i * 5 + j + 1;
- }
- }
-
- // Create a distributed matrix
- int numProcs;
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
- DistributedMatrix matrix(matrixFull, numProcs);
-
- // Compute the sum
- double result = matrix.sum();
-
- // Check
- assert(approxEqual(result, total, 1e-8));
-
- if (rank == 0) {
- std::cout << "Sum test passed!" << std::endl;
- }
-}
-
-// Test matrix multiplication (Matrix * DistributedMatrix)
-void testMultiply() {
- int rank;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
-
- // Create test matrices
- Matrix leftMatrix(2, 3);
- for (int i = 0; i < 2; i++) {
- for (int j = 0; j < 3; j++) {
- leftMatrix.set(i, j, i * 3 + j + 1); // 1-based values for better testing
- }
- }
-
- Matrix rightMatrixFull(3, 4);
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 4; j++) {
- rightMatrixFull.set(i, j, i * 4 + j + 1); // 1-based values
- }
- }
-
- // Create distributed matrix for right operand
- int numProcs;
- MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
- DistributedMatrix rightMatrix(rightMatrixFull, numProcs);
-
- // Multiply
- DistributedMatrix resultMatrix = multiply(leftMatrix, rightMatrix);
-
- // Compute expected result
- Matrix expectedMatrix = leftMatrix * rightMatrixFull;
-
- // Gather and check
- Matrix gathered = resultMatrix.gather();
- assert(matricesEqual(gathered, expectedMatrix, 1e-8)); // Use larger epsilon for multiplication
-
- if (rank == 0) {
- std::cout << "Matrix multiplication test passed!" << std::endl;
- }
-}
-
// Test multiplyTransposed
void testMultiplyTransposed() {
int rank;
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
// Create test matrices
- Matrix matrix1Full(3, 5);
- Matrix matrix2Full(4, 5);
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 5; j++) {
+ Matrix matrix1Full(256, 256);
+ Matrix matrix2Full(256, 256);
+ for (int i = 0; i < 256; i++) {
+ for (int j = 0; j < 256; j++) {
matrix1Full.set(i, j, i * 5 + j + 1);
}
}
- for (int i = 0; i < 4; i++) {
- for (int j = 0; j < 5; j++) {
+ for (int i = 0; i < 256; i++) {
+ for (int j = 0; j < 256; j++) {
matrix2Full.set(i, j, i * 5 + j + 2);
}
}
@@ -430,63 +79,6 @@ void testMultiplyTransposed() {
}
}
-void test_distributed_mlp_training()
-{
- int rank, size;
- MPI_Comm_rank(MPI_COMM_WORLD, &rank);
- MPI_Comm_size(MPI_COMM_WORLD, &size);
-
- // Print info about the MPI environment
- if (rank == 0) {
- std::cout << "Running with " << size << " MPI processes." << std::endl;
- }
-
- // Create a simple XOR dataset
- // Create data
- Matrix X(3, 4);
- Matrix Y(1, 4);
-
- // 0
- X.set(0, 0, 0.0);
- X.set(1, 0, 0.0);
- X.set(2, 0, 1.0);
- Y.set(0, 0, 0.0);
-
- // 1
- X.set(0, 1, 0.0);
- X.set(1, 1, 1.0);
- X.set(2, 1, 1.0);
- Y.set(0, 1, 1.0);
-
- // 2
- X.set(0, 2, 1.0);
- X.set(1, 2, 0.0);
- X.set(2, 2, 1.0);
- Y.set(0, 2, 1.0);
-
- // 3
- X.set(0, 3, 1.0);
- X.set(1, 3, 1.0);
- X.set(2, 3, 1.0);
- Y.set(0, 3, 0.0);
-
- // Distribute the data
- Dataset data = Dataset(DistributedMatrix(X, size), DistributedMatrix(Y, size));
-
- // Create and train the model
- MLP model(3, 128, 1, 0.1);
-
- if (rank == 0) {
- std::cout << "Training distributed MLP for XOR problem..." << std::endl;
- }
-
- model.train(data, 5000);
-
- if (rank==0) {
- std::cout << "Distributed MLP training test completed." << std::endl;
- }
-}
-
int main(int argc, char** argv) {
// Initialize MPI
int initialized;
@@ -504,17 +96,7 @@ int main(int argc, char** argv) {
try {
// Run tests
- testConstructorAndBasics();
- testColumnDistribution();
- testApply();
- testApplyBinary();
- testMultiply();
testMultiplyTransposed();
- testSum();
- testGather();
- testGetAndSet();
- testCopyConstructor();
- test_distributed_mlp_training();
if (rank == 0) {
std::cout << "All tests passed successfully!" << std::endl;