[SYSTEMDS-3914] tsmm ooc operation

src/main/java/org/apache/sysds/hops/AggBinaryOp.java

@@ -179,7 +179,7 @@ public Lop constructLops() {
 				et = ExecType.CP;
 			}
 
-			if (et == ExecType.CP || et == ExecType.GPU || et == ExecType.FED) {
+			if (et == ExecType.CP || et == ExecType.GPU || et == ExecType.FED || et == ExecType.OOC) {
 				//matrix mult operation selection part 3 (CP type)
 				_method = optFindMMultMethodCP(input1.getDim1(), input1.getDim2(),
 						input2.getDim1(), input2.getDim2(), mmtsj, chain, _hasLeftPMInput);
@@ -240,14 +240,6 @@ public Lop constructLops() {
 					default:
 						throw new HopsException(this.printErrorLocation() + "Invalid Matrix Mult Method (" + _method + ") while constructing SPARK lops.");
 				}
-			} else if (et == ExecType.OOC) {
-				Lop in1 = getInput().get(0).constructLops();
-				Lop in2 = getInput().get(1).constructLops();
-				MatMultCP matmult = new MatMultCP(in1, in2, getDataType(), getValueType(),
-					et, OptimizerUtils.getConstrainedNumThreads(_maxNumThreads));
-				setOutputDimensions(matmult);
-				setLineNumbers(matmult);
-				setLops(matmult);
 			}
 		} else
 			throw new HopsException(this.printErrorLocation() + "Invalid operation in AggBinary Hop, aggBin(" + innerOp + "," + outerOp + ") while constructing lops.");

src/main/java/org/apache/sysds/runtime/instructions/OOCInstructionParser.java

@@ -27,6 +27,7 @@
 import org.apache.sysds.runtime.instructions.ooc.BinaryOOCInstruction;
 import org.apache.sysds.runtime.instructions.ooc.OOCInstruction;
 import org.apache.sysds.runtime.instructions.ooc.ReblockOOCInstruction;
+import org.apache.sysds.runtime.instructions.ooc.TSMMOOCInstruction;
 import org.apache.sysds.runtime.instructions.ooc.UnaryOOCInstruction;
 import org.apache.sysds.runtime.instructions.ooc.MatrixVectorBinaryOOCInstruction;
 import org.apache.sysds.runtime.instructions.ooc.TransposeOOCInstruction;
@@ -61,6 +62,8 @@ public static OOCInstruction parseSingleInstruction(InstructionType ooctype, Str
 			case AggregateBinary:
 			case MAPMM:
 				return MatrixVectorBinaryOOCInstruction.parseInstruction(str);
+			case MMTSJ:
+				return TSMMOOCInstruction.parseInstruction(str);
 			case Reorg:
 				return TransposeOOCInstruction.parseInstruction(str);
 

src/main/java/org/apache/sysds/runtime/instructions/ooc/OOCInstruction.java

@@ -30,7 +30,7 @@ public abstract class OOCInstruction extends Instruction {
 	protected static final Log LOG = LogFactory.getLog(OOCInstruction.class.getName());
 
 	public enum OOCType {
-		Reblock, AggregateUnary, Binary, Unary, MAPMM, Reorg, AggregateBinary
+		Reblock, AggregateUnary, Binary, Unary, MAPMM, Reorg, AggregateBinary, MMTSJ
 	}
 
 	protected final OOCInstruction.OOCType _ooctype;

src/main/java/org/apache/sysds/runtime/instructions/ooc/TSMMOOCInstruction.java

@@ -0,0 +1,111 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.sysds.runtime.instructions.ooc;
+
+import org.apache.sysds.common.Opcodes;
+import org.apache.sysds.conf.ConfigurationManager;
+import org.apache.sysds.lops.MMTSJ;
+import org.apache.sysds.runtime.DMLRuntimeException;
+import org.apache.sysds.runtime.controlprogram.caching.MatrixObject;
+import org.apache.sysds.runtime.controlprogram.context.ExecutionContext;
+import org.apache.sysds.runtime.controlprogram.parfor.LocalTaskQueue;
+import org.apache.sysds.runtime.functionobjects.Multiply;
+import org.apache.sysds.runtime.functionobjects.Plus;
+import org.apache.sysds.runtime.instructions.InstructionUtils;
+import org.apache.sysds.runtime.instructions.cp.CPOperand;
+import org.apache.sysds.runtime.instructions.spark.data.IndexedMatrixValue;
+import org.apache.sysds.runtime.matrix.data.MatrixBlock;
+import org.apache.sysds.runtime.matrix.data.MatrixIndexes;
+import org.apache.sysds.runtime.matrix.operators.AggregateBinaryOperator;
+import org.apache.sysds.runtime.matrix.operators.AggregateOperator;
+import org.apache.sysds.runtime.matrix.operators.BinaryOperator;
+import org.apache.sysds.runtime.matrix.operators.Operator;
+import org.apache.sysds.runtime.util.CommonThreadPool;
+
+import java.util.HashMap;
+import java.util.concurrent.ExecutorService;
+
+public class TSMMOOCInstruction extends ComputationOOCInstruction {
+	private final MMTSJ.MMTSJType _type;
+
+	protected TSMMOOCInstruction(OOCType type, Operator op, CPOperand in1, CPOperand out, MMTSJ.MMTSJType mmtsjType, String opcode, String istr) {
+		super(type, op, in1, out, opcode, istr);
+		_type = mmtsjType;
+	}
+
+	public static TSMMOOCInstruction parseInstruction(String str) {
+		String[] parts = InstructionUtils.getInstructionPartsWithValueType(str);
+		InstructionUtils.checkNumFields(parts, 3);
+		String opcode = parts[0];
+		CPOperand in1 = new CPOperand(parts[1]); // the large matrix (streamed), columns <= blocksize
+		CPOperand out = new CPOperand(parts[2]);
+		MMTSJ.MMTSJType mmtsjType = MMTSJ.MMTSJType.valueOf(parts[3]);
+
+		AggregateOperator agg = new AggregateOperator(0, Plus.getPlusFnObject());
+		AggregateBinaryOperator ba = new AggregateBinaryOperator(Multiply.getMultiplyFnObject(), agg);
+
+		return new TSMMOOCInstruction(OOCType.MMTSJ, ba, in1, out, mmtsjType, opcode, str);
+	}
+
+	@Override
+	public void processInstruction( ExecutionContext ec ) {
+		// 1. Identify the inputs
+		MatrixObject min = ec.getMatrixObject(input1); // big matrix
+
+		// number of colBlocks for early block output
+		int nCols = (int) min.getDataCharacteristics().getCols();
+
+		LocalTaskQueue<IndexedMatrixValue> qIn = min.getStreamHandle();
+		LocalTaskQueue<IndexedMatrixValue> qOut = new LocalTaskQueue<>();
+		BinaryOperator plus = InstructionUtils.parseBinaryOperator(Opcodes.PLUS.toString());
+		ec.getMatrixObject(output).setStreamHandle(qOut);
+
+		ExecutorService pool = CommonThreadPool.get();
+		try {
+			// Core logic: background thread
+			pool.submit(() -> {
+				IndexedMatrixValue tmp = null;
+				try {
+					MatrixBlock resultBlock = new MatrixBlock(nCols, nCols, false);
+					while((tmp = qIn.dequeueTask()) != LocalTaskQueue.NO_MORE_TASKS) {
+						MatrixBlock matrixBlock = (MatrixBlock) tmp.getValue();
+
+						// Now, call the operation with the correct, specific operator.
+						MatrixBlock partialResult = matrixBlock.transposeSelfMatrixMultOperations(new MatrixBlock(), _type);
+						resultBlock.binaryOperationsInPlace(plus, partialResult);
+
+					}
+					qOut.enqueueTask(new IndexedMatrixValue(new MatrixIndexes(1, 1), resultBlock));
+				}
+				catch(Exception ex) {
+					throw new DMLRuntimeException(ex);
+				}
+				finally {
+					qOut.closeInput();
+				}
+			});
+		} catch (Exception e) {
+			throw new DMLRuntimeException(e);
+		}
+		finally {
+			pool.shutdown();
+		}
+	}
+}

src/test/java/org/apache/sysds/test/functions/ooc/TSMMTest.java

@@ -0,0 +1,107 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.sysds.test.functions.ooc;
+
+import org.apache.sysds.common.Types;
+import org.apache.sysds.lops.MMTSJ;
+import org.apache.sysds.runtime.io.MatrixWriter;
+import org.apache.sysds.runtime.io.MatrixWriterFactory;
+import org.apache.sysds.runtime.matrix.data.LibMatrixMult;
+import org.apache.sysds.runtime.matrix.data.MatrixBlock;
+import org.apache.sysds.runtime.meta.MatrixCharacteristics;
+import org.apache.sysds.runtime.util.DataConverter;
+import org.apache.sysds.runtime.util.HDFSTool;
+import org.apache.sysds.test.AutomatedTestBase;
+import org.apache.sysds.test.TestConfiguration;
+import org.apache.sysds.test.TestUtils;
+import org.checkerframework.checker.units.qual.A;
+import org.junit.Test;
+
+import java.io.IOException;
+
+public class TSMMTest extends AutomatedTestBase {
+	private final static String TEST_NAME1 = "TSMM";
+	private final static String TEST_DIR = "functions/ooc/";
+	private final static String TEST_CLASS_DIR = TEST_DIR + TSMMTest.class.getSimpleName() + "/";
+	private final static double eps = 1e-10;
+	private static final String INPUT_NAME = "X";
+	private static final String OUTPUT_NAME = "res";
+
+	private final static int rows = 1000;
+	private final static int cols_wide = 1000;
+	private final static double sparsity1 = 0.7;
+	private final static double sparsity2 = 0.1;
+	private final int k = 1;
+
+	@Override
+	public void setUp() {
+		TestUtils.clearAssertionInformation();
+		TestConfiguration config = new TestConfiguration(TEST_CLASS_DIR, TEST_NAME1);
+		addTestConfiguration(TEST_NAME1, config);
+	}
+
+	@Test
+	public void testTSMM1() {
+		runTSMMTest(cols_wide, false);
+	}
+
+	private void runTSMMTest(int cols, boolean sparse )
+	{
+		Types.ExecMode platformOld = setExecMode(Types.ExecMode.SINGLE_NODE);
+
+		try
+		{
+			getAndLoadTestConfiguration(TEST_NAME1);
+			String HOME = SCRIPT_DIR + TEST_DIR;
+			fullDMLScriptName = HOME + TEST_NAME1 + ".dml";
+			programArgs = new String[]{"-explain", "-stats", "-ooc",
+							"-args", input(INPUT_NAME), output(OUTPUT_NAME)};
+
+			// 1. Generate the data in-memory as MatrixBlock objects
+			double[][] A_data = getRandomMatrix(rows, cols, 0, 1, sparse?sparsity2:sparsity1, 10);
+
+			// 2. Convert the double arrays to MatrixBlock objects
+			MatrixBlock A_mb = DataConverter.convertToMatrixBlock(A_data);
+
+			// 3. Create a binary matrix writer
+			MatrixWriter writer = MatrixWriterFactory.createMatrixWriter(Types.FileFormat.BINARY);
+
+			// 4. Write matrix A to a binary SequenceFile
+			writer.writeMatrixToHDFS(A_mb, input(INPUT_NAME), rows, cols, 1000, A_mb.getNonZeros());
+			HDFSTool.writeMetaDataFile(input(INPUT_NAME + ".mtd"), Types.ValueType.FP64,
+							new MatrixCharacteristics(rows, cols, 1000, A_mb.getNonZeros()), Types.FileFormat.BINARY);
+
+			boolean exceptionExpected = false;
+			runTest(true, exceptionExpected, null, -1);
+
+			MatrixBlock ret1 = DataConverter.readMatrixFromHDFS(output(OUTPUT_NAME), Types.FileFormat.BINARY, rows, cols, 1000, 1000);
+			MatrixBlock ret2 = new MatrixBlock(rows, rows, false);
+			A_mb.transposeSelfMatrixMultOperations(ret2, MMTSJ.MMTSJType.LEFT, k);
+			TestUtils.compareMatrices(ret1, ret2, 1e-8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+		finally {
+			resetExecMode(platformOld);
+		}
+	}
+
+}

src/test/scripts/functions/ooc/TSMM.dml

@@ -0,0 +1,28 @@
+#-------------------------------------------------------------
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+#-------------------------------------------------------------
+
+# Read input matrix and operator from command line args
+X = read($1);
+
+# Operation under test
+res = t(X) %*% X;
+
+write(res, $2, format="binary")