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/*
* 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.gpu;
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.functionobjects.Multiply;
import org.apache.sysds.runtime.functionobjects.Plus;
import org.apache.sysds.runtime.functionobjects.SwapIndex;
import org.apache.sysds.runtime.instructions.InstructionUtils;
import org.apache.sysds.runtime.instructions.cp.CPOperand;
import org.apache.sysds.runtime.matrix.data.LibMatrixCUDA;
import org.apache.sysds.runtime.matrix.data.LibMatrixCuMatMult;
import org.apache.sysds.runtime.matrix.data.MatrixBlock;
import org.apache.sysds.runtime.matrix.operators.AggregateBinaryOperator;
import org.apache.sysds.runtime.matrix.operators.Operator;
import org.apache.sysds.runtime.matrix.operators.ReorgOperator;
import org.apache.sysds.utils.GPUStatistics;
public class AggregateBinaryGPUInstruction extends GPUInstruction {
private CPOperand _input1 = null;
private CPOperand _input2 = null;
private CPOperand _output = null;
private boolean _isLeftTransposed;
private boolean _isRightTransposed;
private AggregateBinaryGPUInstruction(Operator op, CPOperand in1, CPOperand in2, CPOperand out, String opcode,
String istr, boolean leftTranspose, boolean rightTranspose) {
super(op, opcode, istr);
_gputype = GPUINSTRUCTION_TYPE.AggregateBinary;
_input1 = in1;
_input2 = in2;
_output = out;
_isLeftTransposed = leftTranspose;
_isRightTransposed = rightTranspose;
}
public static AggregateBinaryGPUInstruction parseInstruction( String str ) {
String[] parts = InstructionUtils.getInstructionPartsWithValueType(str);
String opcode = parts[0];
if ( !opcode.equalsIgnoreCase("ba+*"))
throw new DMLRuntimeException("AggregateBinaryInstruction.parseInstruction():: Unknown opcode " + opcode);
InstructionUtils.checkNumFields( parts, 5 );
CPOperand in1 = new CPOperand(parts[1]);
CPOperand in2 = new CPOperand(parts[2]);
CPOperand out = new CPOperand(parts[3]);
boolean isLeftTransposed = Boolean.parseBoolean(parts[4]);
boolean isRightTransposed = Boolean.parseBoolean(parts[5]);
AggregateBinaryOperator aggbin = InstructionUtils.getMatMultOperator(1);
return new AggregateBinaryGPUInstruction(aggbin, in1, in2, out, opcode, str, isLeftTransposed, isRightTransposed);
}
@Override
public void processInstruction(ExecutionContext ec) {
GPUStatistics.incrementNoOfExecutedGPUInst();
AggregateBinaryOperator op = (AggregateBinaryOperator) _optr;
if( !(op.binaryFn instanceof Multiply && op.aggOp.increOp.fn instanceof Plus) )
throw new DMLRuntimeException("Unsupported binary aggregate operation: ("+op.binaryFn+", "+op.aggOp+").");
MatrixObject m1 = getMatrixInputForGPUInstruction(ec, _input1.getName());
MatrixObject m2 = getMatrixInputForGPUInstruction(ec, _input2.getName());
//compute matrix multiplication
int rlen = (int) (_isLeftTransposed ? m1.getNumColumns() : m1.getNumRows());
int clen = (int) (_isRightTransposed ? m2.getNumRows() : m2.getNumColumns());
ec.setMetaData(_output.getName(), rlen, clen);
LibMatrixCuMatMult.matmult(ec, ec.getGPUContext(0), getExtendedOpcode(), m1, m2, _output.getName(), _isLeftTransposed, _isRightTransposed);
//release inputs/outputs
ec.releaseMatrixInputForGPUInstruction(_input1.getName());
ec.releaseMatrixInputForGPUInstruction(_input2.getName());
ec.releaseMatrixOutputForGPUInstruction(_output.getName());
}
@SuppressWarnings("unused")
private static MatrixBlock transpose(MatrixBlock m1) {
ReorgOperator r_op = new ReorgOperator(SwapIndex.getSwapIndexFnObject(), 1);
return m1.reorgOperations(r_op, new MatrixBlock(), 0, 0, 0);
}
@SuppressWarnings("unused")
private static boolean isSparse(ExecutionContext ec, String var) {
MatrixObject mo = ec.getMatrixObject(var);
return LibMatrixCUDA.isInSparseFormat(ec.getGPUContext(0), mo);
}
}