| /* |
| * 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.sysml.lops; |
| |
| import org.apache.sysml.lops.LopProperties.ExecLocation; |
| import org.apache.sysml.lops.LopProperties.ExecType; |
| import org.apache.sysml.lops.compile.JobType; |
| import org.apache.sysml.parser.Expression.*; |
| |
| |
| /** |
| * Lop to perform binary operation. Both inputs must be matrices or vectors. |
| * Example - A = B + C, where B and C are matrices or vectors. |
| */ |
| |
| public class Binary extends Lop |
| { |
| |
| public enum OperationTypes { |
| ADD, SUBTRACT, MULTIPLY, DIVIDE, MINUS1_MULTIPLY, MODULUS, INTDIV, MATMULT, |
| LESS_THAN, LESS_THAN_OR_EQUALS, GREATER_THAN, GREATER_THAN_OR_EQUALS, EQUALS, NOT_EQUALS, |
| AND, OR, |
| MAX, MIN, POW, SOLVE, NOTSUPPORTED |
| }; |
| |
| private OperationTypes operation; |
| private int numThreads = -1; |
| boolean isLeftTransposed; boolean isRightTransposed; // Used for GPU matmult operation |
| |
| /** |
| * Constructor to perform a binary operation. |
| * @param input |
| * @param op |
| */ |
| public Binary(Lop input1, Lop input2, OperationTypes op, DataType dt, ValueType vt, ExecType et) { |
| this(input1, input2, op, dt, vt, et, 1); |
| } |
| |
| public Binary(Lop input1, Lop input2, OperationTypes op, DataType dt, ValueType vt, ExecType et, int k) { |
| super(Lop.Type.Binary, dt, vt); |
| init(input1, input2, op, dt, vt, et); |
| numThreads = k; |
| } |
| |
| public Binary(Lop input1, Lop input2, OperationTypes op, DataType dt, ValueType vt, ExecType et, |
| boolean isLeftTransposed, boolean isRightTransposed) { |
| super(Lop.Type.Binary, dt, vt); |
| init(input1, input2, op, dt, vt, et); |
| this.isLeftTransposed = isLeftTransposed; |
| this.isRightTransposed = isRightTransposed; |
| } |
| |
| private void init(Lop input1, Lop input2, OperationTypes op, DataType dt, ValueType vt, ExecType et) |
| { |
| operation = op; |
| this.addInput(input1); |
| this.addInput(input2); |
| input1.addOutput(this); |
| input2.addOutput(this); |
| |
| boolean breaksAlignment = false; |
| boolean aligner = false; |
| boolean definesMRJob = false; |
| |
| if ( et == ExecType.MR ) { |
| lps.addCompatibility(JobType.GMR); |
| lps.addCompatibility(JobType.DATAGEN); |
| lps.addCompatibility(JobType.REBLOCK); |
| this.lps.setProperties( inputs, et, ExecLocation.Reduce, breaksAlignment, aligner, definesMRJob ); |
| } |
| else if ( et == ExecType.CP || et == ExecType.SPARK || et == ExecType.GPU ){ |
| lps.addCompatibility(JobType.INVALID); |
| this.lps.setProperties( inputs, et, ExecLocation.ControlProgram, breaksAlignment, aligner, definesMRJob ); |
| } |
| } |
| |
| @Override |
| public String toString() { |
| |
| return " Operation: " + operation; |
| |
| } |
| |
| /** |
| * method to get operation type |
| * @return |
| */ |
| |
| public OperationTypes getOperationType() |
| { |
| return operation; |
| } |
| |
| private String getOpcode() |
| { |
| return getOpcode( operation ); |
| } |
| |
| public static String getOpcode( OperationTypes op ) { |
| switch(op) { |
| /* Arithmetic */ |
| case ADD: |
| return "+"; |
| case SUBTRACT: |
| return "-"; |
| case MULTIPLY: |
| return "*"; |
| case DIVIDE: |
| return "/"; |
| case MODULUS: |
| return "%%"; |
| case INTDIV: |
| return "%/%"; |
| case MATMULT: |
| return "ba+*"; |
| case MINUS1_MULTIPLY: |
| return "1-*"; |
| |
| /* Relational */ |
| case LESS_THAN: |
| return "<"; |
| case LESS_THAN_OR_EQUALS: |
| return "<="; |
| case GREATER_THAN: |
| return ">"; |
| case GREATER_THAN_OR_EQUALS: |
| return ">="; |
| case EQUALS: |
| return "=="; |
| case NOT_EQUALS: |
| return "!="; |
| |
| /* Boolean */ |
| case AND: |
| return "&&"; |
| case OR: |
| return "||"; |
| |
| |
| /* Builtin Functions */ |
| case MIN: |
| return "min"; |
| case MAX: |
| return "max"; |
| case POW: |
| return "^"; |
| |
| case SOLVE: |
| return "solve"; |
| |
| default: |
| throw new UnsupportedOperationException("Instruction is not defined for Binary operation: " + op); |
| } |
| } |
| |
| @Override |
| public String getInstructions(String input1, String input2, String output) |
| throws LopsException |
| { |
| StringBuilder sb = new StringBuilder(); |
| sb.append( getExecType() ); |
| sb.append( OPERAND_DELIMITOR ); |
| sb.append( getOpcode() ); |
| sb.append( OPERAND_DELIMITOR ); |
| |
| sb.append ( getInputs().get(0).prepInputOperand(input1)); |
| sb.append( OPERAND_DELIMITOR ); |
| |
| sb.append ( getInputs().get(1).prepInputOperand(input2)); |
| sb.append( OPERAND_DELIMITOR ); |
| |
| sb.append( this.prepOutputOperand(output)); |
| |
| //append degree of parallelism for matrix multiplications |
| if( operation == OperationTypes.MATMULT && getExecType()==ExecType.CP ) { |
| sb.append( OPERAND_DELIMITOR ); |
| sb.append( numThreads ); |
| } |
| else if( operation == OperationTypes.MATMULT && getExecType()==ExecType.GPU ) { |
| sb.append( OPERAND_DELIMITOR ); |
| sb.append( isLeftTransposed ); |
| sb.append( OPERAND_DELIMITOR ); |
| sb.append( isRightTransposed ); |
| } |
| |
| return sb.toString(); |
| } |
| |
| @Override |
| public String getInstructions(int input_index1, int input_index2, int output_index) throws LopsException |
| { |
| return getInstructions(input_index1+"", input_index2+"", output_index+""); |
| } |
| } |