| /* |
| * 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.IndexFunction; |
| import org.apache.sysds.runtime.functionobjects.ReduceCol; |
| import org.apache.sysds.runtime.functionobjects.ReduceRow; |
| 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.operators.AggregateUnaryOperator; |
| import org.apache.sysds.runtime.matrix.operators.Operator; |
| import org.apache.sysds.utils.GPUStatistics; |
| |
| /** |
| * Implements aggregate unary instructions for CUDA |
| */ |
| public class AggregateUnaryGPUInstruction extends GPUInstruction { |
| private CPOperand _input1 = null; |
| private CPOperand _output = null; |
| |
| private AggregateUnaryGPUInstruction(Operator op, CPOperand in1, CPOperand out, String opcode, String istr) { |
| super(op, opcode, istr); |
| _gputype = GPUINSTRUCTION_TYPE.AggregateUnary; |
| _input1 = in1; |
| _output = out; |
| } |
| |
| public static AggregateUnaryGPUInstruction parseInstruction(String str ) { |
| String[] parts = InstructionUtils.getInstructionPartsWithValueType(str); |
| String opcode = parts[0]; |
| CPOperand in1 = new CPOperand(parts[1]); |
| CPOperand out = new CPOperand(parts[2]); |
| |
| // This follows logic similar to AggregateUnaryCPInstruction. |
| // nrow, ncol & length should either read or refresh metadata |
| Operator aggop = null; |
| if(opcode.equalsIgnoreCase("nrow") || opcode.equalsIgnoreCase("ncol") || opcode.equalsIgnoreCase("length")) { |
| throw new DMLRuntimeException("nrow, ncol & length should not be compiled as GPU instructions!"); |
| } else { |
| aggop = InstructionUtils.parseBasicAggregateUnaryOperator(opcode); |
| } |
| return new AggregateUnaryGPUInstruction(aggop, in1, out, opcode, str); |
| } |
| |
| @Override |
| public void processInstruction(ExecutionContext ec) { |
| GPUStatistics.incrementNoOfExecutedGPUInst(); |
| |
| String opcode = getOpcode(); |
| |
| // nrow, ncol & length should either read or refresh metadata |
| if(opcode.equalsIgnoreCase("nrow") || opcode.equalsIgnoreCase("ncol") || opcode.equalsIgnoreCase("length")) { |
| throw new DMLRuntimeException("nrow, ncol & length should not be compiled as GPU instructions!"); |
| } |
| |
| //get inputs |
| MatrixObject in1 = getMatrixInputForGPUInstruction(ec, _input1.getName()); |
| |
| int rlen = (int)in1.getNumRows(); |
| int clen = (int)in1.getNumColumns(); |
| |
| IndexFunction indexFunction = ((AggregateUnaryOperator) _optr).indexFn; |
| if (indexFunction instanceof ReduceRow){ // COL{SUM, MAX...} |
| ec.setMetaData(_output.getName(), 1, clen); |
| } else if (indexFunction instanceof ReduceCol) { // ROW{SUM, MAX,...} |
| ec.setMetaData(_output.getName(), rlen, 1); |
| } |
| |
| LibMatrixCUDA.unaryAggregate(ec, ec.getGPUContext(0), getExtendedOpcode(), in1, _output.getName(), (AggregateUnaryOperator)_optr); |
| |
| //release inputs/outputs |
| ec.releaseMatrixInputForGPUInstruction(_input1.getName()); |
| |
| // If the unary aggregate is a row reduction or a column reduction, it results in a vector |
| // which needs to be released. Otherwise a scala is produced and it is copied back to the host |
| // and set in the execution context by invoking the setScalarOutput |
| if (indexFunction instanceof ReduceRow || indexFunction instanceof ReduceCol) { |
| ec.releaseMatrixOutputForGPUInstruction(_output.getName()); |
| } |
| } |
| } |