| /* |
| * 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.commons.logging.Log; |
| import org.apache.commons.logging.LogFactory; |
| 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.stat.Timing; |
| import org.apache.sysds.runtime.instructions.cp.CPOperand; |
| import org.apache.sysds.runtime.matrix.data.LibMatrixCUDA; |
| import org.apache.sysds.runtime.matrix.data.LibMatrixCuDNN; |
| import org.apache.sysds.runtime.matrix.operators.Operator; |
| import org.apache.sysds.utils.GPUStatistics; |
| |
| public class MatrixBuiltinGPUInstruction extends BuiltinUnaryGPUInstruction { |
| private static final Log LOG = LogFactory.getLog(MatrixBuiltinGPUInstruction.class.getName()); |
| |
| protected MatrixBuiltinGPUInstruction(Operator op, CPOperand in, CPOperand out, String opcode, String instr) { |
| super(op, in, out, 1, opcode, instr); |
| _gputype = GPUINSTRUCTION_TYPE.BuiltinUnary; |
| } |
| |
| @Override |
| public void processInstruction(ExecutionContext ec) { |
| GPUStatistics.incrementNoOfExecutedGPUInst(); |
| |
| String opcode = getOpcode(); |
| MatrixObject mat = getMatrixInputForGPUInstruction(ec, _input.getName()); |
| if(opcode != "ucumk+*") |
| ec.setMetaData(_output.getName(), mat.getNumRows(), mat.getNumColumns()); |
| |
| Timing time = new Timing(true); |
| switch(opcode) { |
| case "exp": |
| LibMatrixCUDA.exp(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "sqrt": |
| LibMatrixCUDA.sqrt(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "log": |
| LibMatrixCUDA.log(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "round": |
| LibMatrixCUDA.round(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "floor": |
| LibMatrixCUDA.floor(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "ceil": |
| LibMatrixCUDA.ceil(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "abs": |
| LibMatrixCUDA.abs(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "sin": |
| LibMatrixCUDA.sin(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "cos": |
| LibMatrixCUDA.cos(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "tan": |
| LibMatrixCUDA.tan(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "sinh": |
| LibMatrixCUDA.sinh(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "cosh": |
| LibMatrixCUDA.cosh(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "tanh": |
| LibMatrixCUDA.tanh(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "asin": |
| LibMatrixCUDA.asin(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "acos": |
| LibMatrixCUDA.acos(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "atan": |
| LibMatrixCUDA.atan(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "sign": |
| LibMatrixCUDA.sign(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "sigmoid": |
| LibMatrixCUDA.sigmoid(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "softmax": |
| LibMatrixCuDNN.softmax(ec, ec.getGPUContext(0), getExtendedOpcode(), mat, _output.getName()); break; |
| case "ucumk+": |
| LibMatrixCUDA.cumulativeScan(ec, ec.getGPUContext(0), getExtendedOpcode(), "cumulative_sum", mat, |
| _output.getName()); |
| break; |
| case "ucum*": |
| LibMatrixCUDA.cumulativeScan(ec, ec.getGPUContext(0), getExtendedOpcode(), "cumulative_prod", mat, |
| _output.getName()); |
| break; |
| case "ucumk+*": |
| ec.setMetaData(_output.getName(), mat.getNumRows(), 1); |
| LibMatrixCUDA.cumulativeSumProduct(ec, ec.getGPUContext(0), getExtendedOpcode(), "cumulative_sum_prod", |
| mat, _output.getName()); |
| break; |
| case "ucummin": |
| LibMatrixCUDA.cumulativeScan(ec, ec.getGPUContext(0), getExtendedOpcode(), "cumulative_min", mat, |
| _output.getName()); |
| break; |
| case "ucummax": |
| LibMatrixCUDA.cumulativeScan(ec, ec.getGPUContext(0), getExtendedOpcode(), "cumulative_max", mat, |
| _output.getName()); |
| break; |
| default: |
| throw new DMLRuntimeException("Unsupported GPU operator:" + opcode); |
| } |
| |
| if(LOG.isTraceEnabled()) |
| { |
| double duration = time.stop(); |
| LOG.trace("processInstruction() " + getExtendedOpcode() + " executed in " + duration + "ms."); |
| } |
| |
| ec.releaseMatrixInputForGPUInstruction(_input.getName()); |
| ec.releaseMatrixOutputForGPUInstruction(_output.getName()); |
| } |
| } |