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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.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());
}
}