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main.cpp
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main.cpp
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/*******************************************************************************
* Copyright (c) 2015-2017
* School of Electrical, Computer and Energy Engineering, Arizona State University
* PI: Prof. Shimeng Yu
* All rights reserved.
*
* This source code is part of NeuroSim - a device-circuit-algorithm framework to benchmark
* neuro-inspired architectures with synaptic devices(e.g., SRAM and emerging non-volatile memory).
* Copyright of the model is maintained by the developers, and the model is distributed under
* the terms of the Creative Commons Attribution-NonCommercial 4.0 International Public License
* http://creativecommons.org/licenses/by-nc/4.0/legalcode.
* The source code is free and you can redistribute and/or modify it
* by providing that the following conditions are met:
*
* 1) Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* 2) Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
* Developer list:
* Pai-Yu Chen Email: pchen72 at asu dot edu
*
* Xiaochen Peng Email: xpeng15 at asu dot edu
********************************************************************************/
#include <cstdio>
#include <iostream>
#include <random>
#include <vector>
#include "Cell.h"
#include "Array.h"
#include "formula.h"
#include "NeuroSim.h"
#include "Param.h"
#include "IO.h"
#include "Train.h"
#include "Test.h"
#include "Mapping.h"
#include "Definition.h"
int main() {
gen.seed(0);
/* Load in MNIST data */
ReadTrainingDataFromFile("patch60000_train.txt", "label60000_train.txt");
ReadTestingDataFromFile("patch10000_test.txt", "label10000_test.txt");
/* Initialization of synaptic array from input to hidden layer */
//arrayIH->Initialization<IdealDevice>();
arrayIH->Initialization<RealDevice>();
//arrayIH->Initialization<MeasuredDevice>();
//arrayIH->Initialization<SRAM>(param->numWeightBit);
//arrayIH->Initialization<DigitalNVM>(param->numWeightBit);
/* Initialization of synaptic array from hidden to output layer */
//arrayHO->Initialization<IdealDevice>();
arrayHO->Initialization<RealDevice>();
//arrayHO->Initialization<MeasuredDevice>();
//arrayHO->Initialization<SRAM>(param->numWeightBit);
//arrayHO->Initialization<DigitalNVM>(param->numWeightBit);
/* Initialization of NeuroSim synaptic cores */
param->relaxArrayCellWidth = 0;
NeuroSimSubArrayInitialize(subArrayIH, arrayIH, inputParameterIH, techIH, cellIH);
param->relaxArrayCellWidth = 1;
NeuroSimSubArrayInitialize(subArrayHO, arrayHO, inputParameterHO, techHO, cellHO);
/* Calculate synaptic core area */
NeuroSimSubArrayArea(subArrayIH);
NeuroSimSubArrayArea(subArrayHO);
/* Calculate synaptic core standby leakage power */
NeuroSimSubArrayLeakagePower(subArrayIH);
NeuroSimSubArrayLeakagePower(subArrayHO);
/* Initialize the neuron peripheries */
NeuroSimNeuronInitialize(subArrayIH, inputParameterIH, techIH, cellIH, adderIH, muxIH, muxDecoderIH, dffIH);
NeuroSimNeuronInitialize(subArrayHO, inputParameterHO, techHO, cellHO, adderHO, muxHO, muxDecoderHO, dffHO);
/* Calculate the area and standby leakage power of neuron peripheries below subArrayIH */
double heightNeuronIH, widthNeuronIH;
NeuroSimNeuronArea(subArrayIH, adderIH, muxIH, muxDecoderIH, dffIH, &heightNeuronIH, &widthNeuronIH);
double leakageNeuronIH = NeuroSimNeuronLeakagePower(subArrayIH, adderIH, muxIH, muxDecoderIH, dffIH);
/* Calculate the area and standby leakage power of neuron peripheries below subArrayHO */
double heightNeuronHO, widthNeuronHO;
NeuroSimNeuronArea(subArrayHO, adderHO, muxHO, muxDecoderHO, dffHO, &heightNeuronHO, &widthNeuronHO);
double leakageNeuronHO = NeuroSimNeuronLeakagePower(subArrayHO, adderHO, muxHO, muxDecoderHO, dffHO);
/* Print the area of synaptic core and neuron peripheries */
double totalSubArrayArea = subArrayIH->usedArea + subArrayHO->usedArea;
double totalNeuronAreaIH = adderIH.area + muxIH.area + muxDecoderIH.area + dffIH.area;
double totalNeuronAreaHO = adderHO.area + muxHO.area + muxDecoderHO.area + dffHO.area;
printf("Total SubArray (synaptic core) area=%.4e m^2\n", totalSubArrayArea);
printf("Total Neuron (neuron peripheries) area=%.4e m^2\n", totalNeuronAreaIH + totalNeuronAreaHO);
printf("Total area=%.4e m^2\n", totalSubArrayArea + totalNeuronAreaIH + totalNeuronAreaHO);
/* Print the standby leakage power of synaptic core and neuron peripheries */
printf("Leakage power of subArrayIH is : %.4e W\n", subArrayIH->leakage);
printf("Leakage power of subArrayHO is : %.4e W\n", subArrayHO->leakage);
printf("Leakage power of NeuronIH is : %.4e W\n", leakageNeuronIH);
printf("Leakage power of NeuronHO is : %.4e W\n", leakageNeuronHO);
printf("Total leakage power of subArray is : %.4e W\n", subArrayIH->leakage + subArrayHO->leakage);
printf("Total leakage power of Neuron is : %.4e W\n", leakageNeuronIH + leakageNeuronHO);
/* Initialize weights and map weights to conductances for hardware implementation */
WeightInitialize();
if (param->useHardwareInTraining) { WeightToConductance(); }
srand(0); // Pseudorandom number seed
for (int i=1; i<=param->totalNumEpochs/param->interNumEpochs; i++) {
Train(param->numTrainImagesPerEpoch, param->interNumEpochs);
if (!param->useHardwareInTraining && param->useHardwareInTestingFF) { WeightToConductance(); }
Validate();
printf("Accuracy at %d epochs is : %.2f%\n", i*param->interNumEpochs, (double)correct/param->numMnistTestImages*100);
/* Here the performance metrics of subArray also includes that of neuron peripheries (see Train.cpp and Test.cpp) */
printf("\tRead latency=%.4e s\n", subArrayIH->readLatency + subArrayHO->readLatency);
printf("\tWrite latency=%.4e s\n", subArrayIH->writeLatency + subArrayHO->writeLatency);
printf("\tRead energy=%.4e J\n", arrayIH->readEnergy + subArrayIH->readDynamicEnergy + arrayHO->readEnergy + subArrayHO->readDynamicEnergy);
printf("\tWrite energy=%.4e J\n", arrayIH->writeEnergy + subArrayIH->writeDynamicEnergy + arrayHO->writeEnergy + subArrayHO->writeDynamicEnergy);
}
printf("\n");
return 0;
}