poisson_rate.cpp

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/*
 * Copyright (c) 2014 Regents of the University of California. All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided 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.
 *
 * 3. The names of its contributors may not be used to endorse or promote
 *    products derived from this software without specific prior written
 *    permission.
 *
 * 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 OWNER 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.
 *
 * *********************************************************************************************** *
 * CARLsim
 * created by:      (MDR) Micah Richert, (JN) Jayram M. Nageswaran
 * maintained by:   (MA) Mike Avery <averym@uci.edu>, (MB) Michael Beyeler <mbeyeler@uci.edu>,
 *                  (KDC) Kristofor Carlson <kdcarlso@uci.edu>
 *                  (TSC) Ting-Shuo Chou <tingshuc@uci.edu>
 *
 * CARLsim6: LN, JX, KC, KW
 *
 * CARLsim available from http://socsci.uci.edu/~jkrichma/CARLsim/
 * Ver 6/13/2016
 */
#include <cassert> // assert
#include <cstdio>  // printf
#include <cstring> // string, memset
#include <cstdlib> // malloc, free, rand

#include <poisson_rate.h>
#include <carlsim_definitions.h> // ALL
#ifndef __NO_CUDA__
    #include <cuda_version_control.h>
#endif



class PoissonRate::Impl {
public:
    // +++++ PUBLIC METHODS +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //
    Impl(int nNeur, bool onGPU): nNeur_(nNeur), onGPU_(onGPU) {
        assert(nNeur>0);

        h_rates_ = NULL;
        d_rates_ = NULL;

        if (onGPU) {
#ifndef __NO_CUDA__
            // allocate rates on device and set to zero
            CUDA_CHECK_ERRORS(cudaMalloc((void**)&d_rates_, sizeof(float)*nNeur));
            CUDA_CHECK_ERRORS(cudaMemset(d_rates_, 0, sizeof(float)*nNeur));
#else
            printf("Cannot use onGPU when compiled without CUDA library.\n");
            assert(false);
#endif
        } else {
            // allocate rates on host and set to zero
            h_rates_ = new float[nNeur];
            memset(h_rates_, 0, sizeof(float)*nNeur);
        }
    }

    ~Impl() {
        if (isOnGPU()) {
#ifndef __NO_CUDA__
            // clean up device
            if (d_rates_!=NULL) {
                CUDA_CHECK_ERRORS(cudaFree(d_rates_)); // free memory
                d_rates_ = NULL;
            }
#endif
        } else {
            // clean up host
            if (h_rates_!=NULL) {
                delete[] h_rates_;
            }
            h_rates_ = NULL;
        }
    }

    int getNumNeurons() {
        return nNeur_;
    }

    // get rate of certain neuron
    float getRate(int neurId) {
        assert(neurId>=0 && neurId<getNumNeurons());

        if (isOnGPU()) {
            // get data from device (might have kernel launch overhead because float is small)
            float h_d_rate = 0.0f;
//Fix LN20210211 
// warning C4715: 'PoissonRate::Impl::getRate': not all control paths return a value
#ifndef __NO_CUDA__
            CUDA_CHECK_ERRORS( cudaMemcpy(&h_d_rate, &(d_rates_[neurId]), sizeof(float), cudaMemcpyDeviceToHost) );
#endif
            return h_d_rate;
        } else {
            // data is on host
            return h_rates_[neurId];
        }
    }

    // get all rates as vector
    std::vector<float> getRates() {
        if (isOnGPU()) {
//Fix LN20210211 
// warning C4715: 'PoissonRate::Impl::getRate': not all control paths return a value
#ifndef __NO_CUDA__
            // get data from device
            float *h_d_rates = (float*)malloc(sizeof(float)*getNumNeurons());
            CUDA_CHECK_ERRORS( cudaMemcpy(h_d_rates, d_rates_, sizeof(float)*getNumNeurons(), cudaMemcpyDeviceToHost) );

            // copy data to vec
            std::vector<float> rates(h_d_rates, h_d_rates + getNumNeurons());
            free(h_d_rates);

            return rates;
#else
            return std::vector<float>(); // fix compiler warning C4715, this code shall be never reached
#endif
        } else {
            // data is on host
            std::vector<float> rates(h_rates_, h_rates_ + getNumNeurons()); // copy to vec
            return rates;
        }
    }

    // get pointer to rate array on CPU
    float* getRatePtrCPU() {
        assert(!isOnGPU());
        return h_rates_;
    }

    // get pointer to rate array on GPU
    float* getRatePtrGPU() {
        assert(isOnGPU());
        return d_rates_;
    }

    bool isOnGPU() {
        return onGPU_;
    }

    // set rate of a specific neuron
    void setRate(int neurId, float rate) {
        if (neurId==ALL) {
            setRates(rate);
        } else {
            assert(neurId>=0 && neurId<getNumNeurons());
            if (isOnGPU()) {
#ifndef __NO_CUDA__
                // copy float to device (might have kernel launch overhead because float is small)
                CUDA_CHECK_ERRORS( cudaMemcpy(&(d_rates_[neurId]), &rate, sizeof(float), cudaMemcpyHostToDevice) );
#endif
            } else {
                // set float in host array
                h_rates_[neurId] = rate;
            }
        }
    }

    // set rate of all neurons to same value
    void setRates(float rate) {
        assert(rate>=0.0f);

        std::vector<float> rates(getNumNeurons(), rate);
        setRates(rates);
    }

    // set rates with vector
    void setRates(const std::vector<float>& rate) {
        assert(rate.size()==getNumNeurons());

        if (isOnGPU()) {
#ifndef __NO_CUDA__
            // copy to device
            float *h_rates_arr = new float[getNumNeurons()];
            std::copy(rate.begin(), rate.end(), h_rates_arr);
            CUDA_CHECK_ERRORS( cudaMemcpy(d_rates_, h_rates_arr, sizeof(float)*getNumNeurons(), cudaMemcpyHostToDevice) );
            delete[] h_rates_arr;
#endif
        } else {
            // set host array
            std::copy(rate.begin(), rate.end(), h_rates_);
        }
    }


private:
    // +++++ PRIVATE METHODS ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //

    // +++++ PRIVATE STATIC PROPERTIES ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //

    // +++++ PRIVATE PROPERTIES +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //

    float *h_rates_;    
    float *d_rates_;    
    const int nNeur_;   
    const bool onGPU_;  
};


// ****************************************************************************************************************** //
// POISSONRATE API IMPLEMENTATION
// ****************************************************************************************************************** //

// create and destroy a pImpl instance
PoissonRate::PoissonRate(int nNeur, bool onGPU) : _impl( new Impl(nNeur, onGPU) ) {}
PoissonRate::~PoissonRate() { delete _impl; }

int PoissonRate::getNumNeurons() { return _impl->getNumNeurons(); }
float PoissonRate::getRate(int neurId) { return _impl->getRate(neurId); }
std::vector<float> PoissonRate::getRates() { return _impl->getRates(); }
float* PoissonRate::getRatePtrCPU() { return _impl->getRatePtrCPU(); }
float* PoissonRate::getRatePtrGPU() { return _impl->getRatePtrGPU(); }
bool PoissonRate::isOnGPU() { return _impl->isOnGPU(); }
void PoissonRate::setRate(int neurId, float rate) { _impl->setRate(neurId, rate); }
void PoissonRate::setRates(float rate) { _impl->setRates(rate); }
void PoissonRate::setRates(const std::vector<float>& rates) { _impl->setRates(rates); }