/***************************************************************************
* EgidioGranuleCell_TimeDriven_GPU.cu *
* ------------------- *
* copyright : (C) 2013 by Francisco Naveros *
* email : fnaveros@atc.ugr.es *
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 3 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
#include "../../include/neuron_model/EgidioGranuleCell_TimeDriven_GPU.h"
#include "../../include/neuron_model/EgidioGranuleCell_TimeDriven_GPU2.h"
#include "../../include/neuron_model/VectorNeuronState.h"
#include "../../include/neuron_model/VectorNeuronState_GPU.h"
#include <iostream>
#include <cmath>
#include <string>
#include "../../include/spike/EDLUTFileException.h"
#include "../../include/spike/Neuron.h"
#include "../../include/spike/InternalSpike.h"
#include "../../include/spike/PropagatedSpike.h"
#include "../../include/spike/Interconnection.h"
#include "../../include/simulation/Utils.h"
#include "../../include/openmp/openmp.h"
#include "../../include/cudaError.h"
//Library for CUDA
#include <helper_cuda.h>
void EgidioGranuleCell_TimeDriven_GPU::LoadNeuronModel(string ConfigFile) throw (EDLUTFileException){
FILE *fh;
long Currentline = 0L;
fh=fopen(ConfigFile.c_str(),"rt");
if(fh){
Currentline=1L;
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXNa_f)==1){
skip_comments(fh,Currentline);
if (fscanf(fh,"%f",&this->gMAXNa_r)==1){
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXNa_p)==1){
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXK_V)==1){
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXK_A)==1){
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXK_IR)==1){
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXK_Ca)==1){
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXCa)==1){
skip_comments(fh,Currentline);
if(fscanf(fh,"%f",&this->gMAXK_sl)==1){
skip_comments(fh,Currentline);
this->InitialState = (VectorNeuronState_GPU *) new VectorNeuronState_GPU(17);
}
//NEW CODE------------------------------------------------------------------------------
else {
throw EDLUTFileException(13,60,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,61,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,62,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,63,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,64,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,65,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,66,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,67,3,1,Currentline);
}
} else {
throw EDLUTFileException(13,68,3,1,Currentline);
}
//-------------------------------------------------------------------------------------
//INTEGRATION METHOD
this->integrationMethod_GPU=LoadIntegrationMethod_GPU::loadIntegrationMethod_GPU(fh, &Currentline, N_NeuronStateVariables, N_DifferentialNeuronState, N_TimeDependentNeuronState);
//TIME DRIVEN STEP
this->TimeDrivenStep_GPU = LoadTimeEvent_GPU::loadTimeEvent_GPU(fh, &Currentline);
}
}
void EgidioGranuleCell_TimeDriven_GPU::SynapsisEffect(int index, VectorNeuronState_GPU * state, Interconnection * InputConnection){
state->AuxStateCPU[InputConnection->GetType()*state->GetSizeState() + index]+=1e-9f*InputConnection->GetWeight();
}
EgidioGranuleCell_TimeDriven_GPU::EgidioGranuleCell_TimeDriven_GPU(string NeuronTypeID, string NeuronModelID): TimeDrivenNeuronModel_GPU(NeuronTypeID, NeuronModelID), gMAXNa_f(0.0f), gMAXNa_r(0.0f), gMAXNa_p(0.0f), gMAXK_V(0.0f), gMAXK_A(0.0f), gMAXK_IR(0.0f), gMAXK_Ca(0.0f),
gMAXCa(0.0f), gMAXK_sl(0.0f), gLkg1(5.68e-5f), gLkg2(2.17e-5f), VNa(87.39f), VK(-84.69f), VLkg1(-58.0f), VLkg2(-65.0f), V0_xK_Ai(-46.7f),
K_xK_Ai(-19.8f), V0_yK_Ai(-78.8f), K_yK_Ai(8.4f), V0_xK_sli(-30.0f), B_xK_sli(6.0f), F(96485.309f), A(1e-04f), d(0.2f), betaCa(1.5f),
Ca0(1e-04f), R(8.3134f), cao(2.0f), Cm(1.0e-3f), temper(30.0f), Q10_20 ( pow(3,((temper-20.0f)/10.0f))), Q10_22 ( pow(3,((temper-22.0f)/10.0f))),
Q10_30 ( pow(3,((temper-30.0f)/10.0f))), Q10_6_3 ( pow(3,((temper-6.3f)/10.0f))), /*I_inj_abs(11e-12f)*/I_inj_abs(0.0f),
I_inj(-I_inj_abs*1000.0f/299.26058e-8f), eexc(0.0f), einh(-80.0f), texc(0.5f), tinh(10.0f), vthr(-0.25f){
}
EgidioGranuleCell_TimeDriven_GPU::~EgidioGranuleCell_TimeDriven_GPU(void){
DeleteClassGPU2();
}
void EgidioGranuleCell_TimeDriven_GPU::LoadNeuronModel() throw (EDLUTFileException){
this->LoadNeuronModel(this->GetModelID()+".cfg");
}
VectorNeuronState * EgidioGranuleCell_TimeDriven_GPU::InitializeState(){
return this->GetVectorNeuronState();
}
InternalSpike * EgidioGranuleCell_TimeDriven_GPU::ProcessInputSpike(Interconnection * inter, Neuron * target, double time){
int indexGPU =target->GetIndex_VectorNeuronState();
VectorNeuronState_GPU * state = (VectorNeuronState_GPU *) this->InitialState;
// Add the effect of the input spike
this->SynapsisEffect(target->GetIndex_VectorNeuronState(), state, inter);
return 0;
}
__global__ void EgidioGranuleCell_TimeDriven_GPU_UpdateState(EgidioGranuleCell_TimeDriven_GPU2 ** NeuronModel_GPU2, double CurrentTime){
(*NeuronModel_GPU2)->UpdateState(CurrentTime);
}
bool EgidioGranuleCell_TimeDriven_GPU::UpdateState(int index, VectorNeuronState * State, double CurrentTime){
VectorNeuronState_GPU *state = (VectorNeuronState_GPU *) State;
if(prop.canMapHostMemory){
EgidioGranuleCell_TimeDriven_GPU_UpdateState<<<N_block,N_thread>>>(NeuronModel_GPU2, CurrentTime);
}else{
HANDLE_ERROR(cudaMemcpy(state->AuxStateGPU,state->AuxStateCPU,4*state->SizeStates*sizeof(float),cudaMemcpyHostToDevice));
EgidioGranuleCell_TimeDriven_GPU_UpdateState<<<N_block,N_thread>>>(NeuronModel_GPU2, CurrentTime);
HANDLE_ERROR(cudaMemcpy(state->InternalSpikeCPU,state->InternalSpikeGPU,state->SizeStates*sizeof(bool),cudaMemcpyDeviceToHost));
}
if(this->GetVectorNeuronState()->Get_Is_Monitored()){
HANDLE_ERROR(cudaMemcpy(state->VectorNeuronStates,state->VectorNeuronStates_GPU,state->GetNumberOfVariables()*state->SizeStates*sizeof(float),cudaMemcpyDeviceToHost));
HANDLE_ERROR(cudaMemcpy(state->LastUpdate,state->LastUpdateGPU,state->SizeStates*sizeof(double),cudaMemcpyDeviceToHost));
HANDLE_ERROR(cudaMemcpy(state->LastSpikeTime,state->LastSpikeTimeGPU,state->SizeStates*sizeof(double),cudaMemcpyDeviceToHost));
}
HANDLE_ERROR(cudaEventRecord(stop, 0));
HANDLE_ERROR(cudaEventSynchronize(stop));
memset(state->AuxStateCPU,0,N_TimeDependentNeuronState*state->SizeStates*sizeof(float));
return false;
}
ostream & EgidioGranuleCell_TimeDriven_GPU::PrintInfo(ostream & out){
return out;
}
void EgidioGranuleCell_TimeDriven_GPU::InitializeStates(int N_neurons, int OpenMPQueueIndex){
//Select the correnpondent device.
HANDLE_ERROR(cudaSetDevice(GPUsIndex[OpenMPQueueIndex % NumberOfGPUs]));
HANDLE_ERROR(cudaEventCreate(&stop));
HANDLE_ERROR(cudaGetDeviceProperties( &prop, GPUsIndex[OpenMPQueueIndex % NumberOfGPUs]));
VectorNeuronState_GPU * state = (VectorNeuronState_GPU *) this->InitialState;
//Initial State
float xNa_f=0.00047309535f;
float yNa_f=1.0f;
float xNa_r=0.00013423511f;
float yNa_r=0.96227829f;
float xNa_p=0.00050020111f;
float xK_V=0.010183001f;
float xK_A=0.15685486f;
float yK_A=0.53565367f;
float xK_IR=0.37337035f;
float xK_Ca=0.00012384122f;
float xCa=0.0021951104f;
float yCa=0.89509747f;
float xK_sl=0.00024031171f;
float Ca=Ca0;
float V=-80.0f;
float gexc=0.0f;
float ginh=0.0f;
//Initialize neural state variables.
float initialization[] = {xNa_f,yNa_f,xNa_r,yNa_r,xNa_p,xK_V,xK_A,yK_A,xK_IR,xK_Ca,xCa,yCa,xK_sl,Ca,V,gexc,ginh};
state->InitializeStatesGPU(N_neurons, initialization, N_TimeDependentNeuronState, prop);
//INITIALIZE CLASS IN GPU
this->InitializeClassGPU2(N_neurons);
InitializeVectorNeuronState_GPU2();
}
__global__ void EgidioGranuleCell_TimeDriven_GPU2_InitializeClassGPU2(EgidioGranuleCell_TimeDriven_GPU2 ** NeuronModel_GPU2, double new_elapsed_time,
float gMAXNa_f, float gMAXNa_r, float gMAXNa_p, float gMAXK_V,
float gMAXK_A,float gMAXK_IR,float gMAXK_Ca,float gMAXCa,float gMAXK_sl, char const* integrationName, int N_neurons, void ** Buffer_GPU){
if(blockIdx.x==0 && threadIdx.x==0){
(*NeuronModel_GPU2) = new EgidioGranuleCell_TimeDriven_GPU2(new_elapsed_time, gMAXNa_f, gMAXNa_r, gMAXNa_p, gMAXK_V,
gMAXK_A,gMAXK_IR,gMAXK_Ca,gMAXCa,gMAXK_sl,integrationName, N_neurons, Buffer_GPU);
}
}
void EgidioGranuleCell_TimeDriven_GPU::InitializeClassGPU2(int N_neurons){
cudaMalloc(&NeuronModel_GPU2, sizeof(EgidioGranuleCell_TimeDriven_GPU2 **));
char * integrationNameGPU;
cudaMalloc((void **)&integrationNameGPU,32*4);
HANDLE_ERROR(cudaMemcpy(integrationNameGPU,integrationMethod_GPU->GetType(),32*4,cudaMemcpyHostToDevice));
this->N_thread = 128;
this->N_block=prop.multiProcessorCount*4;
if((N_neurons+N_thread-1)/N_thread < N_block){
N_block = (N_neurons+N_thread-1)/N_thread;
}
int Total_N_thread=N_thread*N_block;
integrationMethod_GPU->InitializeMemoryGPU(N_neurons, Total_N_thread);
EgidioGranuleCell_TimeDriven_GPU2_InitializeClassGPU2<<<1,1>>>(NeuronModel_GPU2, TimeDrivenStep_GPU, gMAXNa_f, gMAXNa_r, gMAXNa_p, gMAXK_V,
gMAXK_A,gMAXK_IR,gMAXK_Ca,gMAXCa,gMAXK_sl,integrationNameGPU, N_neurons, integrationMethod_GPU->Buffer_GPU);
cudaFree(integrationNameGPU);
}
__global__ void initializeVectorNeuronState_GPU2(EgidioGranuleCell_TimeDriven_GPU2 ** NeuronModel_GPU2, float * AuxStateGPU, float * StateGPU, double * LastUpdateGPU, double * LastSpikeTimeGPU, bool * InternalSpikeGPU, int SizeStates){
if(blockIdx.x==0 && threadIdx.x==0){
(*NeuronModel_GPU2)->InitializeVectorNeuronState_GPU2(AuxStateGPU, StateGPU, LastUpdateGPU, LastSpikeTimeGPU, InternalSpikeGPU, SizeStates);
}
}
void EgidioGranuleCell_TimeDriven_GPU::InitializeVectorNeuronState_GPU2(){
VectorNeuronState_GPU *state = (VectorNeuronState_GPU *) InitialState;
initializeVectorNeuronState_GPU2<<<1,1>>>(NeuronModel_GPU2, state->AuxStateGPU, state->VectorNeuronStates_GPU, state->LastUpdateGPU, state->LastSpikeTimeGPU, state->InternalSpikeGPU, state->SizeStates);
}
__global__ void DeleteClass_GPU2(EgidioGranuleCell_TimeDriven_GPU2 ** NeuronModel_GPU2){
if(blockIdx.x==0 && threadIdx.x==0){
delete (*NeuronModel_GPU2);
}
}
void EgidioGranuleCell_TimeDriven_GPU::DeleteClassGPU2(){
DeleteClass_GPU2<<<1,1>>>(NeuronModel_GPU2);
cudaFree(NeuronModel_GPU2);
}
int EgidioGranuleCell_TimeDriven_GPU::CheckSynapseTypeNumber(int Type){
if(Type<N_TimeDependentNeuronState && Type>=0){
return Type;
}else{
cout<<"Neuron model "<<this->GetTypeID()<<", "<<this->GetModelID()<<" does not support input synapses of type "<<Type<<endl;
return 0;
}
}