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#ifndef iAN34Y9CxgHgVUyhhdYpI8Ynza8
#define iAN34Y9CxgHgVUyhhdYpI8Ynza8
#include <iostream>
#include <sstream>
#include <string>
#include <boost/type_traits/is_same.hpp>
#include "checkpoint.hpp"
#include "index_spike.hpp"
#include "property_instance.hpp"
#include "simlimits.hpp"
#include "template_helpers.hpp"
namespace PLA_Debug_Space_Impl {
template <class Quant>
struct PLA_Debug_Space_Quant2Num;
// PLA template
struct PLA_Debug_Space {
// action types & consts
typedef Void result_t;
template<typename _ContextProp, bool doWriteResults> struct local_state_t {
typedef _ContextProp prop;
static const bool write = doWriteResults;
};
// action state
result_t result;
// tmp type const; to do: change to quant::runtimeID
static const int cGlobal = 0;
static const int cNeuron = 1;
static const int cSynapse = 2;
static const int cGlobalMsg = 3;
static const int cSpike = 4;
static const int cSpikeArrival = 5;
static const int propCount = 6;
// result storage
// * set by action methods
int num[propCount],
numRead[propCount],
size[propCount],
sizeRead[propCount];
// * set by generateReport()
int totalNum,
totalNumRead,
totalSize;
// methods
PLA_Debug_Space();
std::string generateReport();
// action methods
template<typename _PropList, typename _ContextData, typename LocalState>
inline void pre(_PropList &pc, _ContextData &data, LocalState &state) {
int id = PLA_Debug_Space_Quant2Num<typename LocalState::prop::quant>::eval();
num[id] += 1;
size[id] += LocalState::prop::size;
if (!LocalState::write) {
numRead[id] += 1;
sizeRead[id] += LocalState::prop::size;
}
}
template<typename PropComp, typename Data, typename _LocalState>
inline void post(PropComp &pc, Data &data, _LocalState &state) { }
};
PLA_Debug_Space::PLA_Debug_Space() {
for (int i=0; i<propCount; i++) {
num[i] = 0;
numRead[i] = 0;
size[i] = 0;
sizeRead[i] = 0;
}
}
using namespace std;
string PLA_Debug_Space::generateReport() {
ostringstream &result = *(new ostringstream());
double chkpt_delta = checkpointInterval;
result
<< "Simulation\n"
<< "==========\n\n"
<<"neurons:\t" << maxNeurons << "\n"
<< "synapses:\t" << maxSynapsesPerNeuron * maxNeurons << "\t(" << (int) maxSynapsesPerNeuron << " per neuron)\n"
<< "\n"
<< "max. # spikes:\t\t" << maxSpikes << "\n"
<< "max. # global messages:\t" << maxGlobalMsg << "\n"
<< "max. # checkpojts:\t" << maxCheckpoints << "\n"
<< "checkpoint every\t" << chkpt_delta << " s\n"
<< "\n"
<< "max. run-time:\n"
<< "\t" << min( chkpt_delta * maxCheckpoints, (double) maxSpikes / maxNeurons / 1.0 ) << " s \t@ 1 Hz\n"
<< "\t" << min( chkpt_delta * maxCheckpoints, (double) maxSpikes / maxNeurons / 10.0 ) << " s \t@ 10 Hz\n"
<< "\t" << min( chkpt_delta * maxCheckpoints, (double) maxSpikes / maxNeurons / 100.0 ) << " s \t@ 100 Hz\n"
<< "\n\n";
totalNum = 0;
totalSize = 0;
for (int i=0; i<propCount; i++) {
totalNum += num[i];
totalSize += size[i];
}
result
<< "Properties\n"
<< "==========\n\n"
<< "| Quantor\t| # of \t| size (per\t| size (all \t|\n"
<< "| \t| props\t| instance)\t| instances)\t|\n"
<< "+---------------+-------+---------------+---------------+\n"
<< "| Global \t| " << num[cGlobal] << "\t| " << size[cGlobal] << "\t\t| " << size[cGlobal] << "\t\t|\n"
<< "| Neuron \t| " << num[cNeuron] << "\t| " << size[cNeuron] << "\t\t| " << maxNeurons * size[cNeuron] << "\t\t|\n"
<< "| Synapse \t| " << num[cSynapse] << "\t| " << size[cSynapse] << "\t\t| " << maxNeurons * maxSynapsesPerNeuron * size[cSynapse] << "\t|\n"
<< "| GlobalMsg \t| " << num[cGlobalMsg] << "\t| " << size[cGlobalMsg] << "\t\t| - \t|\n"
<< "| Spike \t| " << num[cSpike] << "\t| " << size[cSpike] << "\t\t| - \t|\n"
<< "| SpikeArrival \t| " << num[cSpikeArrival] << "\t| " << size[cSpikeArrival] << "\t\t| - \t|\n"
<< "+---------------+-------+---------------+---------------+\n"
<< "| Total \t| " << totalNum << "\t| " << totalSize << "\t\t| - \t|\n"
<< "\n\n";
double pt, ps; // per time / spike space requirement
pt = size[cGlobal] + sizeof(Time) * num[cGlobal]
+ (size[cNeuron] + sizeof(Index<Spike>::ptr_t) + sizeof(Time) * (num[cNeuron] + 1)) * maxNeurons // addend 2 and 4 account for Index<Spike>::prevCache
+ (size[cSynapse] + sizeof(Time) * num[cSynapse]) * maxNeurons * maxSynapsesPerNeuron;
pt /= chkpt_delta;
ps = maxNeurons * (2*sizeof(Index<Spike>::ptr_t) + sizeof(Index<Spike>::neuron_ptr_t) + size[cNeuron] + maxSynapsesPerNeuron * size[cSpikeArrival]);
result
<< "Space Requirements\n"
<< "==================\n\n"
<< "These are strict minimum numbers. Global messages, additional managment information (in-app and in-kernel) and many small vars have not been taken into account.\n\n"
<< "\t: 1 s\t\t| 1 h\t\t| 1 d\t\t|\n"
<< "--------+---------------+---------------+---------------+\n"
<< " 1 Hz\t: " << SISuffixify(1 * ( 1 * ps + pt), 1024) << "B\t| " << SISuffixify(3600 * ( 1 * ps + pt), 1024) << "B\t| " << SISuffixify(86400 * ( 1 * ps + pt), 1024) << "B\t|\n"
<< " 10 Hz\t: " << SISuffixify(1 * ( 10 * ps + pt), 1024) << "B\t| " << SISuffixify(3600 * ( 10 * ps + pt), 1024) << "B\t| " << SISuffixify(86400 * ( 10 * ps + pt), 1024) << "B\t|\n"
<< " 100 Hz\t: " << SISuffixify(1 * (100 * ps + pt), 1024) << "B\t| " << SISuffixify(3600 * (100 * ps + pt), 1024) << "B\t| " << SISuffixify(86400 * (100 * ps + pt), 1024) << "B\t|\n"
<< "";
return result.str();
}
// PLA_Debug_Space_Quant2Num implementation
// TODO: overhaul
template <> struct PLA_Debug_Space_Quant2Num<Global> { static int eval() { return PLA_Debug_Space::cGlobal; } };
template <> struct PLA_Debug_Space_Quant2Num<Neuron> { static int eval() { return PLA_Debug_Space::cNeuron; } };
template <> struct PLA_Debug_Space_Quant2Num<Synapse> { static int eval() { return PLA_Debug_Space::cSynapse; } };
template <> struct PLA_Debug_Space_Quant2Num<GlobalMsg> { static int eval() { return PLA_Debug_Space::cGlobalMsg; } };
template <> struct PLA_Debug_Space_Quant2Num<Spike> { static int eval() { return PLA_Debug_Space::cSpike; } };
template <> struct PLA_Debug_Space_Quant2Num<SpikeArrival> { static int eval() { return PLA_Debug_Space::cSpikeArrival; } };
} // NS
using PLA_Debug_Space_Impl::PLA_Debug_Space;
#endif // iAN34Y9CxgHgVUyhhdYpI8Ynza8
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