void StepKernel::Integrate( OpenMM::ContextImpl &context, const Integrator &integrator ) {
ProjectionVectors( integrator );
#ifdef FAST_NOISE
// Add noise for step
kFastNoise( &fastmodule, data.contexts[0], integrator.getNumProjectionVectors(), ( float )( BOLTZ * integrator.getTemperature() ), iterations, *modes, *modeWeights, integrator.getMaxEigenvalue(), *NoiseValues, *pPosqP, integrator.getStepSize() );
#endif
// Calculate Constants
const double friction = integrator.getFriction();
context.updateContextState();
// Do Step
kNMLUpdate( &updatemodule,
data.contexts[0],
integrator.getStepSize(),
friction == 0.0f ? 0.0f : 1.0f / friction,
( float )( BOLTZ * integrator.getTemperature() ),
integrator.getNumProjectionVectors(), kIterations, *modes, *modeWeights, *NoiseValues ); // TMC setting parameters for this
}
void StepKernel::ProjectionVectors( const Integrator &integrator ) {
//check if projection vectors changed
bool modesChanged = integrator.getProjVecChanged();
//projection vectors changed or never allocated
if( modesChanged || modes == NULL ) {
int numModes = integrator.getNumProjectionVectors();
//valid vectors?
if( numModes == 0 ) {
throw OpenMMException( "Projection vector size is zero." );
}
//if( modes != NULL && modes->_length != numModes * mParticles ) {
if( modes != NULL && modes->getSize() != numModes * mParticles ) {
delete modes;
delete modeWeights;
modes = NULL;
modeWeights = NULL;
}
if( modes == NULL ) {
/*modes = new CUDAStream<float4>( numModes * mParticles, 1, "NormalModes" );
modeWeights = new CUDAStream<float>( numModes > data.gpu->sim.blocks ? numModes : data.gpu->sim.blocks, 1, "NormalModeWeights" );*/
//cu->getNumThreadBlocks()*cu->ThreadBlockSize
modes = new CudaArray( *( data.contexts[0] ), numModes * mParticles, sizeof( float4 ), "NormalModes" );
modeWeights = new CudaArray( *( data.contexts[0] ), ( numModes > data.contexts[0]->getNumThreadBlocks()*data.contexts[0]->ThreadBlockSize ? numModes : data.contexts[0]->getNumThreadBlocks()*data.contexts[0]->ThreadBlockSize ), sizeof( float ), "NormalModeWeights" );
oldpos = new CudaArray( *( data.contexts[0] ), data.contexts[0]->getPaddedNumAtoms(), sizeof( float4 ), "OldPositions" );
pPosqP = new CudaArray( *( data.contexts[0] ), data.contexts[0]->getPaddedNumAtoms(), sizeof( float4 ), "MidIntegPositions" );
modesChanged = true;
}
if( modesChanged ) {
int index = 0;
const std::vector<std::vector<Vec3> > &modeVectors = integrator.getProjectionVectors();
std::vector<float4> tmp( numModes * mParticles );;
for( int i = 0; i < numModes; i++ ) {
for( int j = 0; j < mParticles; j++ ) {
tmp[index++] = make_float4( ( float ) modeVectors[i][j][0], ( float ) modeVectors[i][j][1], ( float ) modeVectors[i][j][2], 0.0f );
}
}
modes->upload( tmp );
}
}
}
void StepKernel::LinearMinimize( OpenMM::ContextImpl &context, const Integrator &integrator, const double energy ) {
ProjectionVectors( integrator );
lastPE = energy;
kNMLLinearMinimize( &linmodule, data.contexts[0], integrator.getNumProjectionVectors(), integrator.getMaxEigenvalue(), *pPosqP, *modes, *modeWeights );
}