prefetch = None
if i == 0:
prefetch = db['reducedTimeIntegratedDofs']
elif i == 1:
prefetch = localFlux
else:
prefetch = Kernel.DummyPrefetch()
kernels.append(Kernel.Prototype('localFlux[{}]'.format(i), localFlux, prefetch=prefetch))
for i in range(0, 4):
for j in range(0, 4):
for h in range(0, 3):
neighboringFlux = db['r{}DivM'.format(i+1)] * db['fP{}'.format(h+1)] * db['rT{}'.format(j+1)] * db['reducedTimeIntegratedDofs'] * db['AminusT']
kernels.append(Kernel.Prototype('neighboringFlux[{}]'.format(i*12+j*3+h), neighboringFlux, prefetch=db['reducedTimeIntegratedDofs']))
derivative = db['kXiDivMT'] * db['reducedDofs'] * db['AstarT'] \
+ db['kEtaDivMT'] * db['reducedDofs'] * db['BstarT'] \
+ db['kZetaDivMT'] * db['reducedDofs'] * db['CstarT']
kernels.append(Kernel.Prototype('derivative', derivative, beta=0))
source = db['mechanism'] * db['ET']
kernels.append(Kernel.Prototype('source', source))
DynamicRupture.addKernels(db, kernels, 'timeDerivative0_elastic')
Plasticity.addKernels(db, kernels)
SurfaceDisplacement.addKernels(db, kernels)
# Generate code
Tools.generate(cmdLineArgs.outputDir, db, kernels, libxsmmGenerator, architecture)
volume = db['kXiDivM'] * db['timeIntegrated'] * db['AstarT'] \
+ db['kEtaDivM'] * db['timeIntegrated'] * db['BstarT'] \
+ db['kZetaDivM'] * db['timeIntegrated'] * db['CstarT'] \
+ db['timeIntegrated'] * db['source']
kernels.append(('volume', volume))
for i in range(0, 4):
localFlux = db['fM{}'.format(i+1)] * db['timeIntegrated'] * db['AplusT']
kernels.append(('localFlux[{}]'.format(i), localFlux))
for i in range(0, 4):
for j in range(0, 4):
for h in range(0, 3):
neighboringFlux = db['fP{}{}{}'.format(i+1, j+1, h+1)] * db['timeIntegrated'] * db['AminusT']
kernels.append(('neighboringFlux[{}]'.format(i*12+j*3+h), neighboringFlux))
for i in range(1, order):
lastD = 'timeDerivative{}'.format(str(i-1))
newD = 'timeDerivative{}'.format(str(i))
derivative = db['kXiDivMT'] * db[lastD] * db['AstarT'] \
+ db['kEtaDivMT'] * db[lastD] * db['BstarT'] \
+ db['kZetaDivMT'] * db[lastD] * db['CstarT'] \
+ db[lastD] * db['source']
derivative.fitBlocksToSparsityPattern()
kernels.append(('derivative[{}]'.format(i), derivative))
db.insert(derivative.flat(newD))
db[newD].fitBlocksToSparsityPattern()
# Generate code
Tools.generate(cmdLineArgs.outputDir, db, kernels, libxsmmGenerator, architecture)
