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_simulator_mpi.py
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_simulator_mpi.py
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# Copyright 2017 ProjectQ-Framework (www.projectq.ch)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Contains the projectq interface to a C++-based simulator, which has to be
built first. If the c++ simulator is not exported to python, a (slow) python
implementation is used as an alternative.
"""
import math
import random
import numpy
from projectq.cengines import BasicEngine
from projectq.meta import get_control_count, LogicalQubitIDTag
from projectq.ops import (NOT,
H,
R,
Measure,
FlushGate,
Allocate,
Deallocate,
BasicMathGate,
TimeEvolution, FastForwardingGate)
from projectq.types import WeakQubitRef
from hiq.projectq.ops import MetaSwap, AllocateQuregGate
from ._cppsim_mpi import SimulatorMPI as SimulatorBackend
from mpi4py import rc
rc.thread = True
rc.thread_level = 'funneled'
rc.finalize = True
from mpi4py import MPI # properly loads and initializes MPI environment
class SimulatorMPI(BasicEngine):
"""
SimulatorMPI is a compiler engine which simulates a quantum computer using
C++-based kernels.
OpenMP is enabled and the number of threads can be controlled using the
OMP_NUM_THREADS environment variable, i.e.
.. code-block:: bash
export OMP_NUM_THREADS=4 # use 4 threads
export OMP_PROC_BIND=spread # bind threads to processors by spreading
"""
def __init__(self, gate_fusion=False, rnd_seed=None, num_local_qubits=33, max_fused_qubits=4):
"""
Construct the C++/Python-simulator object and initialize it with a
random seed.
Args:
gate_fusion (bool): If True, gates are cached and only executed
once a certain gate-size has been reached (only has an effect
for the c++ simulator).
rnd_seed (int): Random seed (uses random.randint(0, 4294967295) by
default).
num_local_qubits (int): maximum number of qubits the MPI node can
allocate by itself
max_fused_qubits (int): the maximum number of qubits the fused gate
can act on
Example of gate_fusion: Instead of applying a Hadamard gate to 5
qubits, the simulator calculates the kronecker product of the 1-qubit
gate matrices and then applies one 5-qubit gate. This increases
operational intensity and keeps the simulator from having to iterate
through the state vector multiple times. Depending on the system (and,
especially, number of threads), this may or may not be beneficial.
"""
if not MPI.Is_thread_main():
raise RuntimeError("Incorrect MPI initialization: MPI must be initialized with Init_thread()!")
if MPI.Query_thread() < MPI.THREAD_FUNNELED:
raise RuntimeError("Incorrect MPI thread level: thread level must be >= THREAD_FUNNELED!")
if rnd_seed is None:
rnd_seed = random.randint(0, 4294967295)
BasicEngine.__init__(self)
self._simulator = SimulatorBackend(rnd_seed, num_local_qubits, max_fused_qubits)
self._gate_fusion = gate_fusion
def is_available(self, cmd):
"""
Specialized implementation of is_available: The simulator can deal
with all arbitrarily-controlled gates which provide a
gate-matrix (via gate.matrix) and acts on 5 or less qubits (not
counting the control qubits).
Args:
cmd (Command): Command for which to check availability (single-
qubit gate, arbitrary controls)
Returns:
True if it can be simulated and False otherwise.
"""
if (cmd.gate == Measure or cmd.gate == Allocate or
cmd.gate == Deallocate or
isinstance(cmd.gate, AllocateQuregGate)):
return True
elif (isinstance(cmd.gate, BasicMathGate) or # current version don't support this
isinstance(cmd.gate, TimeEvolution)):
return False
try:
m = cmd.gate.matrix
# Allow up to 5-qubit gates
if len(m) > 2 ** 5:
return False
return True
except:
return False
def _convert_logical_to_mapped_qureg(self, qureg):
"""
Converts a qureg from logical to mapped qubits if there is a mapper.
Args:
qureg (list[Qubit],Qureg): Logical quantum bits
"""
mapper = self.main_engine.mapper
if mapper is not None:
mapped_qureg = []
for qubit in qureg:
if qubit.id not in mapper.current_mapping:
raise RuntimeError("Unknown qubit id. "
"Please make sure you have called "
"eng.flush().")
new_qubit = WeakQubitRef(qubit.engine,
mapper.current_mapping[qubit.id])
mapped_qureg.append(new_qubit)
return mapped_qureg
else:
return qureg
def get_expectation_value(self, qubit_operator, qureg):
"""
Get the expectation value of qubit_operator w.r.t. the current wave
function represented by the supplied quantum register.
Args:
qubit_operator (projectq.ops.QubitOperator): Operator to measure.
qureg (list[Qubit],Qureg): Quantum bits to measure.
Returns:
Expectation value
Note:
Make sure all previous commands (especially allocations) have
passed through the compilation chain (call main_engine.flush() to
make sure).
Note:
If there is a mapper present in the compiler, this function
automatically converts from logical qubits to mapped qubits for
the qureg argument.
Raises:
Exception: If `qubit_operator` acts on more qubits than present in
the `qureg` argument.
"""
qureg = self._convert_logical_to_mapped_qureg(qureg)
num_qubits = len(qureg)
for term, _ in qubit_operator.terms.items():
if not term == () and term[-1][0] >= num_qubits:
raise Exception("qubit_operator acts on more qubits than "
"contained in the qureg.")
operator = [(list(term), coeff) for (term, coeff)
in qubit_operator.terms.items()]
return self._simulator.get_expectation_value(operator,
[qb.id for qb in qureg])
def apply_qubit_operator(self, qubit_operator, qureg):
"""
Apply a (possibly non-unitary) qubit_operator to the current wave
function represented by the supplied quantum register.
Args:
qubit_operator (projectq.ops.QubitOperator): Operator to apply.
qureg (list[Qubit],Qureg): Quantum bits to which to apply the
operator.
Raises:
Exception: If `qubit_operator` acts on more qubits than present in
the `qureg` argument.
Warning:
This function allows applying non-unitary gates and it will not
re-normalize the wave function! It is for numerical experiments
only and should not be used for other purposes.
Note:
Make sure all previous commands (especially allocations) have
passed through the compilation chain (call main_engine.flush() to
make sure).
Note:
If there is a mapper present in the compiler, this function
automatically converts from logical qubits to mapped qubits for
the qureg argument.
"""
qureg = self._convert_logical_to_mapped_qureg(qureg)
num_qubits = len(qureg)
for term, _ in qubit_operator.terms.items():
if not term == () and term[-1][0] >= num_qubits:
raise Exception("qubit_operator acts on more qubits than "
"contained in the qureg.")
operator = [(list(term), coeff) for (term, coeff)
in qubit_operator.terms.items()]
return self._simulator.apply_qubit_operator(operator,
[qb.id for qb in qureg])
def get_probability(self, bit_string, qureg):
"""
Return the probability of the outcome `bit_string` when measuring
the quantum register `qureg`.
Args:
bit_string (list[bool|int]|string[0|1]): Measurement outcome.
qureg (Qureg|list[Qubit]): Quantum register.
Returns:
Probability of measuring the provided bit string.
Note:
Make sure all previous commands (especially allocations) have
passed through the compilation chain (call main_engine.flush() to
make sure).
Note:
If there is a mapper present in the compiler, this function
automatically converts from logical qubits to mapped qubits for
the qureg argument.
"""
qureg = self._convert_logical_to_mapped_qureg(qureg)
bit_string = [bool(int(b)) for b in bit_string]
return self._simulator.get_probability(bit_string,
[qb.id for qb in qureg])
def get_amplitude(self, bit_string, qureg):
"""
Return the probability amplitude of the supplied `bit_string`.
The ordering is given by the quantum register `qureg`, which must
contain all allocated qubits.
Args:
bit_string (list[bool|int]|string[0|1]): Computational basis state
qureg (Qureg|list[Qubit]): Quantum register determining the
ordering. Must contain all allocated qubits.
Returns:
Probability amplitude of the provided bit string.
Note:
Make sure all previous commands (especially allocations) have
passed through the compilation chain (call main_engine.flush() to
make sure).
Note:
If there is a mapper present in the compiler, this function
automatically converts from logical qubits to mapped qubits for
the qureg argument.
"""
qureg = self._convert_logical_to_mapped_qureg(qureg)
bit_string = [bool(int(b)) for b in bit_string]
return self._simulator.get_amplitude(bit_string,
[qb.id for qb in qureg])
def set_wavefunction(self, wavefunction, qureg):
"""
Set the wavefunction and the qubit ordering of the simulator.
The simulator will adopt the ordering of qureg (instead of reordering
the wavefunction).
Args:
wavefunction (list[complex]): Array of complex amplitudes
describing the wavefunction (must be normalized).
qureg (Qureg|list[Qubit]): Quantum register determining the
ordering. Must contain all allocated qubits.
Note:
Make sure all previous commands (especially allocations) have
passed through the compilation chain (call main_engine.flush() to
make sure).
Note:
If there is a mapper present in the compiler, this function
automatically converts from logical qubits to mapped qubits for
the qureg argument.
"""
qureg = self._convert_logical_to_mapped_qureg(qureg)
self._simulator.set_wavefunction(wavefunction,
[qb.id for qb in qureg])
def collapse_wavefunction(self, qureg, values):
"""
Collapse a quantum register onto a classical basis state.
Args:
qureg (Qureg|list[Qubit]): Qubits to collapse.
values (list[bool|int]|string[0|1]): Measurement outcome for each
of the qubits in `qureg`.
Raises:
RuntimeError: If an outcome has probability (approximately) 0 or
if unknown qubits are provided (see note).
Note:
Make sure all previous commands have passed through the
compilation chain (call main_engine.flush() to make sure).
Note:
If there is a mapper present in the compiler, this function
automatically converts from logical qubits to mapped qubits for
the qureg argument.
"""
qureg = self._convert_logical_to_mapped_qureg(qureg)
return self._simulator.collapse_wavefunction([qb.id for qb in qureg],
[bool(int(v)) for v in
values])
def cheat_local(self):
"""
Access the ordering of the qubits and this MPI process's part of
of state vector directly.
Returns:
A tuple where the first entry is a dictionary mapping qubit
indices to bit-locations (all qubits) and the second entry is the local part
of state vector.
"""
return self._simulator.cheat_local()
def cheat(self):
"""
Access the ordering of the qubits and the state vector directly.
This is a cheat function which enables, e.g., more efficient
evaluation of expectation values and debugging.
Returns:
A tuple (id2pos, tot_vec) where the first entry is a dictionary mapping qubit
indices to bit-locations and the second entry is the corresponding
state vector.
Note:
The function performs MPI_Allgather() and returns concatenated
full state vector. It is always concatenated from np parts, so
it is presumed that there are log(np) global qubits. One should
check qubit ordering returned to find out which bit positions are
valid. For example: np = 4, id2pos = {0:0, 1:2} then state vector
size is 8 and valid data at indices 0, 1, 4, 5.
Note:
Make sure all previous commands have passed through the
compilation chain (call main_engine.flush() to make sure).
Note:
If there is a mapper present in the compiler, this function
DOES NOT automatically convert from logical qubits to mapped
qubits.
"""
id2pos, vec = self.cheat_local()
tot_vec = numpy.zeros(len(vec)*MPI.COMM_WORLD.Get_size(), dtype=complex)
MPI.COMM_WORLD.Allgather([numpy.array(vec), MPI.COMPLEX], [tot_vec, MPI.COMPLEX])
return id2pos, tot_vec
def get_qubits_ids(self):
"""
Returns:
A list of all qubits ids allocated in simulator
"""
return self._simulator.get_qubits_ids()
def get_local_qubits_ids(self):
"""
Returns:
A list of local qubits ids
"""
return self._simulator.get_local_qubits_ids()
def get_global_qubits_ids(self):
"""
Returns:
A list of global qubits ids
"""
return self._simulator.get_global_qubits_ids()
def set_qubits_perm(self, ids):
"""
Sets the initial permutation of qubits in simulator
just after a first Qureg has been allocated
Args:
ids (list[int]): list of all qubits ids
"""
self._simulator.set_qubits_perm(ids)
def _do_swap(self, qubits):
self._simulator.swap_qubits(qubits)
def _handle(self, cmd):
"""
Handle all commands, i.e., call the member functions of the C++-
simulator object corresponding to measurement, allocation/
deallocation, and (controlled) single-qubit gate.
Args:
cmd (Command): Command to handle.
Raises:
Exception: If a non-single-qubit gate needs to be processed
(which should never happen due to is_available).
"""
if isinstance(cmd.gate, FlushGate):
pass
elif cmd.gate == MetaSwap:
qubits = [qb.id for qr in cmd.all_qubits for qb in qr]
self._do_swap(qubits)
elif cmd.gate == Measure:
assert(get_control_count(cmd) == 0)
ids = [qb.id for qr in cmd.qubits for qb in qr]
out = self._simulator.measure_qubits(ids)
i = 0
for qr in cmd.qubits:
for qb in qr:
# Check if a mapper assigned a different logical id
logical_id_tag = None
for tag in cmd.tags:
if isinstance(tag, LogicalQubitIDTag):
logical_id_tag = tag
if logical_id_tag is not None:
qb = WeakQubitRef(qb.engine,
logical_id_tag.logical_qubit_id)
self.main_engine.set_measurement_result(qb, out[i])
i += 1
elif cmd.gate == Allocate:
ID = cmd.qubits[0][0].id
self._simulator.allocate_qubit(ID)
elif isinstance(cmd.gate, AllocateQuregGate):
ids = [qb.id for qr in cmd.qubits for qb in qr]
self._simulator.allocate_qureg(ids, cmd.gate.init)
elif cmd.gate == Deallocate:
ID = cmd.qubits[0][0].id
self._simulator.deallocate_qubit(ID)
elif isinstance(cmd.gate, BasicMathGate):
qubitids = []
for qr in cmd.qubits:
qubitids.append([])
for qb in qr:
qubitids[-1].append(qb.id)
math_fun = cmd.gate.get_math_function(cmd.qubits)
self._simulator.emulate_math(math_fun, qubitids,
[qb.id for qb in cmd.control_qubits])
elif isinstance(cmd.gate, TimeEvolution):
op = [(list(term), coeff) for (term, coeff)
in cmd.gate.hamiltonian.terms.items()]
t = cmd.gate.time
qubitids = [qb.id for qb in cmd.qubits[0]]
ctrlids = [qb.id for qb in cmd.control_qubits]
self._simulator.emulate_time_evolution(op, t, qubitids, ctrlids)
elif len(cmd.gate.matrix) <= 2 ** 5:
matrix = cmd.gate.matrix
ids = [qb.id for qr in cmd.qubits for qb in qr]
if not 2 ** len(ids) == len(cmd.gate.matrix):
raise Exception("Simulator: Error applying {} gate: "
"{}-qubit gate applied to {} qubits.".format(
str(cmd.gate),
int(math.log(len(cmd.gate.matrix), 2)),
len(ids)))
self._simulator.apply_controlled_gate(matrix.tolist(),
ids,
[qb.id for qb in
cmd.control_qubits])
if not self._gate_fusion:
self._simulator.run()
else:
raise Exception("This simulator only supports controlled k-qubit"
" gates with k < 6!\nPlease add an auto-replacer"
" engine to your list of compiler engines.")
def receive(self, command_list):
"""
Receive a list of commands from the previous engine and handle them
(simulate them classically) prior to sending them on to the next
engine.
Args:
command_list (list<Command>): List of commands to execute on the
simulator.
"""
for cmd in command_list:
if isinstance(cmd.gate, FlushGate) or isinstance(cmd.gate, FastForwardingGate):
self._simulator.run() # flush gate --> run all saved gates
self._handle(cmd)
if not self.is_last_engine:
self.send([cmd])