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Support measurement sampling seed for cutensornet backends #2398

Merged
merged 8 commits into from
Nov 27, 2024
4 changes: 2 additions & 2 deletions runtime/nvqir/cutensornet/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -60,8 +60,8 @@ set(CUTENSORNET_PATCH ${CMAKE_MATCH_1})

set(CUTENSORNET_VERSION ${CUTENSORNET_MAJOR}.${CUTENSORNET_MINOR}.${CUTENSORNET_PATCH})
message(STATUS "Found cutensornet version: ${CUTENSORNET_VERSION}")
# We need cutensornet v2.3+
if (${CUTENSORNET_VERSION} VERSION_GREATER_EQUAL "2.3")
# We need cutensornet v2.5.0+
if (${CUTENSORNET_VERSION} VERSION_GREATER_EQUAL "2.5")
set (BASE_TENSOR_BACKEND_SRS
simulator_cutensornet.cpp
tensornet_spin_op.cpp
Expand Down
38 changes: 21 additions & 17 deletions runtime/nvqir/cutensornet/mps_simulation_state.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -26,9 +26,11 @@ std::size_t MPSSimulationState::getNumQubits() const {
MPSSimulationState::MPSSimulationState(std::unique_ptr<TensorNetState> inState,
const std::vector<MPSTensor> &mpsTensors,
ScratchDeviceMem &inScratchPad,
cutensornetHandle_t cutnHandle)
cutensornetHandle_t cutnHandle,
std::mt19937 &randomEngine)
: m_cutnHandle(cutnHandle), state(std::move(inState)),
m_mpsTensors(mpsTensors), scratchPad(inScratchPad) {}
m_mpsTensors(mpsTensors), scratchPad(inScratchPad),
m_randomEngine(randomEngine) {}

MPSSimulationState::~MPSSimulationState() { deallocate(); }

Expand Down Expand Up @@ -266,8 +268,8 @@ MPSSimulationState::getAmplitude(const std::vector<int> &basisState) {
}

if (getNumQubits() > 1) {
TensorNetState basisTensorNetState(basisState, scratchPad,
state->getInternalContext());
TensorNetState basisTensorNetState(
basisState, scratchPad, state->getInternalContext(), m_randomEngine);
// Note: this is a basis state, hence bond dim == 1
std::vector<MPSTensor> basisStateTensors = basisTensorNetState.factorizeMPS(
1, std::numeric_limits<double>::min(),
Expand Down Expand Up @@ -369,7 +371,8 @@ static Eigen::MatrixXcd reshapeStateVec(const Eigen::VectorXcd &stateVec) {

MPSSimulationState::MpsStateData MPSSimulationState::createFromStateVec(
cutensornetHandle_t cutnHandle, ScratchDeviceMem &inScratchPad,
std::size_t size, std::complex<double> *ptr, int bondDim) {
std::size_t size, std::complex<double> *ptr, int bondDim,
std::mt19937 &randomEngine) {
const std::size_t numQubits = std::log2(size);
// Reverse the qubit order to match cutensornet convention
auto newStateVec = TensorNetState::reverseQubitOrder(
Expand All @@ -386,8 +389,8 @@ MPSSimulationState::MpsStateData MPSSimulationState::createFromStateVec(
MPSTensor stateTensor;
stateTensor.deviceData = d_tensor;
stateTensor.extents = std::vector<int64_t>{2};
auto state = TensorNetState::createFromMpsTensors({stateTensor},
inScratchPad, cutnHandle);
auto state = TensorNetState::createFromMpsTensors(
{stateTensor}, inScratchPad, cutnHandle, randomEngine);
return {std::move(state), std::vector<MPSTensor>{stateTensor}};
}

Expand Down Expand Up @@ -460,7 +463,7 @@ MPSSimulationState::MpsStateData MPSSimulationState::createFromStateVec(
mpsTensors.emplace_back(stateTensor);
assert(mpsTensors.size() == numQubits);
auto state = TensorNetState::createFromMpsTensors(mpsTensors, inScratchPad,
cutnHandle);
cutnHandle, randomEngine);
return {std::move(state), mpsTensors};
}

Expand All @@ -486,16 +489,17 @@ MPSSimulationState::createFromSizeAndPtr(std::size_t size, void *ptr,
MPSTensor stateTensor{d_tensor, mpsExtents};
mpsTensors.emplace_back(stateTensor);
}
auto state = TensorNetState::createFromMpsTensors(mpsTensors, scratchPad,
m_cutnHandle);
return std::make_unique<MPSSimulationState>(std::move(state), mpsTensors,
scratchPad, m_cutnHandle);
auto state = TensorNetState::createFromMpsTensors(
mpsTensors, scratchPad, m_cutnHandle, m_randomEngine);
return std::make_unique<MPSSimulationState>(
std::move(state), mpsTensors, scratchPad, m_cutnHandle, m_randomEngine);
}
auto [state, mpsTensors] = createFromStateVec(
m_cutnHandle, scratchPad, size,
reinterpret_cast<std::complex<double> *>(ptr), MPSSettings().maxBond);
return std::make_unique<MPSSimulationState>(std::move(state), mpsTensors,
scratchPad, m_cutnHandle);
auto [state, mpsTensors] =
createFromStateVec(m_cutnHandle, scratchPad, size,
reinterpret_cast<std::complex<double> *>(ptr),
MPSSettings().maxBond, m_randomEngine);
return std::make_unique<MPSSimulationState>(
std::move(state), mpsTensors, scratchPad, m_cutnHandle, m_randomEngine);
}

MPSSettings::MPSSettings() {
Expand Down
6 changes: 4 additions & 2 deletions runtime/nvqir/cutensornet/mps_simulation_state.h
Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,8 @@ class MPSSimulationState : public cudaq::SimulationState {
MPSSimulationState(std::unique_ptr<TensorNetState> inState,
const std::vector<MPSTensor> &mpsTensors,
ScratchDeviceMem &inScratchPad,
cutensornetHandle_t cutnHandle);
cutensornetHandle_t cutnHandle,
std::mt19937 &randomEngine);

MPSSimulationState(const MPSSimulationState &) = delete;
MPSSimulationState &operator=(const MPSSimulationState &) = delete;
Expand Down Expand Up @@ -84,7 +85,7 @@ class MPSSimulationState : public cudaq::SimulationState {
ScratchDeviceMem &inScratchPad,
std::size_t size,
std::complex<double> *data,
int bondDim);
int bondDim, std::mt19937 &randomEngine);

/// Retrieve the MPS tensors
std::vector<MPSTensor> getMpsTensors() const { return m_mpsTensors; }
Expand All @@ -105,6 +106,7 @@ class MPSSimulationState : public cudaq::SimulationState {
// This speeds up sequential state amplitude accessors for small states.
static constexpr std::size_t g_maxQubitsForStateContraction = 30;
std::vector<std::complex<double>> m_contractedStateVec;
std::mt19937 &m_randomEngine;
};

} // namespace nvqir
4 changes: 2 additions & 2 deletions runtime/nvqir/cutensornet/simulator_cutensornet.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -289,8 +289,8 @@ void SimulatorTensorNetBase::setToZeroState() {
const auto numQubits = m_state->getNumQubits();
m_state.reset();
// Re-create a zero state of the same size
m_state =
std::make_unique<TensorNetState>(numQubits, scratchPad, m_cutnHandle);
m_state = std::make_unique<TensorNetState>(numQubits, scratchPad,
m_cutnHandle, m_randomEngine);
}

void SimulatorTensorNetBase::swap(const std::vector<std::size_t> &ctrlBits,
Expand Down
6 changes: 2 additions & 4 deletions runtime/nvqir/cutensornet/simulator_cutensornet.h
Original file line number Diff line number Diff line change
Expand Up @@ -93,10 +93,8 @@ class SimulatorTensorNetBase : public nvqir::CircuitSimulatorBase<double> {
std::unique_ptr<TensorNetState> m_state;
std::unordered_map<std::string, void *> m_gateDeviceMemCache;
ScratchDeviceMem scratchPad;
// Note: cutensornet sample API uses an internal random engine that doesn't
// support random seed. This engine only affects the mid-circuit measurements
// whereby this simulator generates a random probability value.
// See also: https://github.com/NVIDIA/cuda-quantum/issues/895
// Random number generator for generating 32-bit numbers with a state size of
// 19937 bits for measurements.
std::mt19937 m_randomEngine;
};

Expand Down
35 changes: 18 additions & 17 deletions runtime/nvqir/cutensornet/simulator_mps_register.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -47,8 +47,8 @@ class SimulatorMPS : public SimulatorTensorNetBase {
throw std::invalid_argument(
"[SimulatorMPS simulator] Incompatible state input");
if (!m_state) {
m_state = TensorNetState::createFromMpsTensors(casted->getMpsTensors(),
scratchPad, m_cutnHandle);
m_state = TensorNetState::createFromMpsTensors(
casted->getMpsTensors(), scratchPad, m_cutnHandle, m_randomEngine);
} else {
// Expand an existing state: Append MPS tensors
// Factor the existing state
Expand Down Expand Up @@ -76,8 +76,8 @@ class SimulatorMPS : public SimulatorTensorNetBase {
tensorSizeBytes, cudaMemcpyDefault));
tensors.emplace_back(MPSTensor(mpsTensor, extents));
}
m_state = TensorNetState::createFromMpsTensors(tensors, scratchPad,
m_cutnHandle);
m_state = TensorNetState::createFromMpsTensors(
tensors, scratchPad, m_cutnHandle, m_randomEngine);
}
}

Expand Down Expand Up @@ -164,13 +164,13 @@ class SimulatorMPS : public SimulatorTensorNetBase {
LOG_API_TIME();
if (!m_state) {
if (!ptr) {
m_state = std::make_unique<TensorNetState>(numQubits, scratchPad,
m_cutnHandle);
m_state = std::make_unique<TensorNetState>(
numQubits, scratchPad, m_cutnHandle, m_randomEngine);
} else {
auto [state, mpsTensors] = MPSSimulationState::createFromStateVec(
m_cutnHandle, scratchPad, 1ULL << numQubits,
reinterpret_cast<std::complex<double> *>(const_cast<void *>(ptr)),
m_settings.maxBond);
m_settings.maxBond, m_randomEngine);
m_state = std::move(state);
}
} else {
Expand All @@ -194,14 +194,14 @@ class SimulatorMPS : public SimulatorTensorNetBase {
cudaMemcpyHostToDevice));
tensors.emplace_back(MPSTensor(mpsTensor, extents));
}
m_state = TensorNetState::createFromMpsTensors(tensors, scratchPad,
m_cutnHandle);
m_state = TensorNetState::createFromMpsTensors(
tensors, scratchPad, m_cutnHandle, m_randomEngine);
} else {
// Non-zero state needs to be factorized and appended.
auto [state, mpsTensors] = MPSSimulationState::createFromStateVec(
m_cutnHandle, scratchPad, 1ULL << numQubits,
reinterpret_cast<std::complex<double> *>(const_cast<void *>(ptr)),
m_settings.maxBond);
m_settings.maxBond, m_randomEngine);
auto tensors =
m_state->factorizeMPS(m_settings.maxBond, m_settings.absCutoff,
m_settings.relCutoff, m_settings.svdAlgo);
Expand All @@ -214,8 +214,8 @@ class SimulatorMPS : public SimulatorTensorNetBase {
mpsTensors.front().extents = extents;
// Combine the list
tensors.insert(tensors.end(), mpsTensors.begin(), mpsTensors.end());
m_state = TensorNetState::createFromMpsTensors(tensors, scratchPad,
m_cutnHandle);
m_state = TensorNetState::createFromMpsTensors(
tensors, scratchPad, m_cutnHandle, m_randomEngine);
}
}
}
Expand All @@ -224,16 +224,17 @@ class SimulatorMPS : public SimulatorTensorNetBase {
LOG_API_TIME();

if (!m_state || m_state->getNumQubits() == 0)
return std::make_unique<MPSSimulationState>(std::move(m_state),
std::vector<MPSTensor>{},
scratchPad, m_cutnHandle);
return std::make_unique<MPSSimulationState>(
std::move(m_state), std::vector<MPSTensor>{}, scratchPad,
m_cutnHandle, m_randomEngine);

if (m_state->getNumQubits() > 1) {
std::vector<MPSTensor> tensors =
m_state->factorizeMPS(m_settings.maxBond, m_settings.absCutoff,
m_settings.relCutoff, m_settings.svdAlgo);
return std::make_unique<MPSSimulationState>(std::move(m_state), tensors,
scratchPad, m_cutnHandle);
scratchPad, m_cutnHandle,
m_randomEngine);
}

auto [d_tensor, numElements] = m_state->contractStateVectorInternal({});
Expand All @@ -244,7 +245,7 @@ class SimulatorMPS : public SimulatorTensorNetBase {

return std::make_unique<MPSSimulationState>(
std::move(m_state), std::vector<MPSTensor>{stateTensor}, scratchPad,
m_cutnHandle);
m_cutnHandle, m_randomEngine);
}

virtual ~SimulatorMPS() noexcept {
Expand Down
18 changes: 9 additions & 9 deletions runtime/nvqir/cutensornet/simulator_tensornet_register.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -47,22 +47,22 @@ class SimulatorTensorNet : public SimulatorTensorNetBase {

std::unique_ptr<cudaq::SimulationState> getSimulationState() override {
LOG_API_TIME();
return std::make_unique<TensorNetSimulationState>(std::move(m_state),
scratchPad, m_cutnHandle);
return std::make_unique<TensorNetSimulationState>(
std::move(m_state), scratchPad, m_cutnHandle, m_randomEngine);
}

void addQubitsToState(std::size_t numQubits, const void *ptr) override {
LOG_API_TIME();
if (!m_state) {
if (!ptr) {
m_state = std::make_unique<TensorNetState>(numQubits, scratchPad,
m_cutnHandle);
m_state = std::make_unique<TensorNetState>(
numQubits, scratchPad, m_cutnHandle, m_randomEngine);
} else {
auto *casted =
reinterpret_cast<std::complex<double> *>(const_cast<void *>(ptr));
std::span<std::complex<double>> stateVec(casted, 1ULL << numQubits);
m_state = TensorNetState::createFromStateVector(stateVec, scratchPad,
m_cutnHandle);
m_state = TensorNetState::createFromStateVector(
stateVec, scratchPad, m_cutnHandle, m_randomEngine);
}
} else {
if (!ptr) {
Expand All @@ -85,9 +85,9 @@ class SimulatorTensorNet : public SimulatorTensorNetBase {
throw std::invalid_argument(
"[Tensornet simulator] Incompatible state input");
if (!m_state) {
m_state = TensorNetState::createFromOpTensors(in_state.getNumQubits(),
casted->getAppliedTensors(),
scratchPad, m_cutnHandle);
m_state = TensorNetState::createFromOpTensors(
in_state.getNumQubits(), casted->getAppliedTensors(), scratchPad,
m_cutnHandle, m_randomEngine);
} else {
// Expand an existing state:
// (1) Create a blank tensor network with combined number of qubits
Expand Down
41 changes: 26 additions & 15 deletions runtime/nvqir/cutensornet/tensornet_state.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,9 @@ namespace nvqir {

TensorNetState::TensorNetState(std::size_t numQubits,
ScratchDeviceMem &inScratchPad,
cutensornetHandle_t handle)
: m_numQubits(numQubits), m_cutnHandle(handle), scratchPad(inScratchPad) {
cutensornetHandle_t handle, std::mt19937 &randomEngine)
: m_numQubits(numQubits), m_cutnHandle(handle), scratchPad(inScratchPad),
m_randomEngine(randomEngine) {
const std::vector<int64_t> qubitDims(m_numQubits, 2);
HANDLE_CUTN_ERROR(cutensornetCreateState(
m_cutnHandle, CUTENSORNET_STATE_PURITY_PURE, m_numQubits,
Expand All @@ -25,8 +26,8 @@ TensorNetState::TensorNetState(std::size_t numQubits,

TensorNetState::TensorNetState(const std::vector<int> &basisState,
ScratchDeviceMem &inScratchPad,
cutensornetHandle_t handle)
: TensorNetState(basisState.size(), inScratchPad, handle) {
cutensornetHandle_t handle, std::mt19937 &randomEngine)
: TensorNetState(basisState.size(), inScratchPad, handle, randomEngine) {
constexpr std::complex<double> h_xGate[4] = {0.0, 1.0, 1.0, 0.0};
constexpr auto sizeBytes = 4 * sizeof(std::complex<double>);
void *d_gate{nullptr};
Expand All @@ -43,8 +44,8 @@ TensorNetState::TensorNetState(const std::vector<int> &basisState,
}

std::unique_ptr<TensorNetState> TensorNetState::clone() const {
return createFromOpTensors(m_numQubits, m_tensorOps, scratchPad,
m_cutnHandle);
return createFromOpTensors(m_numQubits, m_tensorOps, scratchPad, m_cutnHandle,
m_randomEngine);
}

void TensorNetState::applyGate(const std::vector<int32_t> &controlQubits,
Expand Down Expand Up @@ -166,6 +167,16 @@ TensorNetState::sample(const std::vector<int32_t> &measuredBitIds,
HANDLE_CUTN_ERROR(cutensornetSamplerConfigure(
m_cutnHandle, sampler, CUTENSORNET_SAMPLER_OPT_NUM_HYPER_SAMPLES,
&numHyperSamples, sizeof(numHyperSamples)));

// Generate a random seed from the backend simulator's random engine.
// Note: Even after a random seed setting at the user's level,
// consecutive `cudaq::sample` calls will still return different results
// (yet deterministic), i.e., the seed that we send to cutensornet should
// not be the user's seed.
const int32_t rndSeed = m_randomEngine();
HANDLE_CUTN_ERROR(cutensornetSamplerConfigure(
m_cutnHandle, sampler, CUTENSORNET_SAMPLER_CONFIG_DETERMINISTIC,
&rndSeed, sizeof(rndSeed)));
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}

// Prepare the quantum circuit sampler
Expand Down Expand Up @@ -591,12 +602,12 @@ std::complex<double> TensorNetState::computeExpVal(

std::unique_ptr<TensorNetState> TensorNetState::createFromMpsTensors(
const std::vector<MPSTensor> &in_mpsTensors, ScratchDeviceMem &inScratchPad,
cutensornetHandle_t handle) {
cutensornetHandle_t handle, std::mt19937 &randomEngine) {
LOG_API_TIME();
if (in_mpsTensors.empty())
throw std::invalid_argument("Empty MPS tensor list");
auto state = std::make_unique<TensorNetState>(in_mpsTensors.size(),
inScratchPad, handle);
inScratchPad, handle, randomEngine);
std::vector<const int64_t *> extents;
std::vector<void *> tensorData;
for (const auto &tensor : in_mpsTensors) {
Expand All @@ -613,10 +624,11 @@ std::unique_ptr<TensorNetState> TensorNetState::createFromMpsTensors(
/// operators.
std::unique_ptr<TensorNetState> TensorNetState::createFromOpTensors(
std::size_t numQubits, const std::vector<AppliedTensorOp> &opTensors,
ScratchDeviceMem &inScratchPad, cutensornetHandle_t handle) {
ScratchDeviceMem &inScratchPad, cutensornetHandle_t handle,
std::mt19937 &randomEngine) {
LOG_API_TIME();
auto state =
std::make_unique<TensorNetState>(numQubits, inScratchPad, handle);
std::make_unique<TensorNetState>(numQubits, inScratchPad, handle, randomEngine);
for (const auto &op : opTensors)
if (op.isUnitary)
state->applyGate(op.controlQubitIds, op.targetQubitIds, op.deviceData,
Expand All @@ -641,14 +653,13 @@ TensorNetState::reverseQubitOrder(std::span<std::complex<double>> stateVec) {
return ket;
}

std::unique_ptr<TensorNetState>
TensorNetState::createFromStateVector(std::span<std::complex<double>> stateVec,
ScratchDeviceMem &inScratchPad,
cutensornetHandle_t handle) {
std::unique_ptr<TensorNetState> TensorNetState::createFromStateVector(
std::span<std::complex<double>> stateVec, ScratchDeviceMem &inScratchPad,
cutensornetHandle_t handle, std::mt19937 &randomEngine) {
LOG_API_TIME();
const std::size_t numQubits = std::log2(stateVec.size());
auto state =
std::make_unique<TensorNetState>(numQubits, inScratchPad, handle);
std::make_unique<TensorNetState>(numQubits, inScratchPad, handle, randomEngine);

// Support initializing the tensor network in a specific state vector state.
// Note: this is not intended for large state vector but for relatively small
Expand Down
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