@brief Run `cudaq::observe` on the provided kernel and spin operator.
| 108 | |
| 109 | /// @brief Run `cudaq::observe` on the provided kernel and spin operator. |
| 110 | static observe_result |
| 111 | pyObservePar(const PyParType &type, const std::string &shortName, |
| 112 | mlir::ModuleOp module, spin_op &spin_operator, int shots, |
| 113 | std::optional<noise_model> noise, nanobind::args args) { |
| 114 | // Ensure the user input is correct. |
| 115 | auto &platform = get_platform(); |
| 116 | if (!platform.supports_task_distribution()) |
| 117 | throw std::runtime_error( |
| 118 | "The current quantum_platform does not support parallel distribution " |
| 119 | "of observe() expectation value computations."); |
| 120 | |
| 121 | // FIXME Handle noise modeling with parallel distribution. |
| 122 | if (noise) |
| 123 | TODO("Handle Noise Models with python parallel distribution."); |
| 124 | |
| 125 | auto nQpus = platform.num_qpus(); |
| 126 | if (type == PyParType::thread) { |
| 127 | // Does this platform expose more than 1 QPU |
| 128 | // If so, let's distribute the work amongst the QPUs |
| 129 | if (nQpus == 1) |
| 130 | printf( |
| 131 | "[cudaq::observe warning] distributed observe requested but only 1 " |
| 132 | "QPU available. no speedup expected.\n"); |
| 133 | nanobind::gil_scoped_release release; |
| 134 | return detail::distributeComputations( |
| 135 | [&](std::size_t i, const spin_op &op) { |
| 136 | nanobind::gil_scoped_acquire acquire; |
| 137 | return pyObserveAsync(shortName, module, op, i, shots, args); |
| 138 | }, |
| 139 | spin_operator, nQpus); |
| 140 | } |
| 141 | |
| 142 | if (!mpi::is_initialized()) |
| 143 | throw std::runtime_error("Cannot use mpi multi-node observe() without " |
| 144 | "MPI (did you initialize MPI?)."); |
| 145 | |
| 146 | // Necessarily has to be MPI |
| 147 | // Get the rank and the number of ranks |
| 148 | auto rank = mpi::rank(); |
| 149 | auto nRanks = mpi::num_ranks(); |
| 150 | |
| 151 | // Each rank gets a subset of the spin terms |
| 152 | auto spins = spin_operator.distribute_terms(nRanks); |
| 153 | |
| 154 | // Get this rank's set of spins to compute |
| 155 | auto localH = spins[rank]; |
| 156 | |
| 157 | // Distribute locally, i.e. to the local nodes QPUs |
| 158 | nanobind::gil_scoped_release release; |
| 159 | auto localRankResult = detail::distributeComputations( |
| 160 | [&](std::size_t i, const spin_op &op) { |
| 161 | nanobind::gil_scoped_acquire acquire; |
| 162 | return pyObserveAsync(shortName, module, op, i, shots, args); |
| 163 | }, |
| 164 | localH, nQpus); |
| 165 | |
| 166 | // combine all the data via an all_reduce |
| 167 | auto exp_val = localRankResult.expectation(); |
no test coverage detected