Tensornet (TN) with contractions to:
- dense vector
- expecation of given Pauli string
For each TN case:
- single node
- multi node with Message Passing Interface (MPI)
- multi node with NCCL
Tensornet (TN) with contractions to:
- dense vector (single node)

Sample Codes

Single Node

The code below shows an example of how to activate the Cuquantum TensorNetwork backend of Qibo.

import numpy as np
from qibo import Circuit, gates
import qibo

# Below shows 3 ways of setting the computation_settings
# Note that for MPS_enabled and expectation_enabled parameters the accepted inputs are boolean or a dictionary with the format shown below.
# If computation_settings is not specified, the default setting is used in which all booleans will be False. 
# This will trigger the dense vector computation of the tensornet.

    'MPI_enabled': False,
    'MPS_enabled': {
                "qr_method": False,
                "svd_method": {
                    "partition": "UV",
                    "abs_cutoff": 1e-12,
                },
            } ,
    'NCCL_enabled': False,
    'expectation_enabled': False
}

# computation_settings = {
#    'MPI_enabled': False,
#    'MPS_enabled': False,
#    'NCCL_enabled': False,
#    'expectation_enabled': {
#        'pauli_string_pattern': "IXZ"
# }

# computation_settings = {
#     'MPI_enabled': False,
#     'MPS_enabled': True,
#     'NCCL_enabled': False,
#     'expectation_enabled': False
# }

qibo.set_backend(backend="qibotn", runcard=computation_settings)

# Construct the circuit
c = Circuit(2)
# Add some gates
c.add(gates.H(0))
c.add(gates.H(1))

# Execute the circuit and obtain the final state
result = c()

print(result.state())

Multi-Node

Multi-node is enabled by setting either the MPI or NCCL enabled flag to True in the computation settings. Below shows the script to launch on 2 nodes with 2 GPUs each. $node_list contains the IP of the nodes assigned.

mpirun -n 4 -hostfile $node_list python test.py