Code zu Qiskit Serverless portieren

Das folgende Beispiel zeigt, wie du bestehenden Code portierst, um Qiskit Serverless zu nutzen.

hinweis

Der folgende Code setzt voraus, dass du deine Zugangsdaten gespeichert hast. Falls nicht, folge den Anweisungen unter IBM Cloud-Konto einrichten, um dich mit deinem API-Schlüssel zu authentifizieren.

Das Experiment aktualisieren

Local Experiment

from qiskit.transpiler import generate_preset_pass_manager
from qiskit_ibm_runtime import QiskitRuntimeService
from qiskit.circuit.random import random_circuit

qc_random = [(random_circuit(20, 20, measure=True)) for _ in range(30)]
optimization_level = 3

service = QiskitRuntimeService(channel="ibm_quantum_platform")
backend = service.get_backend(backend_name)

pass_manager = generate_preset_pass_manager(
    optimization_level=optimization_level, backend=backend
)

# @distribute_task(target={"cpu": 1})
def transpile_parallel(circuit, pass_manager):
    """Distributed transpilation for an abstract circuit into an ISA circuit for a given backend."""

    isa_circuit = pass_manager.run(circuit)

    return isa_circuit

transpiled_circuits = [
    transpile_parallel(circuit, pass_manager)
    for circuit in circuits
]

print(transpiled_circuits)

Serverless

# transpile_remote.py

from qiskit.transpiler import generate_preset_pass_manager
from qiskit_serverless import get_arguments, save_result, distribute_task, get
from qiskit_ibm_runtime import QiskitRuntimeService

# Get program arguments
arguments = get_arguments()
circuits = arguments.get("circuits")
backend_name = arguments.get("backend_name")
optimization_level = arguments.get("optimization_level")
pass_manager = generate_preset_pass_manager(
optimization_level=optimization_level, backend=backend_name
)

# Distribute task across workers
@distribute_task(target={"cpu": 1})
def transpile_parallel(circuit, pass_manager):
"""Distributed transpilation for an abstract circuit into an ISA circuit for a given backend."""

isa_circuit = pass_manager.run(circuit)

return isa_circuit

try:
# Get backend
service = QiskitRuntimeService()
backend = service.get_backend(backend_name)

# run distributed tasks as async function
# we get task references as a return type
sample_task_references = [
    transpile_parallel(circuit, pass_manager)
    for circuit in circuits
]

# now we need to collect results from task references
results = get(sample_task_references)

# Return results
save_result({
    "transpiled_circuits": results
})

except Exception as e:
# Exception handling
import traceback
print(traceback.format_exc())

In Qiskit Serverless hochladen

Folge den Anweisungen auf der Seite Einführung in Qiskit Functions, um dich mit deinem API-Schlüssel zu authentifizieren.

from qiskit_ibm_catalog import QiskitServerless, QiskitFunction

# Authenticate to the remote cluster and submit the pattern for remote execution.
serverless = QiskitServerless()

transpile_remote_demo = QiskitFunction(
    title="transpile_remote_serverless",
    entrypoint="transpile_remote.py",
    working_dir="./source_files/",
)

serverless.upload(transpile_remote_demo)

Ausgabe

'transpile_remote_serverless'

Remote in Qiskit Serverless ausführen

from qiskit.circuit.random import random_circuit
from qiskit_ibm_runtime import QiskitRuntimeService

# Setup inputs
qc_random = [(random_circuit(20, 20, measure=True)) for _ in range(30)]
backend = "ibm_brisbane"
optimization_level = 3

# Running program
transpile_remote_serverless = serverless.load('transpile_remote_serverless')
job = transpile_remote_serverless.run(
    circuits=qc_random,
    backend=backend,
    optimization_level=optimization_level
)

job.job_id

Ausgabe

'727e921d-512d-4b7d-af97-fe29e93ce7ea'

Nächste Schritte

Empfehlungen

• Lies einen Fachartikel, in dem Forscher Qiskit Serverless und quantenzentriertes Supercomputing nutzten, um Quantenchemie zu erforschen.