{ "cells": [ { "cell_type": "markdown", "id": "6b7abc7b-b435-43d1-9fd8-c349ee8710f3", "metadata": {}, "source": [ "---\n", "title: \"Administrar recursos informáticos y de datos de Qiskit Serverless\"\n", "description: \"Gestione los recursos informáticos y los datos en todo su patrón Qiskit con Qiskit Serverless.\"\n", "---\n", "\n", "\n", "\n", "# Administrar recursos informáticos y de datos de Qiskit Serverless\n", "\n" ] }, { "cell_type": "markdown", "id": "3b0771d6-95c9-46dc-955a-f8702f6a2632", "metadata": { "tags": [ "version-info" ] }, "source": [ "\n", " \n", " El código de esta página se ha desarrollado teniendo en cuenta los siguientes requisitos.\n", " Recomendamos utilizar estas versiones o versiones más recientes.\n", "\n", " ```\n", " qiskit[all]~=2.0.0\n", " qiskit-ibm-runtime~=0.37.0\n", " qiskit-serverless~=0.22.0\n", " ```\n", " \n", "\n", "\n" ] }, { "cell_type": "markdown", "id": "95b2f280-f685-455f-83e9-b172445d7c6a", "metadata": {}, "source": [ "\n", " **Qiskit Serverless está siendo actualizado y sus características están cambiando rápidamente.** Durante esta fase de desarrollo, encontrará las notas de la versión y la documentación más reciente en la página [« Qiskit Serverless » (Notas de la versión y documentación) de GitHub](https://qiskit.github.io/qiskit-serverless/index.html).\n", "\n", "\n", "Con Qiskit Serverless, puedes gestionar la computación y los datos a través de tu [patrón Qiskit](/docs/guides/intro-to-patterns), incluyendo CPUs, QPUs y otros aceleradores de computación.\n", "\n" ] }, { "cell_type": "markdown", "id": "380354c0-5cab-464d-b10f-c94055de3605", "metadata": {}, "source": [ "\n", "\n", "## Establecer estados detallados\n", "\n", "Las cargas de trabajo sin servidor tienen varias etapas a lo largo de un flujo de trabajo. Por defecto, los siguientes estados son visibles con `job.status()`:\n", "\n", "* \\*\\*`QUEUED`\\*\\*la carga de trabajo está en cola para los recursos clásicos\n", "* \\*\\*`INITIALIZING`\\*\\*la carga de trabajo\n", "* \\*\\*`RUNNING`\\*\\*la carga de trabajo se ejecuta actualmente en recursos clásicos\n", "* \\*\\*`DONE`\\*\\*la carga de trabajo se ha completado con éxito\n", "\n", "También puede establecer estados personalizados que describan con más detalle la etapa específica del flujo de trabajo, como se indica a continuación.\n", "\n", "\n", " Si estás ejecutando las celdas de código localmente en un cuaderno, verás el [comando ](https://ipython.readthedocs.io/en/stable/interactive/magics.html#cellmagic-writefile)`%%writefile` mágico. Al ejecutar las celdas con este comando especial, estas se guardan en el disco en lugar de ejecutarse.\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "a69df8bc-5033-45bf-a837-cffa9d29b844", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Writing ./source_files/status_example.py\n" ] } ], "source": [ "%%writefile ./source_files/status_example.py\n", "\n", "# If you include the preceding `%%writefile` command (visible only when you read this locally in a\n", "# notebook), running this cell saves to disk rather than executing the code.\n", "\n", "from qiskit_serverless import update_status, Job\n", "\n", "# # If your function has a mapping stage, particularly application functions, you can set the status\n", "# to \"RUNNING: MAPPING\" as follows:\n", "update_status(Job.MAPPING)\n", "\n", "# # While handling transpilation, error suppression, and so forth, you can set the status to\n", "# \"RUNNING: OPTIMIZING_FOR_HARDWARE\":\n", "update_status(Job.OPTIMIZING_HARDWARE)\n", "\n", "# # After you submit jobs to Qiskit Runtime, the underlying quantum job will be queued. You can set\n", "# status to \"RUNNING: WAITING_FOR_QPU\":\n", "update_status(Job.WAITING_QPU)\n", "\n", "# # When the Qiskit Runtime job starts running on the QPU, set the following status\n", "# \"RUNNING: EXECUTING_QPU\":\n", "update_status(Job.EXECUTING_QPU)\n", "\n", "## Once QPU is completed and post-processing has begun, set the status \"RUNNING: POST_PROCESSING\":\n", "update_status(Job.POST_PROCESSING)" ] }, { "cell_type": "markdown", "id": "a8746eae-6f15-4faf-8771-0f3062efc723", "metadata": {}, "source": [ "Tras completar con éxito esta carga de trabajo (con `save_result()`), este estado se actualizará a `DONE` automáticamente.\n", "\n" ] }, { "cell_type": "markdown", "id": "b2d40a63-3359-46e9-8f1b-4746b449b407", "metadata": {}, "source": [ "\n", "\n", "## Flujos de trabajo paralelos\n", "\n", "Para tareas clásicas que se pueden paralelizar, utiliza el `@distribute_task` decorador para definir los requisitos de computación necesarios para ejecutar una tarea. Empieza recordando el `transpile_remote.py` ejemplo del tema «[Escribe tu primer programa en Qiskit Serverless](/docs/guides/serverless-first-program) » con el siguiente código.\n", "\n", "El siguiente código requiere que ya haya [guardado sus credenciales](/docs/guides/cloud-setup).\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "475d82f0-15cc-4db3-b3b0-54b07822b2a0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Writing ./source_files/transpile_remote.py\n" ] } ], "source": [ "%%writefile ./source_files/transpile_remote.py\n", "\n", "# If you include the preceding `%%writefile` command (visible only when you read this locally in a\n", "# notebook), running this cell saves to disk rather than executing the code.\n", "\n", "from qiskit.transpiler import generate_preset_pass_manager\n", "from qiskit_ibm_runtime import QiskitRuntimeService\n", "from qiskit_serverless import distribute_task\n", "\n", "service = QiskitRuntimeService()\n", "\n", "@distribute_task(target={\"cpu\": 1})\n", "def transpile_remote(circuit, optimization_level, backend):\n", " \"\"\"\n", " Transpiles an abstract circuit (or list of circuits)\n", " into an ISA circuit for a given backend.\n", " \"\"\"\n", " pass_manager = generate_preset_pass_manager(\n", " optimization_level=optimization_level,\n", " backend=service.backend(backend)\n", " )\n", " isa_circuit = pass_manager.run(circuit)\n", " return isa_circuit" ] }, { "cell_type": "markdown", "id": "a5914f1d-f898-4db4-8d1e-ccc8081883b9", "metadata": {}, "source": [ "En este ejemplo, ha decorado la función `transpile_remote()` con `@distribute_task(target={\"cpu\": 1})`. Cuando se ejecuta, crea una tarea de trabajador paralela asíncrona con un único núcleo de CPU y devuelve una referencia para realizar un seguimiento del trabajador. Para obtener el resultado, pase la referencia a la función `get()` . Podemos utilizarlo para ejecutar múltiples tareas paralelas:\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "e8fd31e6-9ab9-4d75-9ef9-a2b9ff9ad37a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Appending to ./source_files/transpile_remote.py\n" ] } ], "source": [ "%%writefile --append ./source_files/transpile_remote.py\n", "\n", "# If you include the preceding `%%writefile` command\n", "# (visible only when you read this locally in a\n", "# notebook), running this cell saves to disk rather than\n", "# executing the code.\n", "\n", "from time import time\n", "from qiskit_serverless import get, get_arguments, save_result, update_status, Job\n", "\n", "# Get arguments\n", "arguments = get_arguments()\n", "circuit = arguments.get(\"circuit\")\n", "optimization_level = arguments.get(\"optimization_level\")\n", "backend = arguments.get(\"backend\")" ] }, { "cell_type": "code", "execution_count": null, "id": "74fdcd4a-01cd-46ca-aa24-2a8a3605346f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Appending to ./source_files/transpile_remote.py\n" ] } ], "source": [ "%%writefile --append ./source_files/transpile_remote.py\n", "# If you include the preceding `%%writefile` command\n", "# (visible only when you read this locally in a\n", "# notebook), running this cell saves to disk rather than executing the code.\n", "\n", "# Start distributed transpilation\n", "update_status(Job.OPTIMIZING_HARDWARE)\n", "\n", "start_time = time()\n", "transpile_worker_references = [\n", " transpile_remote(circuit, optimization_level, backend)\n", " for circuit in arguments.get(\"circuit_list\")\n", "]\n", "\n", "transpiled_circuits = get(transpile_worker_references)\n", "end_time = time()" ] }, { "cell_type": "code", "execution_count": null, "id": "81696ede-3aa5-4e8c-9d35-fdd70c1bf4db", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Appending to ./source_files/transpile_remote.py\n" ] } ], "source": [ "%%writefile --append ./source_files/transpile_remote.py\n", "# If you include the preceding `%%writefile` command\n", "# (visible only when you read this locally in a\n", "# notebook), running this cell saves to disk rather than executing the code.\n", "\n", "# Save result, with metadata\n", "result = {\n", " \"circuits\": transpiled_circuits,\n", " \"metadata\": {\n", " \"resource_usage\": {\n", " \"RUNNING: OPTIMIZING_FOR_HARDWARE\": {\n", " \"CPU_TIME\": end_time - start_time,\n", " \"QPU_TIME\": 0,\n", " },\n", " }\n", " },\n", "}\n", "\n", "save_result(result)" ] }, { "cell_type": "markdown", "id": "611fe030-4494-46b5-9ea1-9678ac513210", "metadata": {}, "source": [ "\n", "\n", "### Explora diferentes configuraciones de tareas\n", "\n", "Puedes asignar de forma flexible CPU, GPU y memoria a tus tareas a través de `@distribute_task()`. Para Qiskit Serverless en IBM Quantum® Platform, cada programa está equipado con 16 núcleos de CPU y 32 GB de RAM, que se pueden asignar dinámicamente según sea necesario.\n", "\n", "Los núcleos de CPU pueden asignarse como núcleos de CPU completos, o incluso como asignaciones fraccionadas, como se muestra a continuación.\n", "\n", "La memoria se asigna en número de bytes. Recordemos que hay 1024 bytes en un kilobyte, 1024 kilobytes en un megabyte y 1024 megabytes en un gigabyte. Para asignar 2 GB de memoria a tu trabajador, necesitas asignar `\"mem\": 2 * 1024 * 1024 * 1024`.\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "cea90969-cfbf-4181-9ffa-524f3709dc69", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Appending to ./source_files/transpile_remote.py\n" ] } ], "source": [ "%%writefile --append ./source_files/transpile_remote.py\n", "# If you include the preceding `%%writefile` command\n", "# (visible only when you read this locally in a\n", "# notebook), running this cell saves to disk rather than executing the code.\n", "\n", "@distribute_task(target={\n", " \"cpu\": 16,\n", " \"mem\": 2 * 1024 * 1024 * 1024\n", "})\n", "def transpile_remote(circuit, optimization_level, backend):\n", " return None" ] }, { "cell_type": "markdown", "id": "6bc45489-56d0-4f46-8659-9df4d1555516", "metadata": {}, "source": [ "\n", "\n", "## Gestiona los datos de todo tu programa\n", "\n", "Qiskit Serverless le permite gestionar archivos en el directorio `/data` a través de todos sus programas. Esto incluye varias limitaciones:\n", "\n", "* Actualmente sólo se admiten los archivos `tar` y `h5`\n", "* Esto es sólo un almacenamiento plano `/data` , y no puede tener `/data/folder/` subdirectorios\n", "\n", "A continuación se muestra cómo cargar archivos. Asegúrate de haber iniciado sesión en Qiskit Serverless con tu cuenta de IBM Quantum (consulta las instrucciones en [Subir a Qiskit Serverless](/docs/guides/serverless-first-program#upload-to-qiskit-serverless) ).\n", "\n" ] }, { "cell_type": "code", "execution_count": 10, "id": "0183278f-8ce3-4466-9255-097b2d211052", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'{\"message\":\"/usr/src/app/media/5e1f442128cdf60018496a04/transpile_demo.tar\"}'" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import tarfile\n", "from qiskit_serverless import IBMServerlessClient\n", "\n", "# Create a tar\n", "filename = \"transpile_demo.tar\"\n", "file = tarfile.open(filename, \"w\")\n", "file.add(\"./source_files/transpile_remote.py\")\n", "file.close()\n", "\n", "# Get a reference to a QiskitFunction\n", "serverless = IBMServerlessClient()\n", "transpile_remote_demo = next(\n", " program\n", " for program in serverless.list()\n", " if program.title == \"transpile_remote_serverless\"\n", ")\n", "\n", "# Upload the tar to Serverless data directory\n", "serverless.file_upload(file=filename, function=transpile_remote_demo)" ] }, { "cell_type": "markdown", "id": "4f762470-945f-48d5-a65b-c60d3b2dae3f", "metadata": {}, "source": [ "A continuación, puedes listar todos los archivos de tu directorio `data` . Todos los programas pueden acceder a estos datos.\n", "\n" ] }, { "cell_type": "code", "execution_count": 11, "id": "14241fc4-d0cb-4803-8752-a460e1f48708", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['classifier_name.pkl.tar', 'output.json.tar', 'transpile_demo.tar']" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "serverless.files(function=transpile_remote_demo)" ] }, { "cell_type": "markdown", "id": "a97bd83e-8250-43bb-b1c4-d40d822c7ba2", "metadata": {}, "source": [ "Esto puede hacerse desde un programa utilizando `file_download()` para descargar el archivo al entorno del programa, y descomprimiendo el `tar`.\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "ef649b2a-ed95-4dd2-89d9-61438faa7c1e", "metadata": {}, "outputs": [], "source": [ "%%writefile ./source_files/extract_tarfile.py\n", "# If you include the preceding `%%writefile` command\n", "# (visible only when you read this locally in a\n", "# notebook), running this cell saves to disk rather than executing the code.\n", "\n", "import tarfile\n", "from qiskit_serverless import IBMServerlessClient\n", "\n", "# For `token`, use the 44-character API_KEY you created\n", "# and saved from the IBM Quantum Platform Home dashboard\n", "serverless = IBMServerlessClient(token=\"\")\n", "files = serverless.files()\n", "demo_file = files[0]\n", "downloaded_tar = serverless.file_download(demo_file)\n", "\n", "\n", "with tarfile.open(downloaded_tar, 'r') as tar:\n", " tar.extractall()" ] }, { "cell_type": "markdown", "id": "5b93dbdb-2060-468b-8496-ba98142a780b", "metadata": {}, "source": [ "En este punto, su programa puede interactuar con los archivos, como lo haría con un experimento local. `file_upload()` `file_download()`, y `file_delete()` pueden ser llamados desde su experimento local, o desde su programa cargado, para una gestión de datos consistente y flexible.\n", "\n" ] }, { "cell_type": "markdown", "id": "a004dd78-0e0a-4a3b-83cb-333469533ef6", "metadata": {}, "source": [ "\n", "\n", "## Próximos pasos\n", "\n", "\n", " * Consulte un ejemplo completo que [adapta el código existente a Qiskit Serverless](/docs/guides/serverless-port-code).\n", " * Lea un artículo en el que los investigadores utilizaron Qiskit Serverless y la supercomputación centrada en la cuántica para [explorar la química cuántica](https://arxiv.org/abs/2405.05068v1).\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "id": "a1b8767d", "source": "© IBM Corp., 2017-2026" } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3" } }, "nbformat": 4, "nbformat_minor": 2 }