Commit 06067492 authored by Gopalakrishnan Meena, Murali's avatar Gopalakrishnan Meena, Murali
Browse files

Merge branch 'qiskit1.0-port' into 'main' 

Qiskit1.0 port

See merge request !1
parents 5babd843 3fed60c5

README.md

+67 −50
Original line number Diff line number Diff line
@@ -40,46 +40,22 @@ All developments were done on [OLCF Andes](https://docs.olcf.ornl.gov/systems/an 
      wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh

      bash Miniconda3-latest-Linux-x86_64.sh -b -p /global/common/software/m4454/env_muraligm

      source /global/common/software/m4454/env_muraligm/bin/activate

      module load cudatoolkit/11.7

      module load cudatoolkit/12.0

      ```

      </details>



      * Since the QLSA circuit generator ([HHL](https://github.com/anedumla/quantum_linear_solvers)) uses an older qiskit version requiring qiskit-terra, we need to make two envs: (1) to generate the circuit and (2) to run the circuit using qiskit 1.0

      1. Install libraries to generate circuit

            * Make custom conda env

            ```

      conda create --name env_custom python=3.9

      conda activate env_custom

      ```

      * Install qiskit

            conda create --name qlsa-circuit python=3.11

            conda activate qlsa-circuit

            ```

      pip install -r requirements.txt --no-cache-dir

      ```

    * **NOTE:** Make sure to test the installation with the sample codes provided: 

      1. Test qiskit installation: [`test_qiskit_installation.py`](test_qiskit_installation.py)



            * Install qiskit and [linear solver](https://github.com/anedumla/quantum_linear_solvers) package

            ```

            python test_qiskit_installation.py -backtyp ideal

            pip install -r requirements_circuit.txt --no-cache-dir

            ```



            <details><summary>Sample output from the test code:</summary>



            ```

            Backend: QasmSimulator('qasm_simulator')

            Job status is JobStatus.DONE



            Total count for 00 and 11 are: {'00': 494, '11': 506}

                ┌───┐     ┌─┐   

            q_0:┤ H ├──■──┤M├───

                └───┘┌─┴─┐└╥┘┌─┐

            q_1:─────┤ X ├─╫─┤M├

                     └───┘ ║ └╥┘

            c:2/═══════════╩══╩═

                           0  1 

            ```

            </details>



            * Change `-backtyp` for different backends.

            * **NOTE:** To run using IBM Provider, you need to add your IBM Quantum Computing API KEY and instance to the `keys.sh` file and source activate it.

      2. Test [linear solver package](https://github.com/anedumla/quantum_linear_solvers): [`test_linear_solver.py`](test_linear_solver.py)

            * Test [linear solver package](https://github.com/anedumla/quantum_linear_solvers): [`test_linear_solver.py`](test_linear_solver.py)



            ```

            python test_linear_solver.py -nq 2
@@ -144,10 +120,47 @@ All developments were done on [OLCF Andes](https://docs.olcf.ornl.gov/systems/an 
            ```

            </details>

      

      2. Install libraries to run the circuit

            * Make custom conda env

            ```

            conda create --name qlsa-solver python=3.11

            conda activate qlsa-solver

            ```

            * Install qiskit and other packages

            ```

            pip install -r requirements_solver.txt --no-cache-dir

            ```



            * Test qiskit installation: [`test_qiskit_installation.py`](test_qiskit_installation.py)



            ```

            python test_qiskit_installation.py -backtyp ideal

            ```



            <details><summary>Sample output from the test code:</summary>



            ```

            Backend: QasmSimulator('qasm_simulator')

            Job status is JobStatus.DONE



            Total count for 00 and 11 are: {'00': 494, '11': 506}

                ┌───┐     ┌─┐   

            q_0:┤ H ├──■──┤M├───

                └───┘┌─┴─┐└╥┘┌─┐

            q_1:─────┤ X ├─╫─┤M├

                     └───┘ ║ └╥┘

            c:2/═══════════╩══╩═

                           0  1 

            ```

            </details>



            * Change `-backtyp` for different backends.

            * **NOTE:** To run using IBM Provider, you need to add your IBM Quantum Computing API KEY and instance to the `keys.sh` file and source activate it.



2. Install GPU version of Aer simulator (skip for Frontier):



    ```

    pip install qiskit-aer-gpu==0.13.3 --no-cache-dir

    pip install qiskit-aer-gpu==0.14.2 --no-cache-dir

    ```

    <details><summary>Notes for Perlmutter:</summary>
@@ -157,11 +170,15 @@ All developments were done on [OLCF Andes](https://docs.olcf.ornl.gov/systems/an 
      ```

      Or

      ```

      export LD_LIBRARY_PATH=/global/common/software/m4454/env_muraligm/envs/env_custom/lib/python3.9/site-packages/nvidia/cuda_runtime/lib:/global/common/software/m4454/env_muraligm/envs/env_custom/lib/python3.9/site-packages/cuquantum/lib:/global/common/software/m4454/env_muraligm/envs/env_custom/lib/python3.9/site-packages/cutensor/lib:$LD_LIBRARY_PATH

      export LD_LIBRARY_PATH=/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/nvidia/cuda_runtime/lib:/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/cuquantum/lib:/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/cutensor/lib:/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

      ```

      </details>



    * **NOTE:** Make sure to test the installation with the sample code provided: [`test_gpu.py`](test_gpu.py)

    * **NOTE:** Make sure to test the installation:

      ```

      python -c "from qiskit_aer import AerSimulator; simulator = AerSimulator(); print(simulator.available_devices())"

      ```

      * with the sample code provided: [`test_gpu.py`](test_gpu.py)



      ```

      python test_gpu.py -nq 2 --gpu
@@ -234,7 +251,7 @@ All developments were done on [OLCF Andes](https://docs.olcf.ornl.gov/systems/an 


      ```

      source /global/common/software/m4454/env_muraligm/bin/activate

      module load cudatoolkit/11.7

      module load cudatoolkit/12.0

      conda activate env_custom

      source init_perlmutter.sh

      ```
@@ -246,9 +263,9 @@ All developments were done on [OLCF Andes](https://docs.olcf.ornl.gov/systems/an 
      ```

      * Change `nq` to change size of system of equations

  

3. Run generalized QLSA script for various use-cases: [`linear_solver.py`](linear_solver.py)

3. Run QLSA circuit generator script for various use-cases: [`circuit_HHL.py`](circuit_HHL.py)

    ```

    srun -N1 -n1 -c2 python linear_solver.py -case [case-name] -casefile [case-var-file] -s [#-shots]  --savedata[optional but recommended]

    srun -N1 -n1 -c2 python circuit_HHL.py -case [case-name] -casefile [case-var-file] --savedata

    ```

      <details><summary>Sample output for Hele-Shaw flow, solving for pressure:</summary>

circuit_HHL.py

0 → 100644
+91 −0
Original line number Diff line number Diff line 
# Introduction

'''

Script to generate HHL circuit that solves any Ax=b problem.

Function `func_matrix_vector.py` is used to define A and b.

Sample code run script:

python circuit_HHL.py -case sample-tridiag -casefile input_vars.yaml --savedata

'''



import numpy as np



# Importing standard Qiskit libraries

from qiskit import QuantumCircuit, transpile

from qiskit import qpy

from qiskit_aer import AerSimulator

from linear_solvers import NumPyLinearSolver, HHL

# library to generate matrix and vector for linear system of equations

import func_matrix_vector as matvec



import time

import os

import argparse

import pickle



parser = argparse.ArgumentParser()

parser.add_argument("-case", "--case_name",  type=str, default='ideal', required=False, help="Name of the problem case: 'sample-tridiag', 'hele-shaw'")

parser.add_argument("-casefile", "--case_variable_file",  type=str, default='ideal', required=False, help="YAML file containing variables for the case: 'input_vars.yaml'")

parser.add_argument("--gpu", default=False, action='store_true', help="Use GPU backend for Aer simulator.")

parser.add_argument("--gpumultiple", default=False, action='store_true', help="Use multiple GPUs for the backend of Aer simulator.")

parser.add_argument("--drawcirc", default=False, action='store_true', help="Draw circuit.")



parser.add_argument("--savedata", default=False, action='store_true', help="Save data at `models/<filename>` with `<filename>` based on parameters.")

args = parser.parse_args()



if __name__ == '__main__':

    # Get system matrix and vector

    matrix, vector, input_vars = matvec.get_matrix_vector(args)

    MATRIX_SIZE = matrix.shape[0]

    n_qubits_matrix = int(np.log2(MATRIX_SIZE))

    

    # setup quantum backend

    backend_type = 'ideal'

    backend_method = 'statevector'

    print(f'Using \'{backend_type}\' simulator with \'{backend_method}\' backend')

    if args.gpu: backend = AerSimulator(method=backend_method, device='GPU')

    elif args.gpumultiple: backend = AerSimulator(method=backend_method, device='GPU', blocking_enable=True, blocking_qubits=18)

    else: backend = AerSimulator(method=backend_method)

    print(f'Backend: {backend}')

    

    # setup HHL solver

    # backend_init = qc_backend('ideal', 'statevector', args)

    hhl = HHL(quantum_instance=backend)

    

    # Solutions

    # classical soultion

    t = time.time()

    classical_solution = NumPyLinearSolver().solve(matrix, vector/np.linalg.norm(vector))

    t_classical = time.time() - t

    print(f'Time elapsed for classical:  {int(t_classical/60)} min {t_classical%60:.2f} sec', flush=True)

    

    # generate HHL circuit

    print(f'==================Generating HHL circuit================', flush=True)

    t = time.time()

    circ = hhl.construct_circuit(matrix, vector)

    t_circ = time.time() - t

    print(f'Time elapsed for generating HHL circuit:  {int(t_circ/60)} min {t_circ%60:.2f} sec')

    

    # Save data

    if args.savedata:

        circ_transpile = transpile(circ, backend)

        # save metadata (DON'T USE Pickle to save the circuit - only works for a given version)

        save_data = {   'args'                  : args,

                        'input_vars'            : input_vars,

                        'matrix'                : matrix,

                        'vector'                : vector,

                        't_circ'                : t_circ}

        filename = input_vars['savefilename'].format(**input_vars)

        savefilename = f'{filename}_circ_nqmatrix{n_qubits_matrix}'

        file = open(f'{savefilename}.pkl', 'wb')

        pickle.dump(save_data, file)

        file.close()

        # save circuit as QPY file

        with open(f'{savefilename}.qpy', 'wb') as fd:

            qpy.dump(circ_transpile, fd)

        print("===========Circuit saved===========")

    

    # Plot circuit

    if args.drawcirc:

        circ.measure_all()

        print(f'Circuit:\n{circ.draw()}', flush=True)

func_matrix_vector.py

+7 −7
Original line number Diff line number Diff line
@@ -30,9 +30,9 @@ def sample_tridiag(doc_id, args): 
    input_vars = get_yaml(args.case_variable_file, doc_id)

    print(f"Case: {input_vars['case_name']}")

    filename = input_vars['savefilename'].format(**input_vars)

    NUM_QUBITS = input_vars['NUM_QUBITS']

    n_qubits_matrix = input_vars['NQ_MATRIX']

    # custom systems

    MATRIX_SIZE = 2 ** NUM_QUBITS

    MATRIX_SIZE = 2 ** n_qubits_matrix

    

    # entries of the tridiagonal Toeplitz symmetric matrix

    a = 1
@@ -41,7 +41,7 @@ def sample_tridiag(doc_id, args): 
                 [-1, 0, 1],

                 shape=(MATRIX_SIZE, MATRIX_SIZE)).toarray()

    vector = np.array([1] + [0]*(MATRIX_SIZE - 1))

    return matrix, vector, filename

    return matrix, vector, input_vars



def Hele_Shaw(doc_id, args):

    input_vars = get_yaml(args.case_variable_file, doc_id)
@@ -138,7 +138,7 @@ def Hele_Shaw(doc_id, args): 
    

    if args.savedata == True:

        MATRIX_SIZE = A_herm.shape[0]

        NUM_QUBITS = int(np.log2(MATRIX_SIZE))

        n_qubits_matrix = int(np.log2(MATRIX_SIZE))

        save_data = {'P_in'                  : P_in,

                     'P_out'                 : P_out,

                     'U_top'                 : U_top,
@@ -151,14 +151,14 @@ def Hele_Shaw(doc_id, args): 
                     'ny'                    : ny,

                     'A_herm'                : A_herm,

                     'B_herm'                : B_herm,

                     'NUM_QUBITS'            : NUM_QUBITS,

                     'n_qubits_matrix'       : n_qubits_matrix,

                     'args'                  : args}

        file = open(f'{filename}_metadata.pkl', 'wb')

        pickle.dump(save_data, file)

        file.close()

        print("===========Metadata saved===========")

    

    return A_herm, B_herm, filename

    return A_herm, B_herm, input_vars



def Cylinder_2D(doc_id, args):

    input_vars = get_yaml(args.case_variable_file, doc_id)
@@ -195,7 +195,7 @@ def Cylinder_2D(doc_id, args): 
    

    print(f'Reformatted A_herm:\n{A_herm}\nB_herm:\n{B_herm}')

    print(f'Determinant of resulting matrix: {np.linalg.det(A_herm)}\nCondition # of resulting matrix: {np.linalg.cond(A_herm)}')

    return A_herm, B_herm, filename

    return A_herm, B_herm, input_vars



# Functions

def next_power_of_2(x):

func_qc.py

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init_perlmutter.sh

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Original line number Diff line number Diff line 
#!/bin/bash



export LD_LIBRARY_PATH=/global/common/software/m4454/env_muraligm/envs/env_custom/lib/python3.9/site-packages/nvidia/cuda_runtime/lib:/global/common/software/m4454/env_muraligm/envs/env_custom/lib/python3.9/site-packages/cuquantum/lib:/global/common/software/m4454/env_muraligm/envs/env_custom/lib/python3.9/site-packages/cutensor/lib:$LD_LIBRARY_PATH



export LD_LIBRARY_PATH=/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/nvidia/cuda_runtime/lib:/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/cuquantum/lib:/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/cutensor/lib:/global/common/software/m4454/env_muraligm/envs/qlsa-solver/lib/python3.11/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH