BTC_01_PL: Probability Loading

This part of the repository is associated with the Benchmark Test Case (BTC) 01: Probability Loading.

Configure the kernel_configuration dictionary at the end of the my_benchmark_execution.py file. The files will be saved in the Results folder (you can change the folder in key argument saving_folder of the benchmark_arguments dictionary). Then you should execute the following command line:

python my_benchmark_execution.py

If you want a complete execution and create the complete JSON file with the complete information of the benchmark results following the NEASQC JSON Schema you can instead execute the script benchmark_exe.sh:

bash benchmark_exe.sh

All the results files and the corresponding JSON will be stored in the Results folder.

my_benchmark_execution

This module execute a complete BTC of the PL kernel

class tnbs.BTC_01_PL.my_benchmark_execution.KERNEL_BENCHMARK(**kwargs)

Bases: object

Class for execute a Kernerl benchmark

exe(): Execute complete Benchmark WorkFlow

save(save, save_name, input_pdf, save_mode)

For saving panda DataFrames to csvs

Parameters:

save (bool) – For saving or not
save_nam (str) – name for file
input_pdf (pandas DataFrame)
save_mode (str) – saving mode: overwrite (w) or append (a)

tnbs.BTC_01_PL.my_benchmark_execution.build_iterator(**kwargs): For building the iterator of the benchmark

tnbs.BTC_01_PL.my_benchmark_execution.compute_samples(**kwargs)

This functions computes the number of executions of the benchmark for assure an error r with a confidence of alpha

Parameters:: kwargs (keyword arguments) – For configuring the sampling computation
Returns:: samples – DataFrame with the number of executions for each integration interval
Return type:: pandas DataFrame

tnbs.BTC_01_PL.my_benchmark_execution.run_code(iterator_step, repetitions, stage_bench, **kwargs)

For configuration and execution of the benchmark kernel.

Parameters:

iterator_step (tuple) – tuple with elements from iterator built from build_iterator.
repetitions (list) – number of repetitions for each execution
stage_bench (str) – benchmark stage. Only: benchmark, pre-benchamrk
kwargs (keyword arguments) – for configuration of the benchmark kernel

Returns:

metrics (pandas DataFrame) – DataFrame with the desired metrics obtained for the integral computation
save_name (string) – Desired name for saving the results of the execution

tnbs.BTC_01_PL.my_benchmark_execution.summarize_results(**kwargs): Create summary with statistics

my_benchmark_info

This module gathers all mandatory information for Benchmarks field of NEASQC JSON report for a BTC PL kernel execution.

tnbs.BTC_01_PL.my_benchmark_info.my_api(**kwargs): Collect the information about the used APIs

tnbs.BTC_01_PL.my_benchmark_info.my_benchmark_info(**kwargs): Complete WorkFlow for getting all the benchmar informated related info

tnbs.BTC_01_PL.my_benchmark_info.my_benchmark_kernel(**kwargs): Name for the benchmark Kernel

tnbs.BTC_01_PL.my_benchmark_info.my_classical_compilation(**kwargs): Information about the classical compilation part of the benchmark

tnbs.BTC_01_PL.my_benchmark_info.my_endtime(**kwargs): Providing the end time of the benchmark

tnbs.BTC_01_PL.my_benchmark_info.my_metadata_info(**kwargs): Other important info user want to store in the final json.

tnbs.BTC_01_PL.my_benchmark_info.my_programlanguage(**kwargs): Getting the programing language used for benchmark

tnbs.BTC_01_PL.my_benchmark_info.my_programlanguage_vendor(**kwargs): Getting the version of the programing language used for benchmark

tnbs.BTC_01_PL.my_benchmark_info.my_programlanguage_version(**kwargs): Getting the version of the programing language used for benchmark

tnbs.BTC_01_PL.my_benchmark_info.my_quantum_compilation(**kwargs): Information about the quantum compilation part of the benchmark

tnbs.BTC_01_PL.my_benchmark_info.my_starttime(**kwargs): Providing the start time of the benchmark

tnbs.BTC_01_PL.my_benchmark_info.my_timemethod(**kwargs): Providing the method for getting the times

my_benchmark_summary

This module is for properly formating the Results sub-field of Benchmarks field of the NEASQC JSON report by gathering the results of a complete BTC of the PL kernel.

tnbs.BTC_01_PL.my_benchmark_summary.summarize_results(**kwargs): Mandatory code for properly present the benchmark results following the NEASQC jsonschema

my_environment_info

Module for gathering different hardware information for main fields of NEASQC report generation for reporting BTC of a PL kernel

tnbs.BTC_01_PL.my_environment_info.my_QPUCPUConnection(**kwargs): Connection between the QPU and the CPU used in the benchmark

tnbs.BTC_01_PL.my_environment_info.my_cpu_model(**kwargs): model of the cpu used in the benchmark

tnbs.BTC_01_PL.my_environment_info.my_frecuency(**kwargs): Frcuency of the used CPU

tnbs.BTC_01_PL.my_environment_info.my_ideal_qpu(**kwargs): Define an ideal qpu

tnbs.BTC_01_PL.my_environment_info.my_machine_name(**kwargs): Name of the machine where the benchmark was performed

tnbs.BTC_01_PL.my_environment_info.my_network(**kwargs): Network connections if several QPUs are used

tnbs.BTC_01_PL.my_environment_info.my_noisy_qpu(qpu_config): Define an ideal qpu

tnbs.BTC_01_PL.my_environment_info.my_organisation(**kwargs): Given information about the organisation how uploads the benchmark

tnbs.BTC_01_PL.my_environment_info.my_qpu(**kwargs): Complete info about the used QPU

tnbs.BTC_01_PL.my_environment_info.my_qpu_model(**kwargs): Name of the model of the QPU

neasqc_benchmark

Module for complete generation of NEASQC Benhmark Test Case report for a BTC PL kernel

class tnbs.BTC_01_PL.neasqc_benchmark.BENCHMARK

Bases: object

Generic class for benchmark applications in NEASQC

exe(info)

Method for filling the report.

Parameters:: info (dictionary)

save(filename)

Method for saving the generated benchmark report

Parameters:: filename (string) – pathf for storing the benchmark report

set_benchmark_info(benchmark_info)

Method for filling Benchmarks field.

Parameters:: benchmark_info (OrderedDict)

set_cpu_model(cpu_model)

Method for filling CPUModel field.

Parameters:: cpu_model (str)

set_frecuency(frecuency)

Method for filling Frequency field.

Parameters:: frecuency (int)

set_machine_name(node_name)

Method for filling MachineName field.

Parameters:: node_name (string)

set_network(network)

Method for filling Network field.

Parameters:: network (OrderedDict)

set_organisation(organisation)

Method for filling ReportOrganization field.

Parameters:: organisation (string)

set_qpu_cpu_connection(qpu_cpu_connection)

Method for filling QPUCPUConnection field.

Parameters:: qpu_cpu_connection (OrderedDict)

set_qpu_description(qpu_description)

Method for filling QPUDescription field.

Parameters:: qpu_description (OrderedDict)

set_qpu_model(qpu_model)

Method for filling QPUModel field.

Parameters:: qpu_model (str)

validate(): Method for validating the generated benchmark report.