QPU access time

import random
import dimod


N = 50

h = {}
J = {(i, j): random.gauss(0, 1) for i in range(N) for j in range(i + 1, N)}

bqm = dimod.BinaryQuadraticModel.from_ising(h, J)

from dwave.system import DWaveSampler, EmbeddingComposite


info_hists_dw2000q = []
info_hists_dwadv = []
for i in range(5):
    print('iteration:', i)

    dw2000q_sampler = EmbeddingComposite(DWaveSampler(profile='sigu-2000q'))
    dwadv_sampler = EmbeddingComposite(DWaveSampler(profile='sigu-adv'))

    sampleset_dw2000q = dw2000q_sampler.sample(bqm, num_reads=1000)
    sampleset_dwadv = dwadv_sampler.sample(bqm, num_reads=1000)

    info_hists_dw2000q.append(list(sampleset_dw2000q.info['timing'].values()))
    info_hists_dwadv.append(list(sampleset_dwadv.info['timing'].values()))

iteration: 0
iteration: 1
iteration: 2
iteration: 3
iteration: 4

import numpy as np
import pandas as pd


timing_infos = {}
timing_infos['2000Q(mean)'] = np.mean(info_hists_dw2000q, axis=0)
timing_infos['2000Q(std)'] = np.std(info_hists_dw2000q, axis=0)
timing_infos['Advantage(mean)'] = np.mean(info_hists_dwadv, axis=0)
timing_infos['Advantage(std)'] = np.std(info_hists_dwadv, axis=0)

index = sampleset_dw2000q.info['timing'].keys()
df_timing_info = pd.DataFrame(timing_infos, index=index)
df_timing_info

	2000Q(mean)	2000Q(std)	Advantage(mean)	Advantage(std)
qpu_sampling_time	238940.0	0.000000	128852.0	12294.425403
qpu_anneal_time_per_sample	20.0	0.000000	20.0	0.000000
qpu_readout_time_per_sample	198.0	0.000000	88.0	12.083046
qpu_access_time	250181.6	14.263239	154888.0	12294.912655
qpu_access_overhead_time	6863.4	424.893210	129140.0	140525.454538
qpu_programming_time	11241.6	14.263239	26036.0	3.633180
qpu_delay_time_per_sample	21.0	0.000000	21.0	0.000000
post_processing_overhead_time	1921.6	385.061346	9138.8	3283.009802
total_post_processing_time	5579.2	457.483289	294.0	160.278508
total_real_time	250181.6	14.263239	154888.0	12294.912655
run_time_chip	238940.0	0.000000	128852.0	12294.425403
anneal_time_per_run	20.0	0.000000	20.0	0.000000
readout_time_per_run	198.0	0.000000	88.0	12.083046

print(np.array(info_hists_dw2000q))

[[238940     20    198 250172   6316  11232     21   1378   5101 250172
  238940     20    198]
 [238940     20    198 250193   6997  11253     21   2467   5326 250193
  238940     20    198]
 [238940     20    198 250204   6592  11264     21   2163   6150 250204
  238940     20    198]
 [238940     20    198 250170   6834  11230     21   1626   6115 250170
  238940     20    198]
 [238940     20    198 250169   7578  11229     21   1974   5204 250169
  238940     20    198]]

print(np.array(info_hists_dwadv))

[[130900     20     90 156942  23032  26042     21  14514    110 156942
  130900     20     90]
 [108540     20     68 134572   8441  26032     21   4390     96 134572
  108540     20     68]
 [122700     20     82 148738 332056  26038     21   9770    355 148738
  122700     20     82]
 [139820     20     99 165855  15687  26035     21   9303    463 165855
  139820     20     99]
 [142300     20    101 168333 266484  26033     21   7717    446 168333
  142300     20    101]]