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@fasiha fasiha/bench.png
Last active May 30, 2017

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RAM Bench on my MacBook Pro mid-2014 (16 GB RAM) and our dual-socket 8-core Xeon E5-2630 2.40GHz (384 GB RAM). https://github.com/emilk/ram_bench
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bytes ns/elem
1024 1.26748
1216 1.28572
1456 1.32916
1728 1.22705
2048 1.2913
2432 1.23978
2896 1.24629
3440 1.28053
4096 1.28473
4864 1.17157
5792 1.16353
6896 1.14323
8192 1.14346
9744 1.14114
11584 1.17841
13776 1.22433
16384 1.18412
19488 1.22828
23168 1.29356
27552 1.2274
32768 1.30686
38960 1.79483
46336 2.12168
55104 2.34285
65536 2.79233
77936 2.90919
92688 3.14796
110224 3.15973
131072 3.32569
155872 3.26357
185360 3.41176
220432 3.37447
262144 3.32435
311744 5.47263
370720 6.61965
440864 7.96085
524288 8.97665
623488 10.116
741456 10.2945
881744 11.3945
1048576 11.8976
1246976 11.7496
1482912 12.4901
1763488 12.6482
2097152 13.2403
2493952 14.1521
2965824 14.2582
3526976 14.4454
4194304 16.5742
4987904 18.689
5931648 31.8123
7053952 42.6559
8388608 48.1828
9975792 60.7956
11863280 63.124
14107904 69.0884
16777216 68.5841
19951584 65.7826
23726560 75.3278
28215808 78.7397
33554432 77.0789
39903168 79.0283
47453136 82.5937
56431600 84.1879
67108864 84.5403
79806336 84.6674
94906272 87.6762
112863200 91.3923
134217728 87.4184
159612672 95.3246
189812528 93.8327
225726416 91.0684
268435456 97.5364
319225360 94.5311
379625056 94.662
451452832 99.4571
536870912 100.111
638450704 102.102
759250128 100.552
902905648 102.459
1073741824 108.175
1276901424 113.263
1518500256 123.657
1805811296 130.013
2147483648 136.022
2553802832 138.179
3037000496 139.398
3611622608 142.518
4294967296 145.496
5107605664 148.811
6074000992 152.272
7223245200 156.281
8589934592 155.283
10215211328 157.612
12148002000 158.171
#bytes ns/elem
1024 1.26748
1216 1.28572
1456 1.32916
1728 1.22705
2048 1.2913
2432 1.23978
2896 1.24629
3440 1.28053
4096 1.28473
4864 1.17157
5792 1.16353
6896 1.14323
8192 1.14346
9744 1.14114
11584 1.17841
13776 1.22433
16384 1.18412
19488 1.22828
23168 1.29356
27552 1.2274
32768 1.30686
38960 1.79483
46336 2.12168
55104 2.34285
65536 2.79233
77936 2.90919
92688 3.14796
110224 3.15973
131072 3.32569
155872 3.26357
185360 3.41176
220432 3.37447
262144 3.32435
311744 5.47263
370720 6.61965
440864 7.96085
524288 8.97665
623488 10.116
741456 10.2945
881744 11.3945
1048576 11.8976
1246976 11.7496
1482912 12.4901
1763488 12.6482
2097152 13.2403
2493952 14.1521
2965824 14.2582
3526976 14.4454
4194304 16.5742
4987904 18.689
5931648 31.8123
7053952 42.6559
8388608 48.1828
9975792 60.7956
11863280 63.124
14107904 69.0884
16777216 68.5841
19951584 65.7826
23726560 75.3278
28215808 78.7397
33554432 77.0789
39903168 79.0283
47453136 82.5937
56431600 84.1879
67108864 84.5403
79806336 84.6674
94906272 87.6762
112863200 91.3923
134217728 87.4184
159612672 95.3246
189812528 93.8327
225726416 91.0684
268435456 97.5364
319225360 94.5311
379625056 94.662
451452832 99.4571
536870912 100.111
638450704 102.102
759250128 100.552
902905648 102.459
1073741824 108.175
1276901424 113.263
1518500256 123.657
1805811296 130.013
2147483648 136.022
2553802832 138.179
3037000496 139.398
3611622608 142.518
4294967296 145.496
5107605664 148.811
6074000992 152.272
7223245200 156.281
8589934592 155.283
10215211328 157.612
12148002000 158.171
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import pandas as pd
mac = pd.read_table('mac-2014.txt', sep=' ')
port = pd.read_table('workstation.txt', sep=' ')
import matplotlib.pyplot as plt
plt.style.use('dark_background')
plt.rcParams['svg.fonttype'] = 'none'
plt.close('all')
fig, ax = plt.subplots()
ax.set_xscale('log', basex=2)
ax.set_yscale('log', basex=10)
plt.plot(mac['#bytes'], mac['ns/elem'],label='Mid-2014 MacBook Pro, 16 GB RAM',linewidth=4)
plt.plot(port['#bytes'], port['ns/elem'],label='Dual 8-core Xeon E5-2630, 384 GB RAM',linewidth=2)
plt.grid('on')
plt.xlabel('Length of list')
plt.ylabel('Time per element (ns/element)')
plt.title('Personal ram_bench results')
plt.legend()
plt.savefig('bench.svg')
plt.savefig('bench.png', dpi=300)
plt.show()
bytes ns/elem
1024 1.4412
1216 1.34557
1456 1.33024
1728 1.31785
2048 1.3078
2432 1.29891
2896 1.29156
3440 1.28524
4096 1.27987
4864 1.27549
5792 1.27184
6896 1.26872
8192 1.26606
9744 1.26392
11584 1.26174
13776 1.26042
16384 1.25926
19488 1.25789
23168 1.25759
27552 1.26073
32768 1.30011
38960 1.81889
46336 2.22758
55104 2.51294
65536 2.76334
77936 2.90802
92688 3.04507
110224 3.17478
131072 3.64729
155872 3.97749
185360 4.61657
220432 4.72227
262144 5.43367
311744 6.93783
370720 8.29729
440864 9.58808
524288 10.7822
623488 11.8714
741456 12.6048
881744 13.281
1048576 13.8113
1246976 14.2085
1482912 14.5811
1763488 14.8816
2097152 15.1544
2493952 15.3397
2965824 13.7785
3526976 14.2022
4194304 14.5673
4987904 13.8348
5931648 14.2508
7053952 13.8736
8388608 14.2853
9975792 14.1157
11863280 14.0545
14107904 14.087
16777216 14.2508
19951584 15.2261
23726560 28.4978
28215808 39.9887
33554432 47.2074
39903168 52.8341
47453136 57.1623
56431600 61.6569
67108864 64.4854
79806336 67.1222
94906272 69.4609
112863200 71.3731
134217728 73.1115
159612672 74.5944
189812528 75.7143
225726416 76.7172
268435456 77.4584
319225360 78.2199
379625056 78.8486
451452832 79.3778
536870912 79.7425
638450704 80.0485
759250128 80.3638
902905648 80.6359
1073741824 80.8252
1276901424 81.013
1518500256 81.187
1805811296 81.3386
2147483648 81.519
2553802832 82.2506
3037000496 82.8557
3611622608 83.3241
4294967296 83.9336
5107605664 84.5133
6074000992 85.0756
7223245200 85.5861
8589934592 86.1321
10215211328 86.6591
12148002000 87.1701
14446490416 87.6023
17179869184 93.9287
#bytes ns/elem
1024 1.4412
1216 1.34557
1456 1.33024
1728 1.31785
2048 1.3078
2432 1.29891
2896 1.29156
3440 1.28524
4096 1.27987
4864 1.27549
5792 1.27184
6896 1.26872
8192 1.26606
9744 1.26392
11584 1.26174
13776 1.26042
16384 1.25926
19488 1.25789
23168 1.25759
27552 1.26073
32768 1.30011
38960 1.81889
46336 2.22758
55104 2.51294
65536 2.76334
77936 2.90802
92688 3.04507
110224 3.17478
131072 3.64729
155872 3.97749
185360 4.61657
220432 4.72227
262144 5.43367
311744 6.93783
370720 8.29729
440864 9.58808
524288 10.7822
623488 11.8714
741456 12.6048
881744 13.281
1048576 13.8113
1246976 14.2085
1482912 14.5811
1763488 14.8816
2097152 15.1544
2493952 15.3397
2965824 13.7785
3526976 14.2022
4194304 14.5673
4987904 13.8348
5931648 14.2508
7053952 13.8736
8388608 14.2853
9975792 14.1157
11863280 14.0545
14107904 14.087
16777216 14.2508
19951584 15.2261
23726560 28.4978
28215808 39.9887
33554432 47.2074
39903168 52.8341
47453136 57.1623
56431600 61.6569
67108864 64.4854
79806336 67.1222
94906272 69.4609
112863200 71.3731
134217728 73.1115
159612672 74.5944
189812528 75.7143
225726416 76.7172
268435456 77.4584
319225360 78.2199
379625056 78.8486
451452832 79.3778
536870912 79.7425
638450704 80.0485
759250128 80.3638
902905648 80.6359
1073741824 80.8252
1276901424 81.013
1518500256 81.187
1805811296 81.3386
2147483648 81.519
2553802832 82.2506
3037000496 82.8557
3611622608 83.3241
4294967296 83.9336
5107605664 84.5133
6074000992 85.0756
7223245200 85.5861
8589934592 86.1321
10215211328 86.6591
12148002000 87.1701
14446490416 87.6023
17179869184 93.9287
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