SME日記その19 SMEでベクトルのスカラー倍を記述してみるのプログラムについて，研究論文にしようと目論んで，フェアで厳正な比較になるようにベンチマークプログラムをCで書き直してみたのですが，残念ながらポジティブな結果は出なかったので，Qiita記事として公開して供養します．

SMEシリーズ

プログラム

実行結果

apple_blas: vec_size: 1000
sscal1
time: 5000005000 (nano sec)
count: 708787
IPS: 0.014176 (giga)
average: 70.543125 (nano sec)
apple_blas: vec_size: 10000
sscal1
time: 5000003000 (nano sec)
count: 233300
IPS: 0.004666 (giga)
average: 214.316459 (nano sec)
apple_blas: vec_size: 100000
sscal1
time: 5000182000 (nano sec)
count: 10790
IPS: 0.000216 (giga)
average: 4634.088971 (nano sec)
apple_blas: vec_size: 1000000
sscal1
time: 5004379000 (nano sec)
count: 893
IPS: 0.000018 (giga)
average: 56040.078387 (nano sec)
apple_blas: vec_size: 10000000
sscal1
time: 5016981000 (nano sec)
count: 88
IPS: 0.000002 (giga)
average: 570111.477273 (nano sec)
----
apple_blas: vec_size: 1000
sscal_scopy
time: 5000000000 (nano sec)
count: 379614
IPS: 0.007592 (giga)
average: 131.712740 (nano sec)
apple_blas: vec_size: 10000
sscal_scopy
time: 5000031000 (nano sec)
count: 126990
IPS: 0.002540 (giga)
average: 393.734231 (nano sec)
apple_blas: vec_size: 100000
sscal_scopy
time: 5000264000 (nano sec)
count: 5492
IPS: 0.000110 (giga)
average: 9104.632192 (nano sec)
apple_blas: vec_size: 1000000
sscal_scopy
time: 5002104000 (nano sec)
count: 505
IPS: 0.000010 (giga)
average: 99051.564356 (nano sec)
apple_blas: vec_size: 10000000
sscal_scopy
time: 5118143000 (nano sec)
count: 41
IPS: 0.000001 (giga)
average: 1248327.560976 (nano sec)
====
open_blas: vec_size: 1000
sscal1
time: 5000003000 (nano sec)
count: 752298
IPS: 0.015046 (giga)
average: 66.463064 (nano sec)
open_blas: vec_size: 10000
sscal1
time: 5000009000 (nano sec)
count: 85504
IPS: 0.001710 (giga)
average: 584.769017 (nano sec)
open_blas: vec_size: 100000
sscal1
time: 5000365000 (nano sec)
count: 7809
IPS: 0.000156 (giga)
average: 6403.335894 (nano sec)
open_blas: vec_size: 1000000
sscal1
time: 5001879000 (nano sec)
count: 732
IPS: 0.000015 (giga)
average: 68331.680328 (nano sec)
open_blas: vec_size: 10000000
sscal1
time: 5012390000 (nano sec)
count: 128
IPS: 0.000003 (giga)
average: 391592.968750 (nano sec)
----
open_blas: vec_size: 1000
sscal_scopy
time: 5000010000 (nano sec)
count: 425703
IPS: 0.008514 (giga)
average: 117.453013 (nano sec)
open_blas: vec_size: 10000
sscal_scopy
time: 5000113000 (nano sec)
count: 42188
IPS: 0.000844 (giga)
average: 1185.197924 (nano sec)
open_blas: vec_size: 100000
sscal_scopy
time: 5006672000 (nano sec)
count: 636
IPS: 0.000013 (giga)
average: 78721.257862 (nano sec)
open_blas: vec_size: 1000000
sscal_scopy
time: 5005451000 (nano sec)
count: 319
IPS: 0.000006 (giga)
average: 156910.689655 (nano sec)
open_blas: vec_size: 10000000
sscal_scopy
time: 5019305000 (nano sec)
count: 66
IPS: 0.000001 (giga)
average: 760500.757576 (nano sec)
====
sme: vec_size: 1000
sscal1
time: 5000007000 (nano sec)
count: 617882
IPS: 0.012358 (giga)
average: 80.921713 (nano sec)
sme: vec_size: 10000
sscal1
time: 5000011000 (nano sec)
count: 74765
IPS: 0.001495 (giga)
average: 668.763593 (nano sec)
sme: vec_size: 100000
sscal1
time: 5000040000 (nano sec)
count: 6579
IPS: 0.000132 (giga)
average: 7600.000000 (nano sec)
sme: vec_size: 1000000
sscal1
time: 5004946000 (nano sec)
count: 587
IPS: 0.000012 (giga)
average: 85263.134583 (nano sec)
sme: vec_size: 10000000
sscal1
time: 5063235000 (nano sec)
count: 59
IPS: 0.000001 (giga)
average: 858175.423729 (nano sec)
----
sme: vec_size: 1000
sscal_scopy
time: 5000001000 (nano sec)
count: 619006
IPS: 0.012380 (giga)
average: 80.774677 (nano sec)
sme: vec_size: 10000
sscal_scopy
time: 5000026000 (nano sec)
count: 74957
IPS: 0.001499 (giga)
average: 667.052577 (nano sec)
sme: vec_size: 100000
sscal_scopy
time: 5000862000 (nano sec)
count: 5302
IPS: 0.000106 (giga)
average: 9432.029423 (nano sec)
sme: vec_size: 1000000
sscal_scopy
time: 5008793000 (nano sec)
count: 545
IPS: 0.000011 (giga)
average: 91904.458716 (nano sec)
sme: vec_size: 10000000
sscal_scopy
time: 5076061000 (nano sec)
count: 54
IPS: 0.000001 (giga)
average: 940011.296296 (nano sec)
====
clang_for: vec_size: 1000
sscal1
time: 5000001000 (nano sec)
count: 866779
IPS: 0.017336 (giga)
average: 57.684842 (nano sec)
clang_for: vec_size: 10000
sscal1
time: 5000052000 (nano sec)
count: 91395
IPS: 0.001828 (giga)
average: 547.081569 (nano sec)
clang_for: vec_size: 100000
sscal1
time: 5000223000 (nano sec)
count: 8554
IPS: 0.000171 (giga)
average: 5845.479308 (nano sec)
clang_for: vec_size: 1000000
sscal1
time: 5000314000 (nano sec)
count: 760
IPS: 0.000015 (giga)
average: 65793.605263 (nano sec)
clang_for: vec_size: 10000000
sscal1
time: 5022664000 (nano sec)
count: 76
IPS: 0.000002 (giga)
average: 660876.842105 (nano sec)
----
clang_for: vec_size: 1000
sscal_scopy
time: 5000012000 (nano sec)
count: 391175
IPS: 0.007823 (giga)
average: 127.820336 (nano sec)
clang_for: vec_size: 10000
sscal_scopy
time: 5000018000 (nano sec)
count: 73085
IPS: 0.001462 (giga)
average: 684.137374 (nano sec)
clang_for: vec_size: 100000
sscal_scopy
time: 5000162000 (nano sec)
count: 6969
IPS: 0.000139 (giga)
average: 7174.862965 (nano sec)
clang_for: vec_size: 1000000
sscal_scopy
time: 5004389000 (nano sec)
count: 709
IPS: 0.000014 (giga)
average: 70583.765867 (nano sec)
clang_for: vec_size: 10000000
sscal_scopy
time: 5001674000 (nano sec)
count: 70
IPS: 0.000001 (giga)
average: 714524.857143 (nano sec)

単位ナノ秒

size	Apple BLAS SSCAL	Apple BLAS SCOPY+SSCAL	Open BLAS SSCAL	OpenBLAS SCOPY+SSCAL	SME SSCAL	SME fused SCOPY+SSCAL	Clang simple for loop -O3 SSCAL	Clang simple for loop -O3 fused SCOPY+SSCAL
1000	71	132	66	117	81	81	58	128
10000	214	394	585	1185	669	667	547	684
100000	4634	9105	6403	78721	7600	9432	5845	7175
1000000	56040	99052	68332	156911	85263	91904	65794	70584
10000000	570111	1248328	391593	760501	858175	940011	660877	714525

Scalable Matrix Extensionを使ったプログラムはほぼ惨敗です．単純なforループ(Clang simple for loop -O3)が思ったより速いですね．OpenBLAS SCOPY+SSCALの挙動が若干不可解で，大きい配列の時にOpenBLAS SSCALよりも速くなります．