Numpy Benchmark

This is a test to obtain the general Numpy performance.

To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark numpy.

Project Site

github.com

Test Created

2 March 2016

Last Updated

13 November 2020

Test Maintainer

Victor Rodriguez Bahena 

Test Type

Processor

Test Dependencies

Python

Accolades

100k+ Downloads

Supported Platforms


Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page Views ***OpenBenchmarking.orgEventsNumpy Benchmark Popularity Statisticspts/numpy2016.032016.062016.092016.122017.032017.062017.092017.122018.032018.062018.092018.122019.032019.062019.092019.122020.032020.062020.092020.122021.032021.062021.092021.122022.032022.062022.092022.122023.032023.062023.092023.122024.032024.062024.097K14K21K28K35K
* Uploading of benchmark result data to OpenBenchmarking.org is always optional (opt-in) via the Phoronix Test Suite for users wishing to share their results publicly.
** Data based on those opting to upload their test results to OpenBenchmarking.org and users enabling the opt-in anonymous statistics reporting while running benchmarks from an Internet-connected platform.
*** Test profile page view reporting began March 2021.
Data updated weekly as of 20 November 2024.

Revision History

pts/numpy-1.2.1   [View Source]   Fri, 13 Nov 2020 13:19:11 GMT
Enable Numpy for macOS.

pts/numpy-1.2.0   [View Source]   Tue, 14 Jan 2020 10:25:37 GMT
Use geometric mean for result per https://github.com/phoronix-test-suite/test-profiles/pull/125

pts/numpy-1.1.0   [View Source]   Fri, 10 Jan 2020 10:40:45 GMT
Updates per https://github.com/phoronix-test-suite/test-profiles/pull/116

pts/numpy-1.0.5   [View Source]   Sun, 08 Apr 2018 13:12:34 GMT
Actually numpy should be working fine now on BSD

pts/numpy-1.0.4   [View Source]   Sat, 07 Apr 2018 21:24:32 GMT
Numpy has issues on BSD.

pts/numpy-1.0.3   [View Source]   Sun, 18 Feb 2018 15:42:43 GMT
Explicitly use python2 for numpy, not python3 when python points there.

pts/numpy-1.0.2   [View Source]   Fri, 13 May 2016 13:34:32 GMT
Set TimesToRun to 1

pts/numpy-1.0.1   [View Source]   Fri, 04 Mar 2016 16:38:36 GMT
Fix results.xml

pts/numpy-1.0.0   [View Source]   Wed, 02 Mar 2016 11:33:31 GMT
Initial commit

Suites Using This Test

Machine Learning

HPC - High Performance Computing

CPU Massive

Server CPU Tests

Python

Single-Threaded


Performance Metrics

Analyze Test Configuration:

Numpy Benchmark

OpenBenchmarking.org metrics for this test profile configuration based on 3,380 public results since 14 January 2020 with the latest data as of 10 November 2024.

Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. It is important to keep in mind particularly in the Linux/open-source space there can be vastly different OS configurations, with this overview intended to offer just general guidance as to the performance expectations.

Component
Percentile Rank
# Compatible Public Results
Score (Average)
100th
8
1056 +/- 6
100th
32
1044 +/- 86
100th
10
1043 +/- 4
100th
7
1042 +/- 12
98th
22
889 +/- 62
97th
7
867 +/- 3
97th
18
858 +/- 61
95th
13
825 +/- 41
95th
12
817 +/- 42
95th
4
810 +/- 2
92nd
15
766 +/- 20
92nd
18
759 +/- 65
90th
8
736 +/- 20
89th
4
710 +/- 1
89th
7
707 +/- 20
89th
10
703 +/- 17
88th
13
691 +/- 40
88th
6
687 +/- 32
88th
5
682 +/- 14
87th
5
669 +/- 31
87th
3
668 +/- 28
87th
9
667 +/- 32
87th
8
666 +/- 20
87th
5
664 +/- 58
86th
30
647 +/- 39
86th
3
645 +/- 52
85th
8
629 +/- 21
83rd
14
608 +/- 11
80th
8
580 +/- 9
80th
5
578 +/- 17
80th
10
575 +/- 23
80th
14
575 +/- 40
79th
10
573 +/- 23
79th
8
573 +/- 65
78th
5
565 +/- 22
78th
8
562 +/- 16
78th
57
558 +/- 37
76th
3
544 +/- 8
76th
8
543 +/- 51
76th
17
542 +/- 36
Mid-Tier
75th
< 539
75th
3
538 +/- 2
74th
3
530 +/- 8
74th
23
529 +/- 70
73rd
38
526 +/- 27
73rd
10
524 +/- 1
73rd
3
523 +/- 25
72nd
6
520 +/- 1
71st
5
517 +/- 1
71st
3
517 +/- 8
69th
3
505 +/- 66
68th
19
501 +/- 17
67th
3
495 +/- 56
67th
3
494 +/- 26
67th
4
491 +/- 58
66th
8
483 +/- 11
65th
3
479 +/- 8
65th
7
472 +/- 14
64th
7
469 +/- 42
64th
14
467 +/- 41
64th
6
465 +/- 40
64th
7
462 +/- 38
63rd
10
461 +/- 39
63rd
6
459 +/- 22
63rd
4
459 +/- 3
63rd
4
458 +/- 8
63rd
11
457 +/- 27
61st
4
447 +/- 28
61st
10
447 +/- 10
61st
12
445 +/- 30
60th
15
444 +/- 23
60th
10
443 +/- 5
60th
20
443 +/- 34
60th
14
441 +/- 41
59th
6
437 +/- 39
59th
4
437 +/- 27
58th
3
434 +/- 34
57th
3
428 +/- 4
56th
5
423 +/- 19
55th
3
419 +/- 1
55th
3
419 +/- 39
54th
23
417 +/- 59
54th
14
415 +/- 25
53rd
13
414 +/- 19
53rd
16
410 +/- 10
Median
50th
402
50th
4
401 +/- 12
49th
23
396 +/- 58
47th
12
389 +/- 15
46th
7
382 +/- 21
45th
5
376 +/- 19
45th
12
375 +/- 17
45th
4
375 +/- 6
44th
13
371 +/- 28
43rd
7
365 +/- 4
42nd
17
363 +/- 14
42nd
4
362 +/- 3
42nd
8
360 +/- 17
40th
21
351 +/- 12
40th
4
351 +/- 9
39th
18
346 +/- 13
39th
3
344 +/- 10
39th
4
343 +/- 9
37th
5
333 +/- 18
37th
5
332 +/- 14
36th
3
329 +/- 2
35th
18
325 +/- 20
35th
10
323 +/- 10
34th
4
322 +/- 14
34th
3
320 +/- 5
33rd
6
319 +/- 5
33rd
3
319 +/- 1
33rd
9
319 +/- 4
32nd
4
316 +/- 19
31st
5
314 +/- 17
31st
7
314 +/- 7
31st
6
314 +/- 2
31st
10
313 +/- 8
30th
5
310 +/- 12
29th
8
309 +/- 4
29th
16
309 +/- 5
29th
3
307 +/- 30
28th
14
305 +/- 9
28th
15
305 +/- 6
28th
10
304 +/- 5
28th
14
304 +/- 12
28th
7
304 +/- 4
27th
5
303 +/- 14
26th
8
301 +/- 6
26th
10
300 +/- 4
26th
6
300 +/- 2
Low-Tier
25th
< 300
25th
10
299 +/- 5
25th
7
299 +/- 6
25th
10
298 +/- 21
25th
10
298 +/- 6
25th
16
297 +/- 18
24th
11
296 +/- 6
23rd
9
294 +/- 19
23rd
8
294 +/- 6
23rd
7
292 +/- 7
23rd
6
291 +/- 13
22nd
5
289 +/- 1
21st
4
286 +/- 9
21st
3
286 +/- 10
21st
4
284 +/- 4
20th
11
282 +/- 13
18th
7
273 +/- 37
18th
5
272 +/- 6
18th
5
271 +/- 7
18th
15
270 +/- 7
17th
11
268 +/- 6
17th
5
268 +/- 2
17th
5
268 +/- 21
17th
3
266 +/- 1
17th
6
264 +/- 12
16th
5
261 +/- 20
15th
3
253 +/- 15
15th
5
251 +/- 12
15th
4
251 +/- 3
14th
3
242 +/- 3
12th
4
222 +/- 6
12th
12
219 +/- 5
11th
3
214 +/- 22
11th
3
213 +/- 22
11th
3
207 +/- 11
11th
5
207 +/- 2
11th
3
206 +/- 1
10th
4
198 +/- 3
10th
4
193 +/- 11
9th
6
173 +/- 3
9th
5
172 +/- 13
7th
9
131 +/- 5
3rd
4
34 +/- 1
OpenBenchmarking.orgDistribution Of Public Results3380 Results Range From 3 To 1183 Score3377110513917320724127530934337741144547951354758161564968371775178581985388792195598910231057109111251159119370140210280350

Based on OpenBenchmarking.org data, the selected test / test configuration (Numpy Benchmark) has an average run-time of 14 minutes. By default this test profile is set to run at least 3 times but may increase if the standard deviation exceeds pre-defined defaults or other calculations deem additional runs necessary for greater statistical accuracy of the result.

OpenBenchmarking.orgMinutesTime Required To Complete BenchmarkRun-Time20406080100Min: 4 / Avg: 13.38 / Max: 129

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.2%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsDeviation246810Min: 0 / Avg: 0.17 / Max: 2

Does It Scale Well With Increasing Cores?

No, based on the automated analysis of the collected public benchmark data, this test / test settings does not generally scale well with increasing CPU core counts. Data based on publicly available results for this test / test settings, separated by vendor, result divided by the reference CPU clock speed, grouped by matching physical CPU core count, and normalized against the smallest core count tested from each vendor for each CPU having a sufficient number of test samples and statistically significant data.

AMDIntelOpenBenchmarking.orgRelative Core Scaling To BaseNumpy Benchmark CPU Core Scaling246810121416182024324864961281921.83.65.47.29

Tested CPU Architectures

This benchmark has been successfully tested on the below mentioned architectures. The CPU architectures listed is where successful OpenBenchmarking.org result uploads occurred, namely for helping to determine if a given test is compatible with various alternative CPU architectures.

CPU Architecture
Kernel Identifier
Verified On
Intel / AMD x86 64-bit
x86_64
(Many Processors)
RISC-V 64-bit
riscv64
SiFive RISC-V, rv64imafdcv
IBM POWER (PowerPC) 64-bit
ppc64le
POWER9 44-Core, POWER9 8-Core
Loongson LoongArch 64-bit
loongarch64
Loongson-3A5000LL, Loongson-3A6000, Loongson-3C5000
Intel / AMD x86 32-bit
i686
(Many Processors)
ARMv7 32-bit
armv7l
ARMv7 4-Core, ARMv7 Cortex-A53 4-Core, ARMv7 Cortex-A72 4-Core
ARMv6 32-bit
armv6l
ARMv7
ARMv8 64-bit
arm64
Apple M1, Apple M1 Max, Apple M1 Pro, Apple M2, Apple M2 Max, Apple M2 Pro, Apple M3 Max, Apple M3 Pro
ARMv8 64-bit
aarch64
ARMv8, ARMv8 Cortex-A53 4-Core, ARMv8 Cortex-A55 4-Core, ARMv8 Cortex-A72 16-Core, ARMv8 Cortex-A72 4-Core, ARMv8 Cortex-A73 6-Core, ARMv8 Cortex-A76 4-Core, ARMv8 Cortex-A77 6-Core, ARMv8 Cortex-A78E, ARMv8 Cortex-A78E 12-Core, ARMv8 Cortex-A78E 6-Core, ARMv8 Cortex-A78E 8-Core, ARMv8 Neoverse-N1, ARMv8 Neoverse-N1 128-Core, ARMv8 Neoverse-N1 4-Core, ARMv8 Neoverse-N1 64-Core, ARMv8 Neoverse-V1, ARMv8 Neoverse-V1 4-Core, ARMv8 Neoverse-V1 64-Core, ARMv8 Neoverse-V2, ARMv8 Neoverse-V2 72-Core, ARMv8 Neoverse-V2 96-Core, ARMv8 rev 0 6-Core, Ampere ARMv8 Neoverse-N1 128-Core, Ampere ARMv8 Neoverse-N1 256-Core, Ampere Altra ARMv8 Neoverse-N1 160-Core, Ampere eMAG ARMv8 32-Core, AmpereOne, AmpereOne 192-Core, AmpereOne 72-Core, Apple, Apple M1, Apple M2, Rockchip ARMv8 Cortex-A76 4-Core, Rockchip ARMv8 Cortex-A76 6-Core, Rockchip RK3588

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4 Systems - 856 Benchmark Results

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