ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve.

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

Project Site

github.com

Test Created

10 November 2015

Last Updated

24 January 2021

Test Maintainer

Michael Larabel 

Test Type

Graphics

Average Install Time

6 Seconds

Average Run Time

1 Minute, 28 Seconds

Test Dependencies

C/C++ Compiler Toolchain + OpenCL + OpenMPI

Accolades

100k+ Downloads

Supported Platforms


Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page Views ***OpenBenchmarking.orgEventsASKAP tConvolveCuda Popularity Statisticspts/askap2015.112016.022016.052016.092016.122017.032017.062017.092017.122018.062018.092018.122019.042019.072019.102020.012020.042020.072020.102021.012021.042021.072021.102022.012022.042022.072022.102023.012023.042023.072023.102024.012024.042024.072024.102K4K6K8K10K
* 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 7 November 2024.
tConvolve OpenMP26.7%Hogbom Clean OpenMP11.7%tConvolve MT24.7%tConvolve MPI37.0%Test Option PopularityOpenBenchmarking.org

Revision History

pts/askap-2.1.0   [View Source]   Sun, 24 Jan 2021 16:58:25 GMT
Update against ASKAP 1.0 upstream.

pts/askap-2.0.1   [View Source]   Sat, 19 Oct 2019 20:43:41 GMT
Add --allow-run-as-root

pts/askap-2.0.0   [View Source]   Fri, 18 Oct 2019 19:38:09 GMT
Add MPI, OpenMP, OpenCL tests and other improvements.

pts/askap-1.0.0   [View Source]   Tue, 10 Nov 2015 12:58:45 GMT
Add ASKAP CUDA test.

Suites Using This Test

Multi-Core

HPC - High Performance Computing

MPI Benchmarks


Performance Metrics

Analyze Test Configuration:

ASKAP 1.0

Test: tConvolve MPI - Gridding

OpenBenchmarking.org metrics for this test profile configuration based on 1,965 public results since 24 January 2021 with the latest data as of 9 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
Mpix/sec (Average)
100th
7
144176 +/- 428
100th
17
138161 +/- 8491
100th
16
121569 +/- 11244
99th
5
115950 +/- 1951
98th
29
92324 +/- 6926
97th
13
74287 +/- 277
96th
13
73034 +/- 1451
96th
20
72953 +/- 1649
94th
21
71122 +/- 3309
93rd
46
69591 +/- 1684
91st
9
66687 +/- 3873
91st
4
65436 +/- 2062
91st
20
60280 +/- 6871
89th
12
50716 +/- 575
88th
21
48337 +/- 1953
86th
48
47055 +/- 1063
85th
31
46329 +/- 1321
83rd
5
44946 +/- 440
83rd
6
44274 +/- 579
81st
23
42749 +/- 845
80th
19
42635 +/- 1022
80th
6
41559 +/- 3834
79th
9
40980 +/- 5704
78th
7
38024 +/- 780
78th
13
37667 +/- 552
77th
13
37339 +/- 108
76th
7
36817 +/- 510
Mid-Tier
75th
< 36627
75th
15
36529 +/- 5005
75th
27
35922 +/- 778
74th
3
32475 +/- 300
73rd
4
31308 +/- 1464
73rd
8
30264 +/- 306
72nd
13
29884 +/- 3392
72nd
12
29602 +/- 798
71st
6
28310 +/- 209
71st
8
28265 +/- 214
71st
3
27258 +/- 503
71st
3
27153 +/- 547
70th
10
25629 +/- 618
69th
8
24289 +/- 362
68th
29
23816 +/- 508
68th
4
23778 +/- 98
67th
19
23386 +/- 595
67th
4
23204 +/- 53
67th
5
23068 +/- 62
66th
4
22729 +/- 53
66th
5
22613 +/- 266
64th
17
21888 +/- 518
64th
5
21826 +/- 55
64th
22
21807 +/- 434
64th
15
21742 +/- 693
63rd
5
21466 +/- 211
63rd
5
21034 +/- 94
62nd
5
20639 +/- 120
61st
4
20520 +/- 251
61st
8
20316 +/- 130
60th
10
19749 +/- 119
59th
29
19677 +/- 1755
59th
3
19662 +/- 528
59th
9
18407 +/- 56
57th
5
17342 +/- 93
57th
5
17286 +/- 518
56th
8
16663 +/- 64
56th
3
16578 +/- 241
56th
8
16520 +/- 350
55th
11
16414 +/- 104
54th
3
16152 +/- 290
54th
9
15060 +/- 336
53rd
8
14956 +/- 477
53rd
4
14519 +/- 181
52nd
3
13976 +/- 141
52nd
5
13940 +/- 106
52nd
3
13736 +/- 278
51st
9
13434 +/- 454
51st
8
13341 +/- 773
51st
7
13239 +/- 430
Median
50th
13120
50th
5
12747 +/- 108
50th
4
12715 +/- 32
48th
4
12383 +/- 196
48th
10
12372 +/- 435
48th
20
12274 +/- 257
48th
5
12212 +/- 16
48th
3
12207 +/- 321
47th
18
12083 +/- 732
46th
18
11550 +/- 319
46th
18
11455 +/- 622
44th
17
11059 +/- 493
43rd
18
10623 +/- 160
42nd
20
10295 +/- 280
41st
7
9884 +/- 474
41st
8
9115 +/- 370
40th
4
8605 +/- 121
38th
3
8269 +/- 103
38th
10
8231 +/- 159
38th
11
8193 +/- 367
38th
20
8179 +/- 573
37th
20
8141 +/- 178
37th
7
8004 +/- 390
36th
8
7539 +/- 226
35th
5
7445 +/- 71
34th
10
7422 +/- 244
34th
5
7373 +/- 33
33rd
5
7206 +/- 62
33rd
5
7148 +/- 38
32nd
25
6791 +/- 287
31st
6
6404 +/- 13
31st
15
6388 +/- 389
30th
5
6296 +/- 37
30th
9
6248 +/- 196
30th
3
6244 +/- 43
30th
5
6206 +/- 15
29th
5
6140 +/- 120
29th
7
6086 +/- 145
27th
3
5694 +/- 106
26th
21
4455 +/- 113
Low-Tier
25th
< 4450
25th
3
4410 +/- 118
25th
4
4352 +/- 119
24th
3
4218 +/- 19
23rd
10
4193 +/- 341
23rd
4
4186 +/- 140
22nd
5
3882 +/- 7
22nd
5
3829 +/- 421
22nd
4
3757 +/- 333
22nd
3
3592 +/- 9
21st
3
3383 +/- 146
21st
7
3327 +/- 12
20th
13
3306 +/- 93
20th
4
3220 +/- 13
18th
4
3057 +/- 23
18th
3
3055 +/- 125
17th
5
2834 +/- 25
17th
7
2832 +/- 56
17th
3
2772 +/- 34
17th
3
2589 +/- 64
17th
6
2390 +/- 42
16th
3
2364 +/- 18
16th
3
2345 +/- 54
16th
3
2173 +/- 21
16th
3
2157 +/- 21
15th
3
2106 +/- 4
15th
3
2095 +/- 20
15th
3
2012 +/- 52
14th
3
1973 +/- 40
14th
3
1957 +/- 72
14th
3
1924 +/- 5
14th
4
1917 +/- 39
13th
10
1909 +/- 42
13th
3
1882 +/- 3
13th
8
1878 +/- 61
13th
5
1823 +/- 6
12th
6
1803 +/- 67
12th
5
1736 +/- 39
11th
3
1618 +/- 10
11th
4
1611 +/- 62
11th
3
1605 +/- 3
10th
6
1541 +/- 14
10th
3
1509 +/- 25
10th
8
1502 +/- 61
10th
5
1498 +/- 47
9th
3
1456 +/- 14
9th
10
1436 +/- 4
8th
3
1410 +/- 19
8th
3
1383 +/- 3
8th
8
1274 +/- 156
8th
4
1274 +/- 38
8th
5
1226 +/- 4
7th
4
1213 +/- 2
7th
3
1197 +/- 80
7th
3
1194 +/- 6
7th
4
1159 +/- 32
7th
4
1156 +/- 9
6th
3
1130 +/- 5
6th
6
1115 +/- 90
6th
3
1091 +/- 4
6th
3
1087 +/- 14
5th
5
1043 +/- 18
5th
3
1042 +/- 29
5th
3
1010 +/- 13
4th
4
997 +/- 12
4th
4
978 +/- 38
4th
3
952 +/- 4
4th
3
930 +/- 8
4th
6
880 +/- 7
3rd
3
873 +/- 3
3rd
3
861 +/- 18
3rd
3
848 +/- 27
3rd
3
832 +/- 52
3rd
3
825 +/- 6
3rd
3
672 +/- 4
3rd
3
668 +/- 3
2nd
3
636 +/- 4
2nd
3
325 +/- 1
OpenBenchmarking.orgDistribution Of Public Results - Test: tConvolve MPI - Gridding1962 Results Range From 66 To 147615 Mpix/sec6630175968891911870148211777220723236742662529576325273547838429413804433147282502335318456135590866203764988679397089073841767927974382694856458859691547944989744910040010335110630210925311220411515511810612105712400812695912991013286113581213876314171414466514761670140210280350

Based on OpenBenchmarking.org data, the selected test / test configuration (ASKAP 1.0 - Test: tConvolve MPI - Gridding) has an average run-time of 3 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 BenchmarkTest: tConvolve MPI - GriddingRun-Time48121620Min: 1 / Avg: 2.72 / Max: 16

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.9%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsTest: tConvolve MPI - GriddingDeviation3691215Min: 0 / Avg: 0.87 / Max: 7

Does It Scale Well With Increasing Cores?

Yes, based on the automated analysis of the collected public benchmark data, this test / test settings does 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 BaseASKAP tConvolveCuda CPU Core ScalingTest: tConvolve MPI - Gridding46810121416243248649612819220406080100

Notable Instruction Set Usage

Notable instruction set extensions supported by this test, based on an automatic analysis by the Phoronix Test Suite / OpenBenchmarking.org analytics engine.

Instruction Set
Support
Instructions Detected
SSE2 (SSE2)
Used by default on supported hardware.
 
MOVD MULSD DIVSD CVTTSD2SI ADDSD CVTSI2SD MOVAPD UCOMISD CVTSD2SS XORPD COMISD SUBSD CVTSS2SD ANDPD
Last automated analysis: 17 January 2022

This test profile binary relies on the shared libraries libOpenCL.so.1, libm.so.6, libc.so.6.

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)
Loongson LoongArch 64-bit
loongarch64
Loongson-3A5000LL
ARMv8 64-bit
aarch64
ARMv8 Cortex-A55 4-Core, ARMv8 Cortex-A57 4-Core, ARMv8 Neoverse-N1, ARMv8 Neoverse-N1 128-Core, ARMv8 Neoverse-N1 80-Core, ARMv8 Neoverse-V1, ARMv8 Neoverse-V2, ARMv8 Neoverse-V2 144-Core, ARMv8 Neoverse-V2 72-Core, ARMv8 rev 0 8-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 128-Core, AmpereOne 160-Core, AmpereOne 192-Core, AmpereOne 32-Core, AmpereOne 64-Core, AmpereOne 72-Core, AmpereOne 96-Core, Apple M1, Rockchip ARMv8 Cortex-A76 8-Core

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