RealSR-NCNN

RealSR-NCNN is an NCNN neural network implementation of the RealSR project and accelerated using the Vulkan API. RealSR is the Real-World Super Resolution via Kernel Estimation and Noise Injection. NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. This test profile times how long it takes to increase the resolution of a sample image by a scale of 4x with Vulkan.

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

Project Site

github.com

Test Created

24 September 2020

Test Maintainer

Michael Larabel 

Test Type

Graphics

Average Install Time

3 Seconds

Average Run Time

7 Minutes, 38 Seconds

Test Dependencies

Vulkan

Accolades

5k+ Downloads

Supported Platforms

Supported Architectures

x86_64
Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page Views ***OpenBenchmarking.orgEventsRealSR-NCNN Popularity Statisticspts/realsr-ncnn2020.092020.102020.112020.122021.012021.022021.032021.042021.052021.062021.072021.082021.092021.102021.112021.122022.012022.022022.032022.042022.052022.062022.072022.082022.092022.102022.112022.122023.012023.022023.032023.042023.052023.062023.072023.082023.0911002200330044005500
* 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 27 September 2023.
No51.4%Yes48.6%TAA Option PopularityOpenBenchmarking.org

Revision History

pts/realsr-ncnn-1.0.0   [View Source]   Thu, 24 Sep 2020 17:11:49 GMT
Initial commit of RealSR-NCNN Vulkan.

Suites Using This Test

NVIDIA GPU Compute

Vulkan Compute


Performance Metrics

Analyze Test Configuration:

RealSR-NCNN 20200818

Scale: 4x - TAA: No

OpenBenchmarking.org metrics for this test profile configuration based on 1,059 public results since 24 September 2020 with the latest data as of 22 September 2023.

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
Seconds (Average)
NVIDIA GeForce RTX 4090
100th
4
5
MSI NVIDIA GeForce RTX 4090
100th
3
5
NVIDIA GeForce RTX 4080
99th
3
5
AMD Radeon RX 6800
97th
5
6
NVIDIA GeForce RTX 3090
95th
42
6
NVIDIA GeForce RTX 3080 Ti
94th
12
6
Sapphire AMD Radeon RX 6800
93rd
3
6
NVIDIA GeForce RTX 3080
88th
46
6
AMD Radeon RX 6700
87th
3
7
NVIDIA GeForce RTX 3070 Ti
84th
11
7
NVIDIA GeForce RTX 2080 Ti
77th
31
8
NVIDIA Quadro RTX 6000
77th
9
8
NVIDIA GeForce RTX 3070
76th
21
8
Gigabyte NVIDIA GeForce RTX 3070
76th
4
8
Mid-Tier
75th
> 8
NVIDIA GeForce RTX 3060 Ti
72nd
34
9
NVIDIA GeForce RTX 2080 SUPER
66th
28
9
AMD Radeon RX 5600 OEM
64th
52
9 +/- 1
Zotac NVIDIA GeForce RTX 2080
62nd
21
10
AMD Radeon RX 56
59th
20
10
NVIDIA GeForce RTX 2070 SUPER
58th
28
10
eVGA NVIDIA GeForce RTX 3060
54th
16
11
Sapphire AMD Radeon RX 5600 OEM
53rd
23
11 +/- 1
ASUS NVIDIA GeForce RTX 2070
51st
24
12
Median
50th
12
NVIDIA GeForce RTX 2060 SUPER
49th
25
12
NVIDIA Quadro RTX 4000
45th
12
13
NVIDIA GeForce GTX 1080 Ti
44th
4
13 +/- 1
NVIDIA GeForce RTX 2060
42nd
29
14 +/- 1
NVIDIA Quadro RTX 5000 with Max-Q Design
42nd
5
14 +/- 1
NVIDIA GeForce GTX 1070
41st
7
15
NVIDIA GeForce GTX 980 Ti
39th
3
16
MSI AMD Radeon RX 470
39th
5
16 +/- 1
NVIDIA GeForce GTX 1080
38th
10
17 +/- 1
eVGA NVIDIA GeForce GTX 1660 Ti
35th
7
17
eVGA NVIDIA GeForce GTX 1660 SUPER
35th
10
17
ASUS NVIDIA GeForce GTX 1660
33rd
8
20
NVIDIA GeForce GTX 1060
32nd
11
21 +/- 1
AMD Radeon RX 580
31st
5
21 +/- 1
ASUS NVIDIA GeForce GTX 1650 SUPER
29th
6
26
Intel HD P630
29th
3
29 +/- 2
ASUS NVIDIA GeForce GTX 1650
28th
7
29
XFX AMD Radeon R9 285
28th
4
30
i915drmfb
27th
5
34 +/- 2
NVIDIA Quadro P2000
26th
8
38 +/- 1
Low-Tier
25th
> 47
eVGA NVIDIA GeForce GTX 950
25th
4
48 +/- 1
AMD Radeon RX 470
23rd
4
59 +/- 1
Intel Xe TGL GT2
21st
10
66 +/- 3
Gigabyte AMD Radeon RX 470
20th
3
67
ASUS Intel ADL-S GT1
14th
7
103 +/- 6
MSI Intel ADL-S GT1
13th
4
104 +/- 1
Sapphire AMD Radeon RX 550 640SP
12th
3
125
ASUS Intel RKL GT1
12th
3
127 +/- 8
Intel Iris Plus G7
11th
11
151 +/- 15
NVIDIA GeForce 920M
8th
6
215
Intel UHD P630
7th
3
223
ASUS Intel UHD 630
7th
15
249 +/- 19
Intel 8th Gen Core Gaussian Mixture Model
6th
3
251
MSI Intel UHD 630
5th
3
255
Gigabyte Intel UHD 630
5th
3
258
Gigabyte AMD Radeon 540
3rd
3
311 +/- 5
Intel HD 530
2nd
3
320 +/- 1
AMD Radeon RX 460
2nd
3
371
OpenBenchmarking.orgDistribution Of Public Results - Scale: 4x - TAA: No1059 Results Range From 3 To 3507 Seconds3741452162873584295005716427137848559269971068113912101281135214231494156516361707177818491920199120622133220422752346241724882559263027012772284329142985305631273198326933403411348235532004006008001000

Based on OpenBenchmarking.org data, the selected test / test configuration (RealSR-NCNN 20200818 - Scale: 4x - TAA: No) 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 BenchmarkScale: 4x - TAA: NoRun-Time510152025Min: 1 / Avg: 2.77 / Max: 21

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.5%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsScale: 4x - TAA: NoDeviation3691215Min: 0 / Avg: 0.48 / Max: 9

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 CVTSI2SD MULSD CVTTSD2SI PSHUFD MOVDQA MOVDQU PSLLDQ PSRLDQ CVTSS2SD PUNPCKLQDQ CVTDQ2PS ADDSD DIVSD CVTSD2SS MOVAPD MULPD CVTPS2PD CVTPD2PS UNPCKLPD SUBSD UCOMISD PMULUDQ PSHUFLW PSHUFHW CVTDQ2PD DIVPD ADDPD MINSD MAXSD XORPD ANDPD CMPLTSD ANDNPD SQRTSD ORPD PUNPCKHQDQ PADDQ PSUBQ
SSSE3 (SSSE3)
Used by default on supported hardware.
 
PSHUFB PABSW PSIGNW PALIGNR
Advanced Vector Extensions (AVX)
Used by default on supported hardware.
Found on Intel processors since Sandy Bridge (2011).
Found on AMD processors since Bulldozer (2011).
 
VZEROUPPER VBROADCASTSS VINSERTF128 VEXTRACTF128 VPERM2F128 VMASKMOVPS
Advanced Vector Extensions 2 (AVX2)
Used by default on supported hardware.
Found on Intel processors since Haswell (2013).
Found on AMD processors since Excavator (2016).
 
VINSERTI128 VPERMQ VEXTRACTI128 VPERM2I128 VGATHERDPS VPERMD VPBROADCASTD
FMA (FMA)
Used by default on supported hardware.
Found on Intel processors since Haswell (2013).
Found on AMD processors since Bulldozer (2011).
 
VFMADD132PS VFMADD213PS VFNMADD231PS VFMADD132SS VFMADD231SS VFMADD231PS VFMSUB132PS VFNMADD132PS
Last automated analysis: 18 January 2022

This test profile binary relies on the shared libraries libc.so.6, libvulkan.so.1, libgomp.so.1, libpthread.so.0, libm.so.6, libmvec.so.1.

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)

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