new tests eo nov

Intel Core i9-14900K testing with a ASUS PRIME Z790-P WIFI (1402 BIOS) and AMD Radeon 15GB on Ubuntu 23.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2311285-PTS-NEWTESTS44
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results
Show Result Confidence Charts

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
a
November 28 2023
  1 Hour, 10 Minutes
b
November 28 2023
  1 Hour, 9 Minutes
c
November 28 2023
  1 Hour, 9 Minutes
d
November 28 2023
  1 Hour, 10 Minutes
e
November 28 2023
  1 Hour, 9 Minutes
Invert Hiding All Results Option
  1 Hour, 9 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


new tests eo novOpenBenchmarking.orgPhoronix Test SuiteIntel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads)ASUS PRIME Z790-P WIFI (1402 BIOS)Intel Device 7a2732GBWestern Digital WD_BLACK SN850X 1000GBAMD Radeon 15GB (1617/1124MHz)Realtek ALC897ASUS VP28UUbuntu 23.106.5.0-10-generic (x86_64)GNOME Shell 45.0X Server 1.21.1.7 + Wayland4.6 Mesa 24.0~git2311100600.05fb6b~oibaf~m (git-05fb6b9 2023-11-10 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.54)GCC 13.2.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionNew Tests Eo Nov BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: intel_pstate powersave (EPP: performance) - CPU Microcode: 0x11d - Thermald 2.5.4- OpenJDK Runtime Environment (build 11.0.20+8-post-Ubuntu-1ubuntu1)- Python 3.11.6- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

abcdeResult OverviewPhoronix Test Suite100%107%115%122%129%WebP2 Image EncodePyTorchOpenSSLJava SciMarkEmbree

new tests eo novwebp2: Quality 100, Lossless Compressionpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lopenssl: SHA512openssl: SHA256webp2: Quality 95, Compression Effort 7pytorch: CPU - 16 - ResNet-152pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lopenssl: RSA4096openssl: RSA4096webp2: Quality 75, Compression Effort 7pytorch: CPU - 1 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 16 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 512 - ResNet-50pytorch: CPU - 32 - ResNet-50embree: Pathtracer - Asian Dragon Objembree: Pathtracer ISPC - Asian Dragon Objjava-scimark2: Compositeembree: Pathtracer - Crownembree: Pathtracer ISPC - Crownembree: Pathtracer - Asian Dragonembree: Pathtracer ISPC - Asian Dragonpytorch: CPU - 1 - ResNet-50webp2: Quality 100, Compression Effort 5webp2: Defaultjava-scimark2: Jacobi Successive Over-Relaxationjava-scimark2: Dense LU Matrix Factorizationjava-scimark2: Sparse Matrix Multiplyjava-scimark2: Fast Fourier Transformjava-scimark2: Monte Carloabcde0.048.858.798.948.9010.0910849481210354749530100.1617.1714.8918.0817.1318.0413.50347145.553600.3528.7139.0546.3246.8246.8846.4831.151631.8584716.0130.071330.478334.44636.212458.848.8315.782940.8713059.894792.041219.731567.510.0410.5111.6511.9811.678.8211062578760359986660200.1617.6318.4217.7118.1517.1213.42355954.354760.3328.9739.3444.4738.9346.7646.7331.122431.74734785.1730.059830.247134.442436.408660.118.9615.892947.9413387.724790.641232.021567.510.0411.608.888.9510.508.8910975727400357623368800.1617.9914.6518.0417.9716.9013.43359762.4553622.3547.0046.4746.9546.3246.7631.088931.7234773.5830.30730.201334.479436.247974.549.9315.402947.9413341.674789.241232.911556.150.048.928.8011.598.9611.7210815857230356253913400.1615.1418.0814.8818.0818.1413.48351474.25410.10.3422.7347.8344.1444.5246.4046.3031.266331.65494772.929.992330.191334.377636.421775.677.6516.242947.9413337.54780.861230.691567.510.048.8711.868.7811.6912.0911006330870355671215400.1618.1718.0918.3018.0718.2413.48352828.95429.50.3422.4539.2938.6846.6746.5846.4931.129431.88134779.5230.096430.273134.503236.222774.039.9815.652949.3613354.24794.851231.131568.08OpenBenchmarking.org

WebP2 Image Encode

This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Lossless Compressionedcba0.0090.0180.0270.0360.0450.040.040.040.040.041. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_ledcba36912158.878.9211.6010.518.85MIN: 4.6 / MAX: 9.03MIN: 4.97 / MAX: 9.08MIN: 5.57 / MAX: 12.14MIN: 4.81 / MAX: 11.29MIN: 4.16 / MAX: 9.06

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_ledcba369121511.868.808.8811.658.79MIN: 5.09 / MAX: 12.28MIN: 5.17 / MAX: 8.94MIN: 4.94 / MAX: 9.08MIN: 5.27 / MAX: 12.15MIN: 4.35 / MAX: 9.75

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_ledcba36912158.7811.598.9511.988.94MIN: 4.28 / MAX: 9.7MIN: 5.55 / MAX: 12.11MIN: 4.32 / MAX: 9MIN: 5.05 / MAX: 12.49MIN: 5 / MAX: 9.09

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_ledcba369121511.698.9610.5011.678.90MIN: 5.58 / MAX: 12.18MIN: 4.16 / MAX: 9.35MIN: 4.78 / MAX: 10.98MIN: 5.41 / MAX: 12.17MIN: 4.78 / MAX: 9.1

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_ledcba369121512.0911.728.898.8210.09MIN: 5.97 / MAX: 12.57MIN: 5.22 / MAX: 12.2MIN: 3.85 / MAX: 9.08MIN: 5.03 / MAX: 9.05MIN: 4.54 / MAX: 12.07

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. The system/openssl test profiles relies on benchmarking the system/OS-supplied openssl binary rather than the pts/openssl test profile that uses the locally-built OpenSSL for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA512edcba2000M4000M6000M8000M10000M11006330870108158572301097572740011062578760108494812101. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

Algorithm: ChaCha20-Poly1305

a: The test run did not produce a result.

b: The test run did not produce a result.

c: The test run did not produce a result.

d: The test run did not produce a result.

e: The test run did not produce a result.

Algorithm: AES-256-GCM

a: The test run did not produce a result. E: 40D7CDBA3B7F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

b: The test run did not produce a result. E: 40B758D5667F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

c: The test run did not produce a result. E: 40276B14D57F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

d: The test run did not produce a result. E: 4007EF5BFD7E0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

e: The test run did not produce a result. E: 40A724E3367F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

Algorithm: AES-128-GCM

a: The test run did not produce a result. E: 40E7AC794F7F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

b: The test run did not produce a result. E: 4007130B2F7F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

c: The test run did not produce a result. E: 4057ED839F7F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

d: The test run did not produce a result. E: 40A7798AFB7F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

e: The test run did not produce a result. E: 40B7D5B7A47F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

Algorithm: ChaCha20

a: The test run did not produce a result.

b: The test run did not produce a result.

c: The test run did not produce a result.

d: The test run did not produce a result.

e: The test run did not produce a result.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA256edcba8000M16000M24000M32000M40000M35567121540356253913403576233688035998666020354749530101. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

WebP2 Image Encode

This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 95, Compression Effort 7edcba0.0360.0720.1080.1440.180.160.160.160.160.161. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152edcba4812162018.1715.1417.9917.6317.17MIN: 9.41 / MAX: 18.96MIN: 5.99 / MAX: 17.74MIN: 7.44 / MAX: 18.86MIN: 8.26 / MAX: 18.7MIN: 7.36 / MAX: 17.91

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152edcba51015202518.0918.0814.6518.4214.89MIN: 8.97 / MAX: 18.85MIN: 8.98 / MAX: 18.85MIN: 6.03 / MAX: 16.53MIN: 9.4 / MAX: 19.35MIN: 6.18 / MAX: 17.49

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152edcba51015202518.3014.8818.0417.7118.08MIN: 10.64 / MAX: 19.07MIN: 6.24 / MAX: 18.19MIN: 8.26 / MAX: 18.82MIN: 6.7 / MAX: 18.52MIN: 10.66 / MAX: 18.86

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152edcba4812162018.0718.0817.9718.1517.13MIN: 7.25 / MAX: 18.84MIN: 11.59 / MAX: 18.87MIN: 8.82 / MAX: 18.73MIN: 6.25 / MAX: 18.92MIN: 6.62 / MAX: 17.92

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152edcba4812162018.2418.1416.9017.1218.04MIN: 8.5 / MAX: 19.02MIN: 9.88 / MAX: 18.9MIN: 6.08 / MAX: 17.69MIN: 6.99 / MAX: 17.92MIN: 9.24 / MAX: 18.83

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_ledcba369121513.4813.4813.4313.4213.50MIN: 10.66 / MAX: 17.95MIN: 11.3 / MAX: 17.93MIN: 10.97 / MAX: 17.86MIN: 10.94 / MAX: 18.06MIN: 11.22 / MAX: 17.95

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. The system/openssl test profiles relies on benchmarking the system/OS-supplied openssl binary rather than the pts/openssl test profile that uses the locally-built OpenSSL for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgverify/s, More Is BetterOpenSSLAlgorithm: RSA4096edcba80K160K240K320K400K352828.9351474.2359762.4355954.3347145.51. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

OpenBenchmarking.orgsign/s, More Is BetterOpenSSLAlgorithm: RSA4096edcba120024003600480060005429.55410.15536.05476.05360.01. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

WebP2 Image Encode

This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 75, Compression Effort 7edba0.07880.15760.23640.31520.3940.340.340.330.351. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

Encode Settings: Quality 75, Compression Effort 7

c: The test run did not produce a result.

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152edcba71421283522.4522.7322.3528.9728.71MIN: 22.19 / MAX: 27.15MIN: 22.46 / MAX: 27.6MIN: 22.12 / MAX: 27.32MIN: 7.95 / MAX: 29.71MIN: 8.87 / MAX: 29.47

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50edcba112233445539.2947.8347.0039.3439.05MIN: 10.75 / MAX: 42.24MIN: 16.97 / MAX: 49.88MIN: 11.89 / MAX: 48.99MIN: 10.03 / MAX: 46.87MIN: 10.5 / MAX: 40.73

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50edcba112233445538.6844.1446.4744.4746.32MIN: 9.93 / MAX: 46.76MIN: 11.59 / MAX: 46.03MIN: 11.72 / MAX: 48.37MIN: 12.19 / MAX: 46.31MIN: 12.67 / MAX: 49.3

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50edcba112233445546.6744.5246.9538.9346.82MIN: 15.18 / MAX: 48.54MIN: 13.09 / MAX: 46.68MIN: 11.8 / MAX: 48.85MIN: 10.46 / MAX: 47.12MIN: 12.21 / MAX: 48.82

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50edcba112233445546.5846.4046.3246.7646.88MIN: 12.98 / MAX: 49.17MIN: 11.75 / MAX: 48.73MIN: 12.42 / MAX: 48.73MIN: 16.58 / MAX: 48.66MIN: 15.71 / MAX: 48.91

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50edcba112233445546.4946.3046.7646.7346.48MIN: 11.98 / MAX: 48.65MIN: 12.41 / MAX: 48.18MIN: 12.51 / MAX: 48.77MIN: 12.71 / MAX: 49.06MIN: 14.21 / MAX: 48.5

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Asian Dragon Objedcba71421283531.1331.2731.0931.1231.15MIN: 30.37 / MAX: 32.25MIN: 30.85 / MAX: 31.86MIN: 30.45 / MAX: 32.14MIN: 30.41 / MAX: 32.05MIN: 30.34 / MAX: 32.27

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragon Objedcba71421283531.8831.6531.7231.7531.86MIN: 31.49 / MAX: 33.08MIN: 31.25 / MAX: 33.03MIN: 31.39 / MAX: 32.38MIN: 31.42 / MAX: 32.35MIN: 31.53 / MAX: 32.96

Java SciMark

This test runs the Java version of SciMark 2, which is a benchmark for scientific and numerical computing developed by programmers at the National Institute of Standards and Technology. This benchmark is made up of Fast Foruier Transform, Jacobi Successive Over-relaxation, Monte Carlo, Sparse Matrix Multiply, and dense LU matrix factorization benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Compositeedcba100020003000400050004779.524772.904773.584785.174716.01

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Crownedcba71421283530.1029.9930.3130.0630.07MIN: 29.54 / MAX: 31.88MIN: 29.36 / MAX: 31.72MIN: 29.74 / MAX: 31.91MIN: 29.51 / MAX: 31.67MIN: 29.59 / MAX: 31.69

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Crownedcba71421283530.2730.1930.2030.2530.48MIN: 29.65 / MAX: 32.08MIN: 29.61 / MAX: 31.75MIN: 29.65 / MAX: 31.81MIN: 29.79 / MAX: 32.07MIN: 29.84 / MAX: 32.11

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Asian Dragonedcba81624324034.5034.3834.4834.4434.45MIN: 33.99 / MAX: 35.71MIN: 33.76 / MAX: 35.61MIN: 33.82 / MAX: 35.74MIN: 33.88 / MAX: 35.6MIN: 33.88 / MAX: 35.95

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragonedcba81624324036.2236.4236.2536.4136.21MIN: 35.75 / MAX: 37.76MIN: 35.89 / MAX: 38.27MIN: 35.88 / MAX: 36.94MIN: 35.88 / MAX: 37.89MIN: 35.74 / MAX: 37.79

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50edcba2040608010074.0375.6774.5460.1158.84MIN: 71.54 / MAX: 75.27MIN: 72.62 / MAX: 75.95MIN: 71.89 / MAX: 75.12MIN: 59.29 / MAX: 71.98MIN: 57.25 / MAX: 68.79

WebP2 Image Encode

This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Compression Effort 5edcba36912159.987.659.938.968.831. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Defaultedcba4812162015.6516.2415.4015.8915.781. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

Java SciMark

This test runs the Java version of SciMark 2, which is a benchmark for scientific and numerical computing developed by programmers at the National Institute of Standards and Technology. This benchmark is made up of Fast Foruier Transform, Jacobi Successive Over-relaxation, Monte Carlo, Sparse Matrix Multiply, and dense LU matrix factorization benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Jacobi Successive Over-Relaxationedcba60012001800240030002949.362947.942947.942947.942940.87

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Dense LU Matrix Factorizationedcba3K6K9K12K15K13354.2013337.5013341.6713387.7213059.89

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Sparse Matrix Multiplyedcba100020003000400050004794.854780.864789.244790.644792.04

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Fast Fourier Transformedcba300600900120015001231.131230.691232.911232.021219.73

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Monte Carloedcba300600900120015001568.081567.511556.151567.511567.51