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
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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
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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 novjava-scimark2: Compositejava-scimark2: Monte Carlojava-scimark2: Fast Fourier Transformjava-scimark2: Sparse Matrix Multiplyjava-scimark2: Dense LU Matrix Factorizationjava-scimark2: Jacobi Successive Over-Relaxationwebp2: Defaultwebp2: Quality 75, Compression Effort 7webp2: Quality 95, Compression Effort 7webp2: Quality 100, Compression Effort 5webp2: Quality 100, Lossless Compressionembree: Pathtracer - Crownembree: Pathtracer ISPC - Crownembree: Pathtracer - Asian Dragonembree: Pathtracer - Asian Dragon Objembree: Pathtracer ISPC - Asian Dragonembree: Pathtracer ISPC - Asian Dragon Objopenssl: SHA256openssl: SHA512openssl: RSA4096openssl: RSA4096pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_labcde4716.011567.511219.734792.0413059.892940.8715.780.350.168.830.0430.071330.478334.44631.151636.212431.85835474953010108494812105360347145.558.8428.7146.3246.4846.8217.1739.0518.0446.8814.8918.0817.1313.508.7910.098.858.948.904785.171567.511232.024790.6413387.722947.9415.890.330.168.960.0430.059830.247134.442431.122436.408631.747335998666020110625787605476355954.360.1128.9744.4746.7338.9317.6339.3417.1246.7618.4217.7118.1513.4211.658.8210.5111.9811.674773.581556.151232.914789.2413341.672947.9415.400.169.930.0430.30730.201334.479431.088936.247931.72335762336880109757274005536359762.474.5422.3546.4746.7646.9517.9947.0016.9046.3214.6518.0417.9713.438.888.8911.608.9510.504772.91567.511230.694780.8613337.52947.9416.240.340.167.650.0429.992330.191334.377631.266336.421731.654935625391340108158572305410.1351474.275.6722.7344.1446.3044.5215.1447.8318.1446.4018.0814.8818.0813.488.8011.728.9211.598.964779.521568.081231.134794.8513354.22949.3615.650.340.169.980.0430.096430.273134.503231.129436.222731.881335567121540110063308705429.5352828.974.0322.4538.6846.4946.6718.1739.2918.2446.5818.0918.3018.0713.4811.8612.098.878.7811.69OpenBenchmarking.org

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: Compositeabcde100020003000400050004716.014785.174773.584772.904779.52

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Monte Carloabcde300600900120015001567.511567.511556.151567.511568.08

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Fast Fourier Transformabcde300600900120015001219.731232.021232.911230.691231.13

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Sparse Matrix Multiplyabcde100020003000400050004792.044790.644789.244780.864794.85

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Dense LU Matrix Factorizationabcde3K6K9K12K15K13059.8913387.7213341.6713337.5013354.20

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Jacobi Successive Over-Relaxationabcde60012001800240030002940.872947.942947.942947.942949.36

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: Defaultabcde4812162015.7815.8915.4016.2415.651. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 75, Compression Effort 7abde0.07880.15760.23640.31520.3940.350.330.340.341. (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.

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 95, Compression Effort 7abcde0.0360.0720.1080.1440.180.160.160.160.160.161. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Compression Effort 5abcde36912158.838.969.937.659.981. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Lossless Compressionabcde0.0090.0180.0270.0360.0450.040.040.040.040.041. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

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: Crownabcde71421283530.0730.0630.3129.9930.10MIN: 29.59 / MAX: 31.69MIN: 29.51 / MAX: 31.67MIN: 29.74 / MAX: 31.91MIN: 29.36 / MAX: 31.72MIN: 29.54 / MAX: 31.88

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Crownabcde71421283530.4830.2530.2030.1930.27MIN: 29.84 / MAX: 32.11MIN: 29.79 / MAX: 32.07MIN: 29.65 / MAX: 31.81MIN: 29.61 / MAX: 31.75MIN: 29.65 / MAX: 32.08

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Asian Dragonabcde81624324034.4534.4434.4834.3834.50MIN: 33.88 / MAX: 35.95MIN: 33.88 / MAX: 35.6MIN: 33.82 / MAX: 35.74MIN: 33.76 / MAX: 35.61MIN: 33.99 / MAX: 35.71

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Asian Dragon Objabcde71421283531.1531.1231.0931.2731.13MIN: 30.34 / MAX: 32.27MIN: 30.41 / MAX: 32.05MIN: 30.45 / MAX: 32.14MIN: 30.85 / MAX: 31.86MIN: 30.37 / MAX: 32.25

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragonabcde81624324036.2136.4136.2536.4236.22MIN: 35.74 / MAX: 37.79MIN: 35.88 / MAX: 37.89MIN: 35.88 / MAX: 36.94MIN: 35.89 / MAX: 38.27MIN: 35.75 / MAX: 37.76

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragon Objabcde71421283531.8631.7531.7231.6531.88MIN: 31.53 / MAX: 32.96MIN: 31.42 / MAX: 32.35MIN: 31.39 / MAX: 32.38MIN: 31.25 / MAX: 33.03MIN: 31.49 / MAX: 33.08

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: SHA256abcde8000M16000M24000M32000M40000M35474953010359986660203576233688035625391340355671215401. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA512abcde2000M4000M6000M8000M10000M10849481210110625787601097572740010815857230110063308701. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

OpenBenchmarking.orgsign/s, More Is BetterOpenSSLAlgorithm: RSA4096abcde120024003600480060005360.05476.05536.05410.15429.51. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

OpenBenchmarking.orgverify/s, More Is BetterOpenSSLAlgorithm: RSA4096abcde80K160K240K320K400K347145.5355954.3359762.4351474.2352828.91. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

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.

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: 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: 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.

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abcde2040608010058.8460.1174.5475.6774.03MIN: 57.25 / MAX: 68.79MIN: 59.29 / MAX: 71.98MIN: 71.89 / MAX: 75.12MIN: 72.62 / MAX: 75.95MIN: 71.54 / MAX: 75.27

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152abcde71421283528.7128.9722.3522.7322.45MIN: 8.87 / MAX: 29.47MIN: 7.95 / MAX: 29.71MIN: 22.12 / MAX: 27.32MIN: 22.46 / MAX: 27.6MIN: 22.19 / MAX: 27.15

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50abcde112233445546.3244.4746.4744.1438.68MIN: 12.67 / MAX: 49.3MIN: 12.19 / MAX: 46.31MIN: 11.72 / MAX: 48.37MIN: 11.59 / MAX: 46.03MIN: 9.93 / MAX: 46.76

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50abcde112233445546.4846.7346.7646.3046.49MIN: 14.21 / MAX: 48.5MIN: 12.71 / MAX: 49.06MIN: 12.51 / MAX: 48.77MIN: 12.41 / MAX: 48.18MIN: 11.98 / MAX: 48.65

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50abcde112233445546.8238.9346.9544.5246.67MIN: 12.21 / MAX: 48.82MIN: 10.46 / MAX: 47.12MIN: 11.8 / MAX: 48.85MIN: 13.09 / MAX: 46.68MIN: 15.18 / MAX: 48.54

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152abcde4812162017.1717.6317.9915.1418.17MIN: 7.36 / MAX: 17.91MIN: 8.26 / MAX: 18.7MIN: 7.44 / MAX: 18.86MIN: 5.99 / MAX: 17.74MIN: 9.41 / MAX: 18.96

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50abcde112233445539.0539.3447.0047.8339.29MIN: 10.5 / MAX: 40.73MIN: 10.03 / MAX: 46.87MIN: 11.89 / MAX: 48.99MIN: 16.97 / MAX: 49.88MIN: 10.75 / MAX: 42.24

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152abcde4812162018.0417.1216.9018.1418.24MIN: 9.24 / MAX: 18.83MIN: 6.99 / MAX: 17.92MIN: 6.08 / MAX: 17.69MIN: 9.88 / MAX: 18.9MIN: 8.5 / MAX: 19.02

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50abcde112233445546.8846.7646.3246.4046.58MIN: 15.71 / MAX: 48.91MIN: 16.58 / MAX: 48.66MIN: 12.42 / MAX: 48.73MIN: 11.75 / MAX: 48.73MIN: 12.98 / MAX: 49.17

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152abcde51015202514.8918.4214.6518.0818.09MIN: 6.18 / MAX: 17.49MIN: 9.4 / MAX: 19.35MIN: 6.03 / MAX: 16.53MIN: 8.98 / MAX: 18.85MIN: 8.97 / MAX: 18.85

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152abcde51015202518.0817.7118.0414.8818.30MIN: 10.66 / MAX: 18.86MIN: 6.7 / MAX: 18.52MIN: 8.26 / MAX: 18.82MIN: 6.24 / MAX: 18.19MIN: 10.64 / MAX: 19.07

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152abcde4812162017.1318.1517.9718.0818.07MIN: 6.62 / MAX: 17.92MIN: 6.25 / MAX: 18.92MIN: 8.82 / MAX: 18.73MIN: 11.59 / MAX: 18.87MIN: 7.25 / MAX: 18.84

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_labcde369121513.5013.4213.4313.4813.48MIN: 11.22 / MAX: 17.95MIN: 10.94 / MAX: 18.06MIN: 10.97 / MAX: 17.86MIN: 11.3 / MAX: 17.93MIN: 10.66 / MAX: 17.95

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_labcde36912158.7911.658.888.8011.86MIN: 4.35 / MAX: 9.75MIN: 5.27 / MAX: 12.15MIN: 4.94 / MAX: 9.08MIN: 5.17 / MAX: 8.94MIN: 5.09 / MAX: 12.28

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_labcde369121510.098.828.8911.7212.09MIN: 4.54 / MAX: 12.07MIN: 5.03 / MAX: 9.05MIN: 3.85 / MAX: 9.08MIN: 5.22 / MAX: 12.2MIN: 5.97 / MAX: 12.57

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_labcde36912158.8510.5111.608.928.87MIN: 4.16 / MAX: 9.06MIN: 4.81 / MAX: 11.29MIN: 5.57 / MAX: 12.14MIN: 4.97 / MAX: 9.08MIN: 4.6 / MAX: 9.03

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_labcde36912158.9411.988.9511.598.78MIN: 5 / MAX: 9.09MIN: 5.05 / MAX: 12.49MIN: 4.32 / MAX: 9MIN: 5.55 / MAX: 12.11MIN: 4.28 / MAX: 9.7

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_labcde36912158.9011.6710.508.9611.69MIN: 4.78 / MAX: 9.1MIN: 5.41 / MAX: 12.17MIN: 4.78 / MAX: 10.98MIN: 4.16 / MAX: 9.35MIN: 5.58 / MAX: 12.18