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Intel Core i5-12600K testing with a ASUS PRIME Z690-P WIFI D4 (0605 BIOS) and ASUS Intel ADL-S GT1 15GB on Ubuntu 22.04 via the Phoronix Test Suite.

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A
October 14 2022
  1 Hour, 37 Minutes
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October 14 2022
  1 Hour, 36 Minutes
C
October 14 2022
  1 Hour, 35 Minutes
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fgds Intel Core i5-12600K testing with a ASUS PRIME Z690-P WIFI D4 (0605 BIOS) and ASUS Intel ADL-S GT1 15GB on Ubuntu 22.04 via the Phoronix Test Suite. ,,"A","B","C" Processor,,Intel Core i5-12600K @ 6.30GHz (10 Cores / 16 Threads),Intel Core i5-12600K @ 6.30GHz (10 Cores / 16 Threads),Intel Core i5-12600K @ 6.30GHz (10 Cores / 16 Threads) Motherboard,,ASUS PRIME Z690-P WIFI D4 (0605 BIOS),ASUS PRIME Z690-P WIFI D4 (0605 BIOS),ASUS PRIME Z690-P WIFI D4 (0605 BIOS) Chipset,,Intel Device 7aa7,Intel Device 7aa7,Intel Device 7aa7 Memory,,16GB,16GB,16GB Disk,,1000GB Western Digital WDS100T1X0E-00AFY0,1000GB Western Digital WDS100T1X0E-00AFY0,1000GB Western Digital WDS100T1X0E-00AFY0 Graphics,,ASUS Intel ADL-S GT1 15GB (1450MHz),ASUS Intel ADL-S GT1 15GB (1450MHz),ASUS Intel ADL-S GT1 15GB (1450MHz) Audio,,Realtek ALC897,Realtek ALC897,Realtek ALC897 Monitor,,ASUS MG28U,ASUS MG28U,ASUS MG28U Network,,Realtek RTL8125 2.5GbE + Intel Device 7af0,Realtek RTL8125 2.5GbE + Intel Device 7af0,Realtek RTL8125 2.5GbE + Intel Device 7af0 OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04 Kernel,,5.19.0-051900rc6daily20220716-generic (x86_64),5.19.0-051900rc6daily20220716-generic (x86_64),5.19.0-051900rc6daily20220716-generic (x86_64) Desktop,,GNOME Shell 42.1,GNOME Shell 42.1,GNOME Shell 42.1 Display Server,,X Server 1.21.1.3 + Wayland,X Server 1.21.1.3 + Wayland,X Server 1.21.1.3 + Wayland OpenGL,,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1 OpenCL,,OpenCL 3.0,OpenCL 3.0,OpenCL 3.0 Vulkan,,1.2.204,1.2.204,1.2.204 Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0 File-System,,ext4,ext4,ext4 Screen Resolution,,3840x2160,3840x2160,3840x2160 ,,"A","B","C" "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.15139,1.01232,1.30001 "AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p (FPS)",HIB,152.85,178.37,153.46 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,2.81573,2.74589,2.54921 "AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p (FPS)",HIB,58.85,57.88,63.46 "OpenRadioss - Model: Bumper Beam (sec)",LIB,247.09,229.96,228.07 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.21457,2.97401,3.14484 "OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,176.92,167.33,164.08 "AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p (FPS)",HIB,120.56,127.4,125.13 "QuadRay - Scene: 5 - Resolution: 1080p (FPS)",HIB,1.25,1.3,1.32 "oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.16332,2.2832,2.27602 "AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,16.65,17.49,17.49 "AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p (FPS)",HIB,143.74,149.25,149.74 "AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,40.35,41.89,41.88 "OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,385.82,372.34,375.12 "AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K (FPS)",HIB,47.81,49.44,49.03 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,41.026,41.3871,40.1623 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,24.3728,24.1602,24.8968 "oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,4.02417,3.91825,3.98114 "OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,801.99,783.86,785.09 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,4508.32,4410.31,4439.89 "AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K (FPS)",HIB,32.46,33.16,32.9 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,9.81485,9.81997,10.0265 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,12.3233,12.4455,12.1851 "AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K (FPS)",HIB,66.8,67.47,68.15 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,56.6863,56.7934,55.685 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,6.8952,6.9928,6.8642 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,181.3915,180.3981,183.7367 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,87.7065,87.6815,89.2754 "Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,20.709,20.576,20.343 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,174.6769,175.7057,172.6192 "spaCy - Model: en_core_web_trf (tokens/sec)",HIB,1089,1070,1074 "AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K (FPS)",HIB,67.8,68.67,68.96 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,27.4492,27.5853,27.1621 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,20.4915,20.5712,20.8072 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,48.7926,48.6039,48.0533 "Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,43.396,43.469,44.053 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4474.24,4409.87,4439.06 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,154.3873,154.5326,152.316 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,6.4771,6.471,6.5651 "AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,0.71,0.72,0.72 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,28.6104,28.3942,28.763 "OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,288.06,285.73,284.58 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,152.3149,152.8951,151.1311 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,6.5652,6.5403,6.6166 "SMHasher - Hash: MeowHash x86_64 AES-NI (MiB/sec)",HIB,49353.69,48796.81,49349.97 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,718.1784,713.0947,720.9402 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2168.08,2159.81,2183.19 "TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,102.28,102.95,103.34 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,38.3527,38.2669,37.961 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,26.0677,26.1249,26.3363 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,44.1097,44.2336,43.7836 "AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,12.81,12.87,12.94 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2161.75,2160.41,2182.09 "AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,7.14,7.17,7.21 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,8.14523,8.06747,8.11715 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,112.5148,112.2559,113.2816 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.09297,2.11167,2.09377 "oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,10.6049,10.6994,10.6977 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,2177.7,2160.58,2179.57 "spaCy - Model: en_core_web_lg (tokens/sec)",HIB,17226,17254,17118 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,14.3255,14.4341,14.3922 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,4439.64,4407.58,4429.54 "SMHasher - Hash: FarmHash32 x86_64 AVX (MiB/sec)",HIB,26888.83,26897.98,26713.68 "TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,54.43,54.06,54.29 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,56.7792,56.416,56.7406 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,87.7613,88.3197,88.0674 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,17.83,17.88,17.93 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,52.52,52.25,52.37 "TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,18.44,18.39,18.47 "SMHasher - Hash: SHA3-256 (MiB/sec)",HIB,244.07,245.01,245.08 "QuadRay - Scene: 1 - Resolution: 1080p (FPS)",HIB,19.5,19.57,19.49 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,6.8935,6.8793,6.8706 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,70.8607,70.7403,70.6592 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,14.108,14.1319,14.1481 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,22.9286,22.9136,22.8682 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,43.6063,43.6348,43.7211 "SMHasher - Hash: wyhash (MiB/sec)",HIB,29154.23,29184.54,29220.87 "QuadRay - Scene: 3 - Resolution: 1080p (FPS)",HIB,4.59,4.6,4.6 "QuadRay - Scene: 1 - Resolution: 4K (FPS)",HIB,4.97,4.98,4.97 "QuadRay - Scene: 2 - Resolution: 1080p (FPS)",HIB,5.6,5.61,5.61 "SMHasher - Hash: FarmHash128 (MiB/sec)",HIB,19170.14,19201.69,19197.59 "oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.46342,1.46173,1.46136 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,719.4564,720.3533,720.1774 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,80.04,80.1,80.04 "SMHasher - Hash: Spooky32 (MiB/sec)",HIB,17969.01,17981.71,17979.56 "SMHasher - Hash: t1ha2_atonce (MiB/sec)",HIB,21936.55,21929.77,21936.73 "SMHasher - Hash: t1ha0_aes_avx2 x86_64 (MiB/sec)",HIB,72005.91,72004.31,71999.16 "SMHasher - Hash: fasthash32 (MiB/sec)",HIB,7604.24,7603.85,7604.38 "AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,0.24,0.24,0.24 "QuadRay - Scene: 5 - Resolution: 4K (FPS)",HIB,0.32,0.32,0.32 "QuadRay - Scene: 3 - Resolution: 4K (FPS)",HIB,1.18,1.18,1.18 "QuadRay - Scene: 2 - Resolution: 4K (FPS)",HIB,1.42,1.42,1.42 "SMHasher - Hash: MeowHash x86_64 AES-NI (cycles/hash)",LIB,54.283,54.33,54.315 "SMHasher - Hash: t1ha0_aes_avx2 x86_64 (cycles/hash)",LIB,25.065,25.065,25.065 "SMHasher - Hash: FarmHash32 x86_64 AVX (cycles/hash)",LIB,32.834,32.608,32.823 "SMHasher - Hash: t1ha2_atonce (cycles/hash)",LIB,25.296,25.296,25.296 "SMHasher - Hash: FarmHash128 (cycles/hash)",LIB,53.742,53.742,53.742 "SMHasher - Hash: fasthash32 (cycles/hash)",LIB,28.186,28.186,28.188 "SMHasher - Hash: Spooky32 (cycles/hash)",LIB,33.853,33.782,33.818 "SMHasher - Hash: SHA3-256 (cycles/hash)",LIB,1599.281,1595.176,1596.083 "SMHasher - Hash: wyhash (cycles/hash)",LIB,18.552,18.552,18.551