AMD Ryzen 9 7900X Linux AMD Ryzen 9 7900X 12-Core testing with a ASRock X670E PG Lightning (1.11 BIOS) and XFX AMD Radeon RX 6400 4GB on Ubuntu 22.10 via the Phoronix Test Suite. ,,"a","b" Processor,,AMD Ryzen 9 7900X 12-Core @ 5.73GHz (12 Cores / 24 Threads),AMD Ryzen 9 7900X 12-Core @ 5.73GHz (12 Cores / 24 Threads) Motherboard,,ASRock X670E PG Lightning (1.11 BIOS),ASRock X670E PG Lightning (1.11 BIOS) Chipset,,AMD Device 14d8,AMD Device 14d8 Memory,,32GB,32GB Disk,,1000GB Western Digital WDS100T1X0E-00AFY0,1000GB Western Digital WDS100T1X0E-00AFY0 Graphics,,XFX AMD Radeon RX 6400 4GB (2320/1000MHz),XFX AMD Radeon RX 6400 4GB (2320/1000MHz) Audio,,AMD Navi 21/23,AMD Navi 21/23 Monitor,,ASUS MG28U,ASUS MG28U Network,,Realtek RTL8125 2.5GbE,Realtek RTL8125 2.5GbE OS,,Ubuntu 22.10,Ubuntu 22.10 Kernel,,5.19.0-23-generic (x86_64),5.19.0-23-generic (x86_64) Desktop,,GNOME Shell 43.0,GNOME Shell 43.0 Display Server,,X Server + Wayland,X Server + Wayland OpenGL,,4.6 Mesa 22.2.1 (LLVM 15.0.2 DRM 3.47),4.6 Mesa 22.2.1 (LLVM 15.0.2 DRM 3.47) Vulkan,,1.3.224,1.3.224 Compiler,,GCC 12.2.0,GCC 12.2.0 File-System,,ext4,ext4 Screen Resolution,,3840x2160,3840x2160 ,,"a","b" "OpenFOAM - Input: motorBike (sec)",LIB,, "OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Execution Time (sec)",LIB,2217.7849,2222.2378 "OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Mesh Time (sec)",LIB,205.73347,209.58637 "OpenFOAM - Input: motorBike - Execution Time (sec)",LIB,,2.65814 "BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,308235,304290 "TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec)",HIB,39.8,39.82 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,635.91,635.69 "TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec)",HIB,121.89,121.98 "nekRS - Input: TurboPipe Periodic (FLOP/s)",HIB,64871200000,65118300000 "SMHasher - Hash: SHA3-256 (cycles/hash)",LIB,2499.008,2530.422 "SMHasher - Hash: SHA3-256 (MiB/sec)",HIB,161.66,155.7 "OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,337.94,338.61 "Timed Node.js Compilation - Time To Compile (sec)",LIB,314.638,312.035 "JPEG XL libjxl - Input: JPEG - Quality: 100 (MP/s)",HIB,0.97,0.93 "TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,121.77,121.89 "JPEG XL libjxl - Input: PNG - Quality: 100 (MP/s)",HIB,1.05,1.03 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,211.89,211.89 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,178.55423,176.08591 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,25.203143,25.805769 "OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,193.52,192.08 "FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,18.13,18.08 "FFmpeg - Encoder: libx264 - Scenario: Upload (sec)",LIB,139.275300113,139.66 "Timed CPython Compilation - Build Configuration: Released Build, PGO + LTO Optimized (sec)",LIB,183.357,182.609 "FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,44.70,45.21 "FFmpeg - Encoder: libx265 - Scenario: Platform (sec)",LIB,169.47,167.5404742 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,45.01,45.25 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (sec)",LIB,168.30,167.40 "TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,39.48,39.53 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,169.11,169.57 "FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,22.22,22.27 "FFmpeg - Encoder: libx265 - Scenario: Upload (sec)",LIB,113.65,113.360639293 "TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,357.68,357.7 "PostgreSQL - Scaling Factor: 100 - Clients: 1 - Mode: Read Only - Average Latency (ms)",LIB,0.016,0.018 "PostgreSQL - Scaling Factor: 100 - Clients: 1 - Mode: Read Only (TPS)",HIB,61322,56707 "PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency (ms)",LIB,0.152,0.153 "PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Only (TPS)",HIB,656243,652856 "PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency (ms)",LIB,1.723,1.668 "PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Write (TPS)",HIB,58054,59960 "PostgreSQL - Scaling Factor: 100 - Clients: 1 - Mode: Read Write - Average Latency (ms)",LIB,0.37,0.367 "PostgreSQL - Scaling Factor: 100 - Clients: 1 - Mode: Read Write (TPS)",HIB,2705,2724 "PostgreSQL - Scaling Factor: 100 - Clients: 50 - Mode: Read Only - Average Latency (ms)",LIB,0.069,0.068 "PostgreSQL - Scaling Factor: 100 - Clients: 50 - Mode: Read Only (TPS)",HIB,722315,736786 "PostgreSQL - Scaling Factor: 100 - Clients: 50 - Mode: Read Write - Average Latency (ms)",LIB,1.129,0.995 "PostgreSQL - Scaling Factor: 100 - Clients: 50 - Mode: Read Write (TPS)",HIB,44304,50233 "PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency (ms)",LIB,41.058,40.957 "PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Write (TPS)",HIB,2436,2442 "PostgreSQL - Scaling Factor: 1 - Clients: 1 - Mode: Read Only - Average Latency (ms)",LIB,0.017,0.017 "PostgreSQL - Scaling Factor: 1 - Clients: 1 - Mode: Read Only (TPS)",HIB,59102,58025 "PostgreSQL - Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency (ms)",LIB,18.369,18.424 "PostgreSQL - Scaling Factor: 1 - Clients: 50 - Mode: Read Write (TPS)",HIB,2722,2714 "PostgreSQL - Scaling Factor: 1 - Clients: 1 - Mode: Read Write - Average Latency (ms)",LIB,0.352,0.357 "PostgreSQL - Scaling Factor: 1 - Clients: 1 - Mode: Read Write (TPS)",HIB,2838,2799 "PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency (ms)",LIB,0.148,0.143 "PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Only (TPS)",HIB,674178,700101 "PostgreSQL - Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency (ms)",LIB,0.064,0.065 "PostgreSQL - Scaling Factor: 1 - Clients: 50 - Mode: Read Only (TPS)",HIB,779915,772349 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s)",HIB,40.974,41.054 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (GFInst/s)",HIB,1024.349,1026.341 "FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,69.28,68.83 "FFmpeg - Encoder: libx264 - Scenario: Video On Demand (sec)",LIB,109.33,110.05 "FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,69.14,69.43 "FFmpeg - Encoder: libx264 - Scenario: Platform (sec)",LIB,109.552711309,109.10 "Mobile Neural Network - Model: inception-v3 (ms)",LIB,21.158,20.742 "Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,3.251,3.233 "Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,2.857,3.04 "Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,3.692,3.751 "Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,12.864,12.582 "Mobile Neural Network - Model: squeezenetv1.1 (ms)",LIB,2.308,2.389 "Mobile Neural Network - Model: mobilenetV3 (ms)",LIB,1.428,1.466 "Mobile Neural Network - Model: nasnet (ms)",LIB,9.676,10.135 "OpenRadioss - Model: Bumper Beam (sec)",LIB,100.34,100.56 "JPEG XL libjxl - Input: JPEG - Quality: 80 (MP/s)",HIB,11.93,12.48 "JPEG XL libjxl - Input: PNG - Quality: 80 (MP/s)",HIB,12.02,12.74 "TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,39.35,39.31 "nginx - Connections: 1000 (Reqs/sec)",HIB,125963.01,122285.31 "nginx - Connections: 500 (Reqs/sec)",HIB,135867.53,133787.04 "nginx - Connections: 200 (Reqs/sec)",HIB,137835.76,136170.71 "nginx - Connections: 100 (Reqs/sec)",HIB,137650.85,136318.84 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,85.49,85.08 "libavif avifenc - Encoder Speed: 0 (sec)",LIB,84.035,84.756 "TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,348.9,348.49 "OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,78.35,77.83 "JPEG XL libjxl - Input: JPEG - Quality: 90 (MP/s)",HIB,11.78,12.4 "Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,12605.1,13238.9 "AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,10.08,10.14 "JPEG XL libjxl - Input: PNG - Quality: 90 (MP/s)",HIB,11.96,12.67 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,1464.71,1462.28 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1468.84,1461.51 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1461.42,1468.12 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,749.498,748.408 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,749.601,749.088 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,751.24,749.215 "ClickHouse - 100M Rows Web Analytics Dataset, Third Run (Queries/min, Geo Mean)",HIB,269.06,273.74 "ClickHouse - 100M Rows Web Analytics Dataset, Second Run (Queries/min, Geo Mean)",HIB,259.88,273.31 "ClickHouse - 100M Rows Web Analytics Dataset, First Run / Cold Cache (Queries/min, Geo Mean)",HIB,231.71,252.20 "OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,66.53,66.45 "Dragonflydb - Clients: 200 - Set To Get Ratio: 5:1 (Ops/sec)",HIB,4624845.97,4630859.67 "Dragonflydb - Clients: 200 - Set To Get Ratio: 1:1 (Ops/sec)",HIB,4831108.14,4763803.93 "Dragonflydb - Clients: 200 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,4968213.38,5055548.28 "Dragonflydb - Clients: 50 - Set To Get Ratio: 5:1 (Ops/sec)",HIB,4692530.64,4640660.41 "Dragonflydb - Clients: 50 - Set To Get Ratio: 1:1 (Ops/sec)",HIB,4846900.63,4791381.14 "Dragonflydb - Clients: 50 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,5133428.52,5031752.18 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,66.07,66.19 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,15466.9,15523.4 "Timed Erlang/OTP Compilation - Time To Compile (sec)",LIB,65.646,64.454 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,1015.76,1020.98 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,5.87,5.84 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,1014.92,1019.72 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,5.9,5.85 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,559.91,558.64 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,10.69,10.72 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,287.38,287.56 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,20.84,20.83 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,55.16,55.87 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,108.68,107.32 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,4.8,4.81 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,1249.34,1244.72 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.25,0.25 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,47791.89,47792.77 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,4.33,4.34 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,1384.25,1382.6 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,8.35,8.25 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,717.9,726.25 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.35,0.35 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,33642.44,33761.4 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,5.59,5.59 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,1071.83,1071.58 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,5.53,5.53 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,2168.46,2168.92 "TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,123.2,123.4 "FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,114.72,114.97 "FFmpeg - Encoder: libx265 - Scenario: Live (sec)",LIB,44.02,43.93 "AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,0.35,0.36 "spaCy - Model: en_core_web_trf (tokens/sec)",HIB,1514,1518 "spaCy - Model: en_core_web_lg (tokens/sec)",HIB,18996,19009 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,38.17,38.16 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,632.756,632.2099 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,9.4344,9.4433 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,630.9481,631.7603 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,9.4567,9.4533 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,82.9905,83.6437 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,72.282,71.7045 "AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,17.6,17.83 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,20.0699,20.3906 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,49.816,49.033 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,114.3078,114.0039 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,8.748,8.7713 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,113.91,113.9358 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,8.7785,8.7765 "libavif avifenc - Encoder Speed: 2 (sec)",LIB,41.365,42.38 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,65.4985,65.5084 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,91.5744,91.5226 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,17.567,17.5355 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,56.905,57.0091 "Timed PHP Compilation - Time To Compile (sec)",LIB,39.368,39.473 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,41.8197,41.7556 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,143.4093,143.6075 "JPEG XL Decoding libjxl - CPU Threads: 1 (MP/s)",HIB,68.43,73.37 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,10.4443,10.5361 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,95.7092,94.8741 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,63.412,63.3274 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,94.5869,94.6963 "AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,19.19,19.23 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,13.5387,13.542 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,73.8179,73.8024 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,26.8652,26.8227 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,223.1411,223.5328 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,7.2448,7.2408 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,137.9275,138.0086 "Timed Wasmer Compilation - Time To Compile (sec)",LIB,35.704,35.917 "Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,7269058.58,7822736.2 "Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,15910,16300 "Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,515.94,509.75 "TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,124.88,124.83 "Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,12824745.14,12852176.64 "Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,6023.06,6055.08 "Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,105410.52,100434.75 "Stress-NG - Test: Forking (Bogo Ops/s)",HIB,85644.09,88150.54 "Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,34722.62,32274.88 "Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,1052.54,1052.36 "Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,24051732.07,24222411.86 "Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,24405.52,27013 "Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,203812.22,199497.81 "Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,604.96,570.87 "Stress-NG - Test: Futex (Bogo Ops/s)",HIB,3968210.34,3648065 "Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,288.78,290.15 "Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,140.39,145.06 "Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,285.64,283.15 "Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,3786314.58,3784061.09 "Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,21588.47,19398.62 "Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,107491.73,107282.73 "Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,2647043.16,2653440.36 "Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,44344.82,44430.82 "Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,386040.06,387020.54 "Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,10556564.45,11885212.76 "Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,3641.88,3537.11 "Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,3286.46,3291.46 "Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,109350,109450 "JPEG XL Decoding libjxl - CPU Threads: All (MP/s)",HIB,179.93,198.29 "Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,1343070,1029150 "Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,863.91,852.17 "FFmpeg - Encoder: libx264 - Scenario: Live (FPS)",HIB,299.42,298.97 "FFmpeg - Encoder: libx264 - Scenario: Live (sec)",LIB,16.865922261,16.89 "Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,322550,338820 "Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,231140,235620 "Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,209170,209440 "Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,50470,51020 "Cpuminer-Opt - Algorithm: x25x (kH/s)",HIB,885.22,889.91 "EnCodec - Target Bandwidth: 24 kbps (sec)",LIB,28.898,28.712 "TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,289.65,289.36 "EnCodec - Target Bandwidth: 6 kbps (sec)",LIB,25.189,25.251 "EnCodec - Target Bandwidth: 3 kbps (sec)",LIB,24.989,25.064 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (UE Mb/s)",HIB,239.3,249.1 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (eNb Mb/s)",HIB,626.3,668.5 "EnCodec - Target Bandwidth: 1.5 kbps (sec)",LIB,24.334,24.28 "Stream - Type: Copy (MB/s)",HIB,60212.6,60281.9 "Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,21.889,21.881 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5.19899,5.19599 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,4.04957,3.91733 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.547255,0.54655 "srsRAN - Test: OFDM_Test (Samples / Second)",HIB,222900000,225000000 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (UE Mb/s)",HIB,227.6,231.2 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (eNb Mb/s)",HIB,603.1,611.3 "AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,1.01,1.01 "QuadRay - Scene: 5 - Resolution: 4K (FPS)",HIB,1.44,1.55 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s)",HIB,40.287,40.296 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (GFInst/s)",HIB,1007.166,1007.41 "Natron - Input: Spaceship (FPS)",HIB,5.5,5.4 "QuadRay - Scene: 1 - Resolution: 4K (FPS)",HIB,19.81,20 "QuadRay - Scene: 3 - Resolution: 4K (FPS)",HIB,4.83,4.84 "QuadRay - Scene: 2 - Resolution: 4K (FPS)",HIB,5.52,5.62 "QuadRay - Scene: 5 - Resolution: 1080p (FPS)",HIB,5.71,5.96 "QuadRay - Scene: 3 - Resolution: 1080p (FPS)",HIB,18.52,18.55 "QuadRay - Scene: 2 - Resolution: 1080p (FPS)",HIB,20.95,21.31 "QuadRay - Scene: 1 - Resolution: 1080p (FPS)",HIB,76.23,76.57 "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,136525,136291 "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,154326,154559 "AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K (FPS)",HIB,35.96,37.19 "AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,44.2,44.39 "TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,227.01,227.31 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,123.22,123.22 "oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,2.20161,2.2027 "oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,0.973041,0.989482 "oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.521835,0.496825 "Timed CPython Compilation - Build Configuration: Default (sec)",LIB,13.037,13.14 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,158.36,158.05 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (UE Mb/s)",HIB,251,251 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (eNb Mb/s)",HIB,650.9,643.9 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,0.293989,0.293853 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,0.553097,0.553435 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.179975,0.179875 "AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K (FPS)",HIB,51.88,54.63 "C-Blosc - Test: blosclz bitshuffle (MB/s)",HIB,11242.2,11489.5 "FLAC Audio Encoding - WAV To FLAC (sec)",LIB,11.732,11.79 "Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,10.28,10.225 "srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (UE Mb/s)",HIB,122.9,137.5 "srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (eNb Mb/s)",HIB,200.6,200.8 "SMHasher - Hash: FarmHash128 (cycles/hash)",LIB,64.582,64.658 "SMHasher - Hash: FarmHash128 (MiB/sec)",HIB,15702.24,15674.6 "TensorFlow - Device: CPU - Batch Size: 512 - Model: ResNet-50 (images/sec)",HIB,, "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (UE Mb/s)",HIB,239.2,242.4 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (eNb Mb/s)",HIB,601.3,598.7 "oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,3.2857,3.27851 "AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K (FPS)",HIB,68.39,72.65 "oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1.52187,1.5797 "oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.337307,0.369351 "SMHasher - Hash: MeowHash x86_64 AES-NI (cycles/hash)",LIB,57.823,58.316 "SMHasher - Hash: MeowHash x86_64 AES-NI (MiB/sec)",HIB,42374.8,41856.36 "AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K (FPS)",HIB,69.66,73.51 "AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p (FPS)",HIB,66.86,78.1 "SMHasher - Hash: Spooky32 (cycles/hash)",LIB,36.371,36.577 "SMHasher - Hash: Spooky32 (MiB/sec)",HIB,15384.04,15317.97 "C-Blosc - Test: blosclz shuffle (MB/s)",HIB,20713.1,21142.2 "libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,6.224,6.315 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,5.75764,5.75116 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,5.38305,5.38606 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1.8424,1.83776 "SMHasher - Hash: FarmHash32 x86_64 AVX (cycles/hash)",LIB,35.607,34.029 "SMHasher - Hash: FarmHash32 x86_64 AVX (MiB/sec)",HIB,29550.62,31036.72 "SMHasher - Hash: fasthash32 (cycles/hash)",LIB,30.057,30.098 "SMHasher - Hash: fasthash32 (MiB/sec)",HIB,6548.49,6508.85 "SMHasher - Hash: t1ha2_atonce (cycles/hash)",LIB,27.273,27.237 "SMHasher - Hash: t1ha2_atonce (MiB/sec)",HIB,14943.5,14998.97 "SMHasher - Hash: t1ha0_aes_avx2 x86_64 (cycles/hash)",LIB,27.632,27.511 "SMHasher - Hash: t1ha0_aes_avx2 x86_64 (MiB/sec)",HIB,75924.15,76015.27 "AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p (FPS)",HIB,119.52,124.05 "Unpacking The Linux Kernel - linux-5.19.tar.xz (sec)",LIB,4.64,4.63 "AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p (FPS)",HIB,148.98,148.57 "SMHasher - Hash: wyhash (cycles/hash)",LIB,19.608,19.924 "SMHasher - Hash: wyhash (MiB/sec)",HIB,23038,22824.89 "AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p (FPS)",HIB,150.63,153.13 "libavif avifenc - Encoder Speed: 6 (sec)",LIB,3.769,3.736 "libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,3.535,3.543 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,3.11616,3.11582 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1.85387,1.85422 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.789632,0.763137 "nginx - Connections: 4000 (Reqs/sec)",HIB,, "nginx - Connections: 1 (Reqs/sec)",HIB,, "nginx - Connections: 20 (Reqs/sec)",HIB,, "Stress-NG - Test: x86_64 RdRand ()",,, "Stream - Type: Add (MB/s)",HIB,44030.5,43942.1 "Stream - Type: Triad (MB/s)",HIB,44032.4,44086.5 "Stream - Type: Scale (MB/s)",HIB,39775.5,39742.5