christmas comet Intel Core i7-10700T testing with a Logic Supply RXM-181 (Z01-0002A026 BIOS) and Intel UHD 630 CML GT2 30GB on Ubuntu 22.04 via the Phoronix Test Suite. a: Processor: Intel Core i7-10700T @ 4.50GHz (8 Cores / 16 Threads), Motherboard: Logic Supply RXM-181 (Z01-0002A026 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: 256GB TS256GMTS800, Graphics: Intel UHD 630 CML GT2 30GB (1200MHz), Audio: Realtek ALC233, Monitor: DELL P2415Q, Network: Intel I219-LM + Intel I210 OS: Ubuntu 22.04, Kernel: 5.15.0-52-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1080 b: Processor: Intel Core i7-10700T @ 4.50GHz (8 Cores / 16 Threads), Motherboard: Logic Supply RXM-181 (Z01-0002A026 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: 256GB TS256GMTS800, Graphics: Intel UHD 630 CML GT2 30GB (1200MHz), Audio: Realtek ALC233, Monitor: DELL P2415Q, Network: Intel I219-LM + Intel I210 OS: Ubuntu 22.04, Kernel: 5.15.0-52-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1080 c: Processor: Intel Core i7-10700T @ 4.50GHz (8 Cores / 16 Threads), Motherboard: Logic Supply RXM-181 (Z01-0002A026 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: 256GB TS256GMTS800, Graphics: Intel UHD 630 CML GT2 30GB (1200MHz), Audio: Realtek ALC233, Monitor: DELL P2415Q, Network: Intel I219-LM + Intel I210 OS: Ubuntu 22.04, Kernel: 5.15.0-52-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1080 FluidX3D 1.4 Test: FP32-FP32 MLUPs/s > Higher Is Better a . 201 |====================================================================== b . 201 |====================================================================== c . 200 |====================================================================== FluidX3D 1.4 Test: FP32-FP16C MLUPs/s > Higher Is Better a . 173 |===================================================================== b . 175 |====================================================================== c . 175 |====================================================================== FluidX3D 1.4 Test: FP32-FP16S MLUPs/s > Higher Is Better a . 357 |================================================================== b . 377 |===================================================================== c . 381 |====================================================================== nekRS 22.0 Input: TurboPipe Periodic FLOP/s > Higher Is Better a . 25130200000 |============================================================= b . 25286500000 |============================================================== c . 25386800000 |============================================================== rav1e 0.6.1 Speed: 1 Frames Per Second > Higher Is Better a . 0.413 |=================================================================== b . 0.417 |==================================================================== c . 0.416 |==================================================================== rav1e 0.6.1 Speed: 5 Frames Per Second > Higher Is Better a . 2.238 |=================================================================== b . 2.269 |==================================================================== c . 2.284 |==================================================================== rav1e 0.6.1 Speed: 6 Frames Per Second > Higher Is Better a . 3.125 |=================================================================== b . 3.163 |==================================================================== c . 3.155 |==================================================================== rav1e 0.6.1 Speed: 10 Frames Per Second > Higher Is Better a . 8.330 |================================================================= b . 8.621 |==================================================================== c . 8.654 |==================================================================== SVT-AV1 1.4 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 1.229 |=================================================================== b . 1.247 |==================================================================== c . 1.247 |==================================================================== SVT-AV1 1.4 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 16.50 |=================================================================== b . 16.69 |==================================================================== c . 16.67 |==================================================================== SVT-AV1 1.4 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 73.51 |================================================================== b . 75.45 |==================================================================== c . 74.67 |=================================================================== SVT-AV1 1.4 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 79.11 |================================================================== b . 80.31 |=================================================================== c . 80.97 |==================================================================== SVT-AV1 1.4 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 4.392 |=================================================================== b . 4.433 |==================================================================== c . 4.446 |==================================================================== SVT-AV1 1.4 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 51.63 |================================================================== b . 53.45 |==================================================================== c . 53.15 |==================================================================== SVT-AV1 1.4 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 323.23 |================================================================== b . 324.32 |================================================================== c . 328.00 |=================================================================== SVT-AV1 1.4 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 356.09 |================================================================== b . 356.33 |================================================================== c . 364.04 |=================================================================== OpenVKL 1.3.1 Benchmark: vklBenchmark ISPC Items / Sec > Higher Is Better a . 93 |====================================================================== b . 94 |======================================================================= c . 94 |======================================================================= OpenVKL 1.3.1 Benchmark: vklBenchmark Scalar Items / Sec > Higher Is Better a . 46 |======================================================================= b . 46 |======================================================================= c . 46 |======================================================================= Stargate Digital Audio Workstation 22.11.5 Sample Rate: 44100 - Buffer Size: 512 Render Ratio > Higher Is Better a . 1.699390 |================================================================ b . 1.717714 |================================================================= c . 1.704004 |================================================================ Stargate Digital Audio Workstation 22.11.5 Sample Rate: 96000 - Buffer Size: 512 Render Ratio > Higher Is Better a . 1.204979 |================================================================= b . 1.206529 |================================================================= c . 1.206909 |================================================================= Stargate Digital Audio Workstation 22.11.5 Sample Rate: 192000 - Buffer Size: 512 Render Ratio > Higher Is Better a . 0.791489 |================================================================= b . 0.794756 |================================================================= c . 0.792159 |================================================================= Stargate Digital Audio Workstation 22.11.5 Sample Rate: 44100 - Buffer Size: 1024 Render Ratio > Higher Is Better a . 1.798704 |================================================================= b . 1.802469 |================================================================= c . 1.802314 |================================================================= Stargate Digital Audio Workstation 22.11.5 Sample Rate: 480000 - Buffer Size: 512 Render Ratio > Higher Is Better a . 1.638868 |================================================================= b . 1.651464 |================================================================= c . 1.649194 |================================================================= Stargate Digital Audio Workstation 22.11.5 Sample Rate: 96000 - Buffer Size: 1024 Render Ratio > Higher Is Better a . 1.293792 |================================================================= b . 1.295920 |================================================================= c . 1.295966 |================================================================= Stargate Digital Audio Workstation 22.11.5 Sample Rate: 192000 - Buffer Size: 1024 Render Ratio > Higher Is Better a . 0.867297 |================================================================= b . 0.870159 |================================================================= c . 0.870579 |================================================================= Stargate Digital Audio Workstation 22.11.5 Sample Rate: 480000 - Buffer Size: 1024 Render Ratio > Higher Is Better a . 1.731054 |================================================================= b . 1.733011 |================================================================= c . 1.737779 |================================================================= Timed Linux Kernel Compilation 6.1 Build: defconfig Seconds < Lower Is Better a . 190.42 |=================================================================== b . 189.63 |=================================================================== c . 189.63 |=================================================================== Timed Linux Kernel Compilation 6.1 Build: allmodconfig Seconds < Lower Is Better a . 2642.39 |================================================================= b . 2642.66 |================================================================= c . 2688.94 |================================================================== oneDNN 3.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.11104 |===== b . 5.03425 |===== c . 67.41070 |================================================================= oneDNN 3.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 10.84 |=============== b . 10.88 |================ c . 47.68 |==================================================================== oneDNN 3.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.37749 |==== b . 2.26968 |==== c . 40.09630 |================================================================= oneDNN 3.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.48501 |=== b . 2.47157 |=== c . 51.50730 |================================================================= oneDNN 3.0 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.0 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 17.14 |=================================================================== b . 17.12 |=================================================================== c . 17.30 |==================================================================== oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 11.69 |=============================================================== b . 12.59 |==================================================================== c . 11.71 |=============================================================== oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 8.30947 |================================================================= b . 8.38301 |================================================================= c . 8.47927 |================================================================== oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 15.50 |==================================================================== b . 15.57 |==================================================================== c . 15.47 |==================================================================== oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3.80985 |================================================================== b . 3.77816 |================================================================= c . 3.78238 |================================================================== oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 5.02536 |================================================================ b . 5.05109 |================================================================= c . 5.15364 |================================================================== oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 6850.49 |================================================================== b . 6861.12 |================================================================== c . 6832.22 |================================================================== oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 3625.06 |================================================================== b . 3632.36 |================================================================== c . 3629.54 |================================================================== oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 6878.39 |================================================================== b . 6904.88 |================================================================== c . 6850.47 |================================================================= oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3622.80 |=============================================================== b . 3783.41 |================================================================== c . 3612.19 |=============================================================== oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 3.99763 |================================================================== b . 4.01087 |================================================================== c . 3.99005 |================================================================== oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 6869.52 |================================================================== b . 6897.51 |================================================================== c . 6842.96 |================================================================= oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3640.28 |================================================================== b . 3657.32 |================================================================== c . 3636.49 |================================================================== oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.23303 |================================================================== b . 2.20570 |================================================================= c . 2.14039 |=============================================================== oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 128 ops/s > Higher Is Better a . 174.4 |==================================================================== b . 175.2 |==================================================================== c . 173.1 |=================================================================== CockroachDB 22.2 Workload: MoVR - Concurrency: 256 ops/s > Higher Is Better a . 174.8 |==================================================================== b . 175.2 |==================================================================== c . 167.0 |================================================================= CockroachDB 22.2 Workload: MoVR - Concurrency: 512 ops/s > Higher Is Better a . 173.9 |==================================================================== b . 172.1 |=================================================================== c . 173.1 |==================================================================== CockroachDB 22.2 Workload: MoVR - Concurrency: 1024 ops/s > Higher Is Better a . 173.6 |==================================================================== b . 171.6 |=================================================================== c . 168.9 |================================================================== CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 128 ops/s > Higher Is Better a . 12318.5 |================================================================= b . 12364.9 |================================================================== c . 12422.9 |================================================================== CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 256 ops/s > Higher Is Better a . 21256.3 |================================================================== b . 21051.4 |================================================================= c . 21050.4 |================================================================= CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 512 ops/s > Higher Is Better a . 22167.5 |================================================================== b . 22053.8 |================================================================== c . 22080.3 |================================================================== CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 128 ops/s > Higher Is Better a . 21728.4 |================================================================== b . 21711.8 |================================================================== c . 21625.8 |================================================================== CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 256 ops/s > Higher Is Better a . 25273.3 |================================================================== b . 25267.5 |================================================================== c . 25133.1 |================================================================== CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 512 ops/s > Higher Is Better a . 25227.2 |================================================================== b . 25164.2 |================================================================== c . 25045.3 |================================================================== CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 128 ops/s > Higher Is Better a . 24369.6 |================================================================== b . 24360.3 |================================================================== c . 24267.8 |================================================================== CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 256 ops/s > Higher Is Better a . 26268.4 |================================================================== b . 26246.9 |================================================================== c . 26188.0 |================================================================== CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 512 ops/s > Higher Is Better a . 25923.7 |================================================================== b . 25936.5 |================================================================== c . 26058.7 |================================================================== CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 128 ops/s > Higher Is Better a . 31139.2 |================================================================== b . 30808.9 |================================================================= c . 30644.9 |================================================================= CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 256 ops/s > Higher Is Better a . 30543.0 |================================================================== b . 30259.7 |================================================================= c . 30253.2 |================================================================= CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 512 ops/s > Higher Is Better a . 29621.9 |================================================================== b . 29633.5 |================================================================== c . 29572.8 |================================================================== CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 21256.4 |================================================================== b . 21125.9 |================================================================== c . 21160.8 |================================================================== CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 23641.5 |================================================================== b . 23487.2 |================================================================== c . 23596.0 |================================================================== CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 24536.7 |================================================================== b . 24424.9 |================================================================== c . 24231.0 |================================================================= CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 28002.8 |================================================================== b . 27948.0 |================================================================== c . 27834.5 |================================================================== Blender 3.4 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 306.09 |=================================================================== b . 305.77 |=================================================================== c . 307.76 |=================================================================== Blender 3.4 Blend File: Classroom - Compute: CPU-Only Seconds < Lower Is Better a . 902.53 |=================================================================== b . 904.16 |=================================================================== c . 905.71 |=================================================================== Blender 3.4 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 417.83 |=================================================================== b . 417.45 |=================================================================== c . 417.82 |=================================================================== Blender 3.4 Blend File: Barbershop - Compute: CPU-Only Seconds < Lower Is Better a . 3260.14 |================================================================== b . 3257.91 |================================================================== c . 3234.94 |================================================================= Blender 3.4 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 1083.60 |================================================================== b . 1086.78 |================================================================== c . 1083.92 |================================================================== OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU FPS > Higher Is Better a . 1.37 |===================================================================== b . 1.37 |===================================================================== c . 1.38 |===================================================================== OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU ms < Lower Is Better a . 2907.95 |================================================================== b . 2900.79 |================================================================== c . 2889.56 |================================================================== OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU FPS > Higher Is Better a . 0.86 |===================================================================== b . 0.86 |===================================================================== c . 0.86 |===================================================================== OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU ms < Lower Is Better a . 4564.30 |================================================================== b . 4567.98 |================================================================== c . 4555.58 |================================================================== OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU FPS > Higher Is Better a . 0.85 |===================================================================== b . 0.85 |===================================================================== c . 0.85 |===================================================================== OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU ms < Lower Is Better a . 4627.40 |================================================================= b . 4705.67 |================================================================== c . 4632.94 |================================================================= OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better a . 105.44 |=================================================================== b . 104.28 |================================================================== c . 104.85 |=================================================================== OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better a . 37.90 |=================================================================== b . 38.33 |==================================================================== c . 38.12 |==================================================================== OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 2.57 |===================================================================== b . 2.57 |===================================================================== c . 2.58 |===================================================================== OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 1552.62 |================================================================== b . 1555.24 |================================================================== c . 1548.90 |================================================================== OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 164.79 |=================================================================== b . 164.14 |=================================================================== c . 164.12 |=================================================================== OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 24.25 |==================================================================== b . 24.35 |==================================================================== c . 24.35 |==================================================================== OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU FPS > Higher Is Better a . 124.59 |=================================================================== b . 124.97 |=================================================================== c . 125.45 |=================================================================== OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU ms < Lower Is Better a . 32.08 |==================================================================== b . 31.98 |==================================================================== c . 31.85 |==================================================================== OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU FPS > Higher Is Better a . 14.90 |==================================================================== b . 14.92 |==================================================================== c . 14.93 |==================================================================== OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU ms < Lower Is Better a . 268.31 |=================================================================== b . 267.76 |=================================================================== c . 267.65 |=================================================================== OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 260.10 |=================================================================== b . 258.24 |=================================================================== c . 257.58 |================================================================== OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 30.73 |=================================================================== b . 30.96 |==================================================================== c . 31.03 |==================================================================== OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU FPS > Higher Is Better a . 181.05 |=================================================================== b . 177.44 |================================================================== c . 174.87 |================================================================= OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU ms < Lower Is Better a . 22.07 |================================================================== b . 22.52 |=================================================================== c . 22.85 |==================================================================== OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better a . 3609.48 |================================================================== b . 3595.44 |================================================================== c . 3620.42 |================================================================== OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better a . 2.20 |===================================================================== b . 2.21 |===================================================================== c . 2.20 |===================================================================== OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU FPS > Higher Is Better a . 3914.10 |================================================================= b . 3925.52 |================================================================= c . 3970.02 |================================================================== OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU ms < Lower Is Better a . 2.03 |===================================================================== b . 2.03 |===================================================================== c . 2.00 |==================================================================== Numenta Anomaly Benchmark 1.1 Detector: KNN CAD Seconds < Lower Is Better a . 364.40 |=================================================================== b . 364.88 |=================================================================== c . 360.59 |================================================================== Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy Seconds < Lower Is Better a . 32.18 |================================================================ b . 32.45 |================================================================ c . 34.34 |==================================================================== Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian Seconds < Lower Is Better a . 18.27 |=================================================================== b . 18.34 |=================================================================== c . 18.65 |==================================================================== Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline Seconds < Lower Is Better a . 200.78 |=================================================================== b . 193.30 |================================================================ c . 201.31 |=================================================================== Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint Seconds < Lower Is Better a . 56.71 |================================================================ b . 60.65 |==================================================================== c . 60.22 |==================================================================== Numenta Anomaly Benchmark 1.1 Detector: Contextual Anomaly Detector OSE Seconds < Lower Is Better a . 69.89 |==================================================================== b . 70.24 |==================================================================== c . 69.63 |=================================================================== Scikit-Learn 1.1.3 Benchmark: MNIST Dataset Seconds < Lower Is Better a . 251.41 |=================================================================== b . 252.30 |=================================================================== c . 251.82 |=================================================================== Scikit-Learn 1.1.3 Benchmark: TSNE MNIST Dataset Seconds < Lower Is Better a . 109.35 |=================================================================== b . 108.38 |================================================================== c . 110.00 |=================================================================== Scikit-Learn 1.1.3 Benchmark: Sparse Random Projections, 100 Iterations Seconds < Lower Is Better a . 3294.52 |================================================================== b . 3294.87 |================================================================== c . 3302.55 |==================================================================