tiger christrmas Intel Core i7-1165G7 testing with a Dell 0GG9PT (3.11.0 BIOS) and Intel Xe TGL GT2 3GB on Ubuntu 21.10 via the Phoronix Test Suite. a: Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.11.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 3GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 OS: Ubuntu 21.10, Kernel: 5.13.0-52-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 21.2.2, OpenCL: OpenCL 3.0, Vulkan: 1.2.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1200 b: Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.11.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 3GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 OS: Ubuntu 21.10, Kernel: 5.13.0-52-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 21.2.2, OpenCL: OpenCL 3.0, Vulkan: 1.2.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1200 c: Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.11.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 3GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 OS: Ubuntu 21.10, Kernel: 5.13.0-52-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 21.2.2, OpenCL: OpenCL 3.0, Vulkan: 1.2.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1200 FluidX3D 1.4 Test: FP32-FP32 MLUPs/s > Higher Is Better a . 354 |====================================================================== b . 353 |====================================================================== c . 352 |====================================================================== FluidX3D 1.4 Test: FP32-FP16C MLUPs/s > Higher Is Better a . 617 |====================================================================== b . 619 |====================================================================== c . 613 |===================================================================== FluidX3D 1.4 Test: FP32-FP16S MLUPs/s > Higher Is Better a . 674 |====================================================================== b . 674 |====================================================================== c . 673 |====================================================================== OpenVKL 1.3.1 Benchmark: vklBenchmark ISPC Items / Sec > Higher Is Better a . 85 |======================================================================= b . 83 |===================================================================== c . 84 |====================================================================== OpenVKL 1.3.1 Benchmark: vklBenchmark Scalar Items / Sec > Higher Is Better a . 32 |======================================================================= b . 31 |===================================================================== c . 31 |===================================================================== oneDNN 3.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 7.90117 |=============================================================== b . 7.83017 |============================================================== c . 8.29020 |================================================================== oneDNN 3.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.82337 |================================================================== b . 5.82751 |================================================================== c . 5.78771 |================================================================== oneDNN 3.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.61858 |================================================================ b . 1.66244 |================================================================== c . 1.59253 |=============================================================== oneDNN 3.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.26772 |================================================================== b . 2.24367 |================================================================= c . 2.26345 |================================================================== oneDNN 3.0 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 19.56 |==================================================================== b . 19.68 |==================================================================== c . 18.78 |================================================================= oneDNN 3.0 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 6.27663 |================================================================== b . 6.16745 |================================================================= c . 6.23449 |================================================================== oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 8.94631 |================================================================= b . 9.07376 |================================================================== c . 8.77594 |================================================================ oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 11.81 |==================================================================== b . 11.87 |==================================================================== c . 11.39 |================================================================= oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 10.85 |==================================================================== b . 10.83 |==================================================================== c . 10.41 |================================================================= oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 8.19741 |================================================================== b . 8.01075 |================================================================ c . 7.87596 |=============================================================== oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.16245 |================================================================== b . 2.17719 |================================================================== c . 2.15107 |================================================================= oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.53818 |================================================================ b . 2.61272 |================================================================== c . 2.53415 |================================================================ oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 7247.05 |================================================================ b . 7050.25 |=============================================================== c . 7444.00 |================================================================== oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 3841.61 |================================================================== b . 3690.15 |=============================================================== c . 3792.72 |================================================================= oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 7481.76 |================================================================== b . 7304.32 |================================================================ c . 7403.27 |================================================================= oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 41.39 |============================================================== b . 41.86 |============================================================== c . 45.70 |==================================================================== oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 45.85 |================================================================== b . 47.11 |==================================================================== c . 45.26 |================================================================= oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 40.05 |=================================================================== b . 40.50 |==================================================================== c . 38.28 |================================================================ oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3809.20 |================================================================== b . 3729.76 |================================================================ c . 3832.92 |================================================================== oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 3.55613 |================================================================== b . 3.53667 |================================================================== c . 3.54678 |================================================================== oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 7483.36 |================================================================== b . 7492.16 |================================================================== c . 7502.88 |================================================================== oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3829.54 |================================================================== b . 3759.52 |================================================================= c . 3840.61 |================================================================== oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.42268 |================================================================= b . 1.42052 |================================================================= c . 1.43733 |================================================================== oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 8.66355 |=============================================================== b . 9.07093 |================================================================== c . 8.56415 |============================================================== CockroachDB 22.2 Workload: MoVR - Concurrency: 128 ops/s > Higher Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 256 ops/s > Higher Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 512 ops/s > Higher Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 1024 ops/s > Higher Is Better CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 128 ops/s > Higher Is Better a . 16035.1 |================================================================== b . 10347.1 |=========================================== c . 10276.6 |========================================== CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 256 ops/s > Higher Is Better a . 14329.3 |============================================================ b . 15092.2 |=============================================================== c . 15748.0 |================================================================== CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 512 ops/s > Higher Is Better a . 15619.7 |================================================================== b . 14915.5 |=============================================================== c . 15444.8 |================================================================= CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 128 ops/s > Higher Is Better a . 15097.5 |============================================================= b . 16230.1 |================================================================== c . 14302.4 |========================================================== CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 256 ops/s > Higher Is Better a . 17250.2 |================================================================== b . 16457.3 |=============================================================== c . 17022.7 |================================================================= CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 512 ops/s > Higher Is Better a . 15393.2 |========================================================== b . 15557.4 |=========================================================== c . 17401.2 |================================================================== CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 128 ops/s > Higher Is Better a . 17788.9 |================================================================ b . 18334.7 |================================================================== c . 16174.6 |========================================================== CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 256 ops/s > Higher Is Better a . 17805.3 |=============================================================== b . 16540.3 |=========================================================== c . 18639.0 |================================================================== CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 512 ops/s > Higher Is Better a . 17337.3 |============================================================== b . 18445.8 |================================================================== c . 17455.4 |============================================================== CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 128 ops/s > Higher Is Better a . 22544.5 |================================================================== b . 21846.2 |================================================================ c . 21954.4 |================================================================ CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 256 ops/s > Higher Is Better a . 21902.9 |================================================================= b . 21093.0 |=============================================================== c . 22070.5 |================================================================== CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 512 ops/s > Higher Is Better a . 20479.8 |================================================================= b . 20291.7 |================================================================ c . 20768.3 |================================================================== CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 14276.6 |================================================================== b . 13523.0 |=============================================================== c . 14007.8 |================================================================= CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 16024.2 |=============================================================== b . 16834.3 |================================================================== c . 16320.2 |================================================================ CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 16513.5 |============================================================== b . 16445.4 |============================================================== c . 17463.1 |================================================================== CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 1024 ops/s > Higher Is Better a . 19697.7 |================================================================= b . 19853.0 |================================================================== c . 19959.0 |================================================================== OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU FPS > Higher Is Better a . 1.10 |===================================================================== b . 1.10 |===================================================================== c . 1.08 |==================================================================== OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU ms < Lower Is Better a . 3638.45 |================================================================= b . 3643.49 |================================================================= c . 3709.36 |================================================================== OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU FPS > Higher Is Better a . 0.63 |==================================================================== b . 0.64 |===================================================================== c . 0.63 |==================================================================== OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU ms < Lower Is Better a . 6273.54 |================================================================== b . 6248.19 |================================================================= c . 6305.72 |================================================================== OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU FPS > Higher Is Better a . 0.68 |===================================================================== b . 0.68 |===================================================================== c . 0.66 |=================================================================== OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU ms < Lower Is Better a . 5826.84 |================================================================ b . 5887.78 |================================================================= c . 5983.48 |================================================================== OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better a . 82.25 |==================================================================== b . 82.06 |==================================================================== c . 82.00 |==================================================================== OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better a . 48.61 |==================================================================== b . 48.72 |==================================================================== c . 48.76 |==================================================================== OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 4.21 |===================================================================== b . 4.21 |===================================================================== c . 4.02 |================================================================== OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 946.91 |================================================================ b . 948.20 |================================================================ c . 991.24 |=================================================================== OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 226.85 |=================================================================== b . 224.65 |================================================================== c . 225.20 |=================================================================== OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 17.61 |=================================================================== b . 17.79 |==================================================================== c . 17.75 |==================================================================== OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU FPS > Higher Is Better a . 110.69 |=================================================================== b . 110.18 |=================================================================== c . 108.14 |================================================================= OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU ms < Lower Is Better a . 36.12 |================================================================== b . 36.28 |=================================================================== c . 36.97 |==================================================================== OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU FPS > Higher Is Better a . 13.56 |=================================================================== b . 13.54 |=================================================================== c . 13.67 |==================================================================== OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU ms < Lower Is Better a . 294.52 |=================================================================== b . 295.25 |=================================================================== c . 292.07 |================================================================== OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 411.78 |=================================================================== b . 412.26 |=================================================================== c . 399.31 |================================================================= OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 9.70 |================================================================== b . 9.68 |================================================================== c . 10.00 |==================================================================== OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU FPS > Higher Is Better a . 154.26 |=================================================================== b . 150.89 |================================================================== c . 152.23 |================================================================== OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU ms < Lower Is Better a . 25.91 |=================================================================== b . 26.49 |==================================================================== c . 26.25 |=================================================================== OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better a . 2967.18 |================================================================== b . 2809.48 |============================================================== c . 2802.51 |============================================================== OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better a . 1.33 |================================================================= b . 1.41 |===================================================================== c . 1.41 |===================================================================== OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU FPS > Higher Is Better a . 3202.10 |============================================================ b . 3515.84 |================================================================== c . 3485.19 |================================================================= OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU ms < Lower Is Better a . 1.24 |===================================================================== b . 1.13 |=============================================================== c . 1.14 |===============================================================