icelake pop os
Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.4.0 BIOS) and Intel Xe TGL GT2 3GB on Pop 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2206073-NE-ICELAKEPO77.
Etcpak
Benchmark: Multi-Threaded - Configuration: ETC2
Etcpak
Benchmark: Single-Threaded - Configuration: ETC2
simdjson
Throughput Test: Kostya
simdjson
Throughput Test: TopTweet
simdjson
Throughput Test: LargeRandom
simdjson
Throughput Test: PartialTweets
simdjson
Throughput Test: DistinctUserID
Renaissance
Test: Scala Dotty
Renaissance
Test: Random Forest
Renaissance
Test: ALS Movie Lens
Renaissance
Test: Apache Spark ALS
Renaissance
Test: Apache Spark Bayes
Renaissance
Test: Savina Reactors.IO
Renaissance
Test: Apache Spark PageRank
Renaissance
Test: Finagle HTTP Requests
Renaissance
Test: In-Memory Database Shootout
Renaissance
Test: Akka Unbalanced Cobwebbed Tree
Renaissance
Test: Genetic Algorithm Using Jenetics + Futures
Nettle
Test: aes256
Nettle
Test: chacha
Nettle
Test: sha512
Nettle
Test: poly1305-aes
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 10 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 10 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
SVT-HEVC
Tuning: 7 - Input: Bosphorus 4K
SVT-HEVC
Tuning: 10 - Input: Bosphorus 4K
SVT-HEVC
Tuning: 7 - Input: Bosphorus 1080p
SVT-HEVC
Tuning: 10 - Input: Bosphorus 1080p
SVT-VP9
Tuning: VMAF Optimized - Input: Bosphorus 4K
SVT-VP9
Tuning: VMAF Optimized - Input: Bosphorus 1080p
SVT-VP9
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 4K
SVT-VP9
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p
SVT-VP9
Tuning: Visual Quality Optimized - Input: Bosphorus 4K
SVT-VP9
Tuning: Visual Quality Optimized - Input: Bosphorus 1080p
x264
Video Input: Bosphorus 4K
x264
Video Input: Bosphorus 1080p
OSPray
Benchmark: particle_volume/ao/real_time
OSPray
Benchmark: particle_volume/scivis/real_time
OSPray
Benchmark: particle_volume/pathtracer/real_time
OSPray
Benchmark: gravity_spheres_volume/dim_512/ao/real_time
OSPray
Benchmark: gravity_spheres_volume/dim_512/scivis/real_time
OSPray
Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time
libavif avifenc
Encoder Speed: 6
libavif avifenc
Encoder Speed: 6, Lossless
libavif avifenc
Encoder Speed: 10, Lossless
Timed MPlayer Compilation
Time To Compile
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
OSPray Studio
Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer
OSPray Studio
Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer
OSPray Studio
Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer
OSPray Studio
Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer
OSPray Studio
Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer
OSPray Studio
Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer
WebP2 Image Encode
Encode Settings: Default
WebP2 Image Encode
Encode Settings: Quality 75, Compression Effort 7
WebP2 Image Encode
Encode Settings: Quality 95, Compression Effort 7
WebP2 Image Encode
Encode Settings: Quality 100, Compression Effort 5
WebP2 Image Encode
Encode Settings: Quality 100, Lossless Compression
GROMACS
Implementation: MPI CPU - Input: water_GMX50_bare
TensorFlow Lite
Model: SqueezeNet
TensorFlow Lite
Model: Inception V4
TensorFlow Lite
Model: NASNet Mobile
TensorFlow Lite
Model: Mobilenet Float
TensorFlow Lite
Model: Mobilenet Quant
TensorFlow Lite
Model: Inception ResNet V2
Facebook RocksDB
Test: Random Read
Facebook RocksDB
Test: Update Random
Facebook RocksDB
Test: Read While Writing
Facebook RocksDB
Test: Read Random Write Random
Java JMH
Throughput
ONNX Runtime
Model: GPT-2 - Device: CPU - Executor: Standard
ONNX Runtime
Model: yolov4 - Device: CPU - Executor: Standard
ONNX Runtime
Model: bertsquad-12 - Device: CPU - Executor: Standard
ONNX Runtime
Model: fcn-resnet101-11 - Device: CPU - Executor: Standard
ONNX Runtime
Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard
ONNX Runtime
Model: super-resolution-10 - Device: CPU - Executor: Standard
InfluxDB
Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
InfluxDB
Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
InfluxDB
Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
Phoronix Test Suite v10.8.5