Xeon E3-1245 v5 Ubuntu Linux 5.4 Suite
1.0.0
System
Test suite extracted from Xeon E3-1245 v5 Ubuntu Linux 5.4.
pts/ai-benchmark-1.0.0
Device Inference Score
pts/ai-benchmark-1.0.0
Device Training Score
pts/ai-benchmark-1.0.0
Device AI Score
pts/aom-av1-2.1.2
--cpu-used=0 --limit=10
Encoder Mode: Speed 0 Two-Pass
pts/aom-av1-2.1.2
--cpu-used=4 --limit=40
Encoder Mode: Speed 4 Two-Pass
pts/aom-av1-2.1.2
--cpu-used=6 --rt
Encoder Mode: Speed 6 Realtime
pts/aom-av1-2.1.2
--cpu-used=6 --limit=80
Encoder Mode: Speed 6 Two-Pass
pts/aom-av1-2.1.2
--cpu-used=8 --rt
Encoder Mode: Speed 8 Realtime
pts/couchdb-1.0.1
100 1000 24
Bulk Size: 100 - Inserts: 1000 - Rounds: 24
pts/astcenc-1.0.0
-fast
Preset: Fast
pts/astcenc-1.0.0
-medium
Preset: Medium
pts/astcenc-1.0.0
-thorough
Preset: Thorough
pts/astcenc-1.0.0
-exhaustive
Preset: Exhaustive
pts/blender-1.8.0
-b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE
Blend File: BMW27 - Compute: CPU-Only
pts/blender-1.8.0
-b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE
Blend File: Fishy Cat - Compute: CPU-Only
pts/byte-1.2.2
TEST_DHRY2
Computational Test: Dhrystone 2
pts/caffe-1.5.0
--model=../models/bvlc_alexnet/deploy.prototxt -iterations 100
Model: AlexNet - Acceleration: CPU - Iterations: 100
pts/caffe-1.5.0
--model=../models/bvlc_alexnet/deploy.prototxt -iterations 200
Model: AlexNet - Acceleration: CPU - Iterations: 200
pts/caffe-1.5.0
--model=../models/bvlc_googlenet/deploy.prototxt -iterations 100
Model: GoogleNet - Acceleration: CPU - Iterations: 100
pts/caffe-1.5.0
--model=../models/bvlc_googlenet/deploy.prototxt -iterations 200
Model: GoogleNet - Acceleration: CPU - Iterations: 200
pts/crafty-1.4.4
Elapsed Time
pts/deepspeech-1.0.0
CPU
Acceleration: CPU
pts/dolfyn-1.0.3
Computational Fluid Dynamics
pts/ecp-candle-1.0.1
P1B2
Benchmark: P1B2
pts/ecp-candle-1.0.1
P3B1
Benchmark: P3B1
pts/ecp-candle-1.0.1
P3B2
Benchmark: P3B2
pts/espeak-1.6.0
Text-To-Speech Synthesis
pts/ffte-1.2.1
N=256, 3D Complex FFT Routine
pts/glmark2-1.2.0
-s 1920x1080
Resolution: 1920 x 1080
pts/glmark2-1.2.0
-s 3840x2160
Resolution: 3840 x 2160
pts/gpaw-1.0.0
carbon-nanotube
Input: Carbon Nanotube
pts/gromacs-1.4.0
Water Benchmark
pts/hint-1.0.3
FLOAT
Test: FLOAT
system/hugin-1.0.0
Panorama Photo Assistant + Stitching Time
pts/incompact3d-1.0.0
examples/Cylinder/input.i3d
Input: Cylinder
pts/influxdb-1.0.0
-c 4 -b 10000 -t 2,5000,1 -p 10000
Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
pts/influxdb-1.0.0
-c 64 -b 10000 -t 2,5000,1 -p 10000
Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
pts/influxdb-1.0.0
-c 1024 -b 10000 -t 2,5000,1 -p 10000
Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
pts/keydb-1.2.0
pts/kripke-1.0.0
pts/lammps-1.2.1
in.rhodo
Model: Rhodopsin Protein
pts/lczero-1.5.1
-b blas
Backend: BLAS
pts/lczero-1.5.1
-b eigen
Backend: Eigen
pts/avifenc-1.0.0
-s 0
Encoder Speed: 0
pts/avifenc-1.0.0
-s 2
Encoder Speed: 2
pts/avifenc-1.0.0
-s 8
Encoder Speed: 8
pts/avifenc-1.0.0
-s 10
Encoder Speed: 10
pts/libraw-1.0.0
Post-Processing Benchmark
pts/mlpack-1.0.2
SCIKIT_ICA
Benchmark: scikit_ica
pts/mlpack-1.0.2
SCIKIT_QDA
Benchmark: scikit_qda
pts/mlpack-1.0.2
SCIKIT_SVM
Benchmark: scikit_svm
pts/mlpack-1.0.2
SCIKIT_LINEARRIDGEREGRESSION
Benchmark: scikit_linearridgeregression
pts/mnn-1.0.1
Model: SqueezeNetV1.0
pts/mnn-1.0.1
Model: resnet-v2-50
pts/mnn-1.0.1
Model: MobileNetV2_224
pts/mnn-1.0.1
Model: mobilenet-v1-1.0
pts/mnn-1.0.1
Model: inception-v3
pts/montage-1.0.0
Mosaic of M17, K band, 1.5 deg x 1.5 deg
pts/mocassin-1.0.0
Input: Dust 2D tau100.0
system/mpv-1.0.1
bbb_sunflower_2160p_30fps_normal.mp4 --hwdec=no
Video Input: Big Buck Bunny Sunflower 4K - Decode: Software Only
system/mpv-1.0.1
bbb_sunflower_1080p_30fps_normal.mp4 --hwdec=no
Video Input: Big Buck Bunny Sunflower 1080p - Decode: Software Only
pts/namd-1.2.1
ATPase Simulation - 327,506 Atoms
pts/ncnn-1.0.3
-1
Target: CPU - Model: squeezenet
pts/ncnn-1.0.3
-1
Target: CPU - Model: mobilenet
pts/ncnn-1.0.3
-1
Target: CPU-v2-v2 - Model: mobilenet-v2
pts/ncnn-1.0.3
-1
Target: CPU-v3-v3 - Model: mobilenet-v3
pts/ncnn-1.0.3
-1
Target: CPU - Model: shufflenet-v2
pts/ncnn-1.0.3
-1
Target: CPU - Model: mnasnet
pts/ncnn-1.0.3
-1
Target: CPU - Model: efficientnet-b0
pts/ncnn-1.0.3
-1
Target: CPU - Model: blazeface
pts/ncnn-1.0.3
-1
Target: CPU - Model: googlenet
pts/ncnn-1.0.3
-1
Target: CPU - Model: vgg16
pts/ncnn-1.0.3
-1
Target: CPU - Model: resnet18
pts/ncnn-1.0.3
-1
Target: CPU - Model: alexnet
pts/ncnn-1.0.3
-1
Target: CPU - Model: resnet50
pts/ncnn-1.0.3
-1
Target: CPU - Model: yolov4-tiny
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: squeezenet
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: mobilenet
pts/ncnn-1.0.3
Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2
pts/ncnn-1.0.3
Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: shufflenet-v2
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: mnasnet
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: efficientnet-b0
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: blazeface
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: googlenet
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: vgg16
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: resnet18
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: alexnet
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: resnet50
pts/ncnn-1.0.3
Target: Vulkan GPU - Model: yolov4-tiny
system/ocrmypdf-1.0.0
Processing 60 Page PDF Document
pts/onednn-1.5.0
--ip --batch=inputs/ip/ip_1d --cfg=f32 --engine=cpu
Harness: IP Batch 1D - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--ip --batch=inputs/ip/ip_all --cfg=f32 --engine=cpu
Harness: IP Batch All - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--ip --batch=inputs/ip/ip_1d --cfg=u8s8f32 --engine=cpu
Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU
pts/onednn-1.5.0
--ip --batch=inputs/ip/ip_all --cfg=u8s8f32 --engine=cpu
Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU
pts/onednn-1.5.0
--conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--deconv --batch=inputs/deconv/deconv_1d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--deconv --batch=inputs/deconv/deconv_3d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
pts/onednn-1.5.0
--deconv --batch=inputs/deconv/deconv_1d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-1.5.0
--deconv --batch=inputs/deconv/deconv_3d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-1.5.0
--rnn --batch=inputs/rnn/rnn_training --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--rnn --batch=inputs/rnn/rnn_inference --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
pts/onednn-1.5.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
pts/realsr-ncnn-1.0.0
-s 4
Scale: 4x - TAA: No
pts/rnnoise-1.0.2
pts/rodinia-1.3.1
OMP_LAVAMD
Test: OpenMP LavaMD
pts/rodinia-1.3.1
OMP_HOTSPOT3D
Test: OpenMP HotSpot3D
pts/rodinia-1.3.1
OMP_LEUKOCYTE
Test: OpenMP Leukocyte
pts/rodinia-1.3.1
OMP_CFD
Test: OpenMP CFD Solver
pts/rodinia-1.3.1
OMP_STREAMCLUSTER
Test: OpenMP Streamcluster
pts/system-decompress-gzip-1.1.1
pts/tensorflow-lite-1.0.0
--graph=squeezenet.tflite
Model: SqueezeNet
pts/tensorflow-lite-1.0.0
--graph=inception_v4.tflite
Model: Inception V4
pts/tensorflow-lite-1.0.0
--graph=nasnet_mobile.tflite
Model: NASNet Mobile
pts/tensorflow-lite-1.0.0
--graph=mobilenet_v1_1.0_224.tflite
Model: Mobilenet Float
pts/tensorflow-lite-1.0.0
--graph=mobilenet_v1_1.0_224_quant.tflite
Model: Mobilenet Quant
pts/tensorflow-lite-1.0.0
--graph=inception_resnet_v2.tflite
Model: Inception ResNet V2
system/tesseract-ocr-1.0.1
Time To OCR 7 Images
pts/build-apache-1.6.1
Time To Compile
pts/build-gdb-1.0.1
Time To Compile
pts/hmmer-1.2.0
Pfam Database Search
pts/build-linux-kernel-1.10.2
Time To Compile
pts/build-llvm-1.2.1
Time To Compile
pts/mafft-1.6.1
Multiple Sequence Alignment - LSU RNA
pts/tnn-1.0.0
-dt NAIVE -mp ../benchmark/benchmark-model/mobilenet_v2.tnnproto
Target: CPU - Model: MobileNet v2
pts/tnn-1.0.0
-dt NAIVE -mp ../benchmark/benchmark-model/squeezenet_v1.1.tnnproto
Target: CPU - Model: SqueezeNet v1.1
pts/tscp-1.2.2
AI Chess Performance
pts/vkfft-1.0.0
pts/webp-1.0.0
Encode Settings: Default
pts/webp-1.0.0
-q 100
Encode Settings: Quality 100
pts/webp-1.0.0
-q 100 -lossless
Encode Settings: Quality 100, Lossless
pts/webp-1.0.0
-q 100 -m 6
Encode Settings: Quality 100, Highest Compression
pts/webp-1.0.0
-q 100 -lossless -m 6
Encode Settings: Quality 100, Lossless, Highest Compression
pts/compress-xz-1.1.0
Compressing ubuntu-16.04.3-server-i386.img, Compression Level 9
pts/compress-zstd-1.2.1
-b3
Compression Level: 3
pts/compress-zstd-1.2.1
-b19
Compression Level: 19