Ubuntu 20.10 Devel Suite
1.0.0
System
Test suite extracted from Ubuntu 20.10 Devel.
pts/cryptopp-1.0.1
b2
Test: Keyed Algorithms
pts/hpcg-1.2.1
pts/cp2k-1.0.0
Fayalite-FIST Data
pts/namd-1.2.1
ATPase Simulation - 327,506 Atoms
pts/dolfyn-1.0.3
Computational Fluid Dynamics
pts/amg-1.0.1
pts/ffte-1.2.1
N=256, 3D Complex FFT Routine
pts/hmmer-1.2.0
Pfam Database Search
pts/lammps-1.2.1
benchmark_20k_atoms.in
Model: 20k Atoms
pts/lammps-1.2.1
in.rhodo
Model: Rhodopsin Protein
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/java-gradle-perf-1.1.0
TEST_REACTOR
Gradle Build: Reactor
pts/dacapobench-1.0.1
h2
Java Test: H2
pts/dacapobench-1.0.1
jython
Java Test: Jython
pts/dacapobench-1.0.1
tradesoap
Java Test: Tradesoap
pts/dacapobench-1.0.1
tradebeans
Java Test: Tradebeans
pts/compress-zstd-1.2.1
-b3
Compression Level: 3
pts/compress-zstd-1.2.1
-b19
Compression Level: 19
pts/crafty-1.4.4
Elapsed Time
pts/node-express-loadtest-1.0.1
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
--ip --batch=inputs/ip/ip_1d --cfg=bf16bf16bf16 --engine=cpu
Harness: IP Batch 1D - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-1.5.0
--ip --batch=inputs/ip/ip_all --cfg=bf16bf16bf16 --engine=cpu
Harness: IP Batch All - Data Type: bf16bf16bf16 - 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
--conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-1.5.0
--deconv --batch=inputs/deconv/deconv_1d --cfg=bf16bf16bf16 --engine=cpu
Harness: Deconvolution Batch deconv_1d - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-1.5.0
--deconv --batch=inputs/deconv/deconv_3d --cfg=bf16bf16bf16 --engine=cpu
Harness: Deconvolution Batch deconv_3d - Data Type: bf16bf16bf16 - 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/onednn-1.5.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
pts/svt-av1-2.2.1
-enc-mode 4 -n 80 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Enc Mode 4 - Input: 1080p
pts/svt-av1-2.2.1
-enc-mode 8 -n 320 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Enc Mode 8 - Input: 1080p
pts/svt-vp9-1.2.2
-tune 1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p
pts/svt-vp9-1.2.2
-tune 0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Tuning: Visual Quality Optimized - Input: Bosphorus 1080p
pts/oidn-1.2.0
-hdr memorial.pfm
Scene: Memorial
pts/openvkl-1.0.0
vklBenchmark
Benchmark: vklBenchmark
pts/coremark-1.0.0
CoreMark Size 666 - Iterations Per Second
pts/himeno-1.3.0
Poisson Pressure Solver
pts/asmfish-1.1.1
1024 Hash Memory, 26 Depth
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/build-linux-kernel-1.10.2
Time To Compile
pts/build-php-1.5.1
Time To Compile
pts/deepspeech-1.0.0
CPU
Acceleration: CPU
pts/openssl-1.11.0
RSA 4096-bit Performance
pts/tjbench-1.1.1
decompression-throughput
Test: Decompression Throughput
pts/leveldb-1.0.0
--benchmarks=readhot --num=1000000
Benchmark: Hot Read
pts/leveldb-1.0.0
--benchmarks=readrandom --num=1000000
Benchmark: Random Read
pts/leveldb-1.0.0
--benchmarks=seekrandom --num=1000000
Benchmark: Seek Random
pts/gromacs-1.4.0
Water Benchmark
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
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/basis-1.0.1
Settings: ETC1S
pts/basis-1.0.1
-uastc -uastc_level 0
Settings: UASTC Level 0
pts/basis-1.0.1
-uastc -uastc_level 2
Settings: UASTC Level 2
pts/basis-1.0.1
-uastc -uastc_level 3
Settings: UASTC Level 3
pts/basis-1.0.1
-uastc -uastc_level 2 -uastc_rdo_q .75
Settings: UASTC Level 2 + RDO Post-Processing
pts/sqlite-speedtest-1.0.0
Timed Time - Size 1,000
system/darktable-1.0.4
bench.SRW output.jpg --core -d perf --disable-opencl
Test: Boat - Acceleration: CPU-only
system/darktable-1.0.4
masskrug.NEF output.jpg --core -d perf --disable-opencl
Test: Masskrug - Acceleration: CPU-only
system/darktable-1.0.4
server-rack.dng output.jpg --core -d perf --disable-opencl
Test: Server Rack - Acceleration: CPU-only
system/darktable-1.0.4
server_room.NEF output.jpg --core -d perf --disable-opencl
Test: Server Room - Acceleration: CPU-only
system/gegl-1.0.0
antialias
Operation: Antialias
system/gegl-1.0.0
tile-glass tile-width=20 tile-height=20
Operation: Tile Glass
system/gegl-1.0.0
wavelet-blur
Operation: Wavelet Blur
system/gegl-1.0.0
color-enhance
Operation: Color Enhance
system/gegl-1.0.0
rotate-on-center degrees=90
Operation: Rotate 90 Degrees
system/rawtherapee-1.0.1
Total Benchmark Time
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 200
Model: GoogleNet - Acceleration: CPU - Iterations: 200
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: inception-v3
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 - 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
-1
Target: CPU - Model: shufflenet-v2
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/plaidml-1.0.4
--no-fp16 --no-train vgg16 CPU
FP16: No - Mode: Inference - Network: VGG16 - Device: CPU
pts/plaidml-1.0.4
--no-fp16 --no-train vgg19 CPU
FP16: No - Mode: Inference - Network: VGG19 - Device: CPU
pts/plaidml-1.0.4
--no-fp16 --no-train imdb_lstm CPU
FP16: No - Mode: Inference - Network: IMDB LSTM - Device: CPU
pts/plaidml-1.0.4
--no-fp16 --no-train mobilenet CPU
FP16: No - Mode: Inference - Network: Mobilenet - Device: CPU
pts/plaidml-1.0.4
--no-fp16 --no-train resnet50 CPU
FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU
pts/plaidml-1.0.4
--no-fp16 --no-train densenet201 CPU
FP16: No - Mode: Inference - Network: DenseNet 201 - Device: CPU
pts/plaidml-1.0.4
--no-fp16 --no-train inception_v3 CPU
FP16: No - Mode: Inference - Network: Inception V3 - Device: CPU
pts/rocksdb-1.0.2
--benchmarks="fillrandom"
Test: Random Fill
pts/rocksdb-1.0.2
--benchmarks="readrandom"
Test: Random Read
pts/rocksdb-1.0.2
--benchmarks="fillseq"
Test: Sequential Fill
pts/rocksdb-1.0.2
--benchmarks="readwhilewriting"
Test: Read While Writing
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 ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE
Blend File: Classroom - 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/blender-1.8.0
-b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE
Blend File: Barbershop - Compute: CPU-Only
pts/blender-1.8.0
-b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE
Blend File: Pabellon Barcelona - Compute: CPU-Only
pts/pybench-1.1.3
Total For Average Test Times
pts/pyperformance-1.0.2
go
Benchmark: go
pts/pyperformance-1.0.2
2to3
Benchmark: 2to3
pts/pyperformance-1.0.2
chaos
Benchmark: chaos
pts/pyperformance-1.0.2
float
Benchmark: float
pts/pyperformance-1.0.2
nbody
Benchmark: nbody
pts/pyperformance-1.0.2
pathlib
Benchmark: pathlib
pts/pyperformance-1.0.2
raytrace
Benchmark: raytrace
pts/pyperformance-1.0.2
json_loads
Benchmark: json_loads
pts/pyperformance-1.0.2
crypto_pyaes
Benchmark: crypto_pyaes
pts/pyperformance-1.0.2
regex_compile
Benchmark: regex_compile
pts/pyperformance-1.0.2
python_startup
Benchmark: python_startup
pts/pyperformance-1.0.2
django_template
Benchmark: django_template
pts/pyperformance-1.0.2
pickle_pure_python
Benchmark: pickle_pure_python
pts/hint-1.0.3
FLOAT
Test: FLOAT
pts/appleseed-1.0.1
emily.appleseed
Scene: Emily
pts/appleseed-1.0.1
disney_material_1.appleseed
Scene: Disney Material
pts/appleseed-1.0.1
material_tester_ambient_occlusion.appleseed
Scene: Material Tester
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/phpbench-1.1.5
PHP Benchmark Suite
pts/git-1.1.0
Time To Complete Common Git Commands
pts/kripke-1.0.0
pts/brl-cad-1.1.0
VGR Performance Metric
system/gimp-1.1.2
resize
Test: resize
system/gimp-1.1.2
rotate
Test: rotate
system/gimp-1.1.2
auto-levels
Test: auto-levels
system/gimp-1.1.2
unsharp-mask
Test: unsharp-mask
pts/mnn-1.0.1
Model: mobilenet-v1-1.0
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