sfsd Suite
1.0.0
System
Test suite extracted from sfsd.
pts/unpack-linux-1.2.0
linux-5.19.tar.xz
pts/unvanquished-1.7.0
+set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/high.cfg
Resolution: 1920 x 1080 - Effects Quality: High
pts/unvanquished-1.7.0
+set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/ultra.cfg
Resolution: 1920 x 1080 - Effects Quality: Ultra
pts/unvanquished-1.7.0
+set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/medium.cfg
Resolution: 1920 x 1080 - Effects Quality: Medium
pts/blosc-1.2.0
blosclz shuffle
Test: blosclz shuffle
pts/blosc-1.2.0
blosclz bitshuffle
Test: blosclz bitshuffle
pts/lammps-1.4.0
in.rhodo
Model: Rhodopsin Protein
pts/graphics-magick-2.1.0
-swirl 90
Operation: Swirl
pts/graphics-magick-2.1.0
-rotate 90
Operation: Rotate
pts/graphics-magick-2.1.0
-sharpen 0x2.0
Operation: Sharpen
pts/graphics-magick-2.1.0
-enhance
Operation: Enhanced
pts/graphics-magick-2.1.0
-resize 50%
Operation: Resizing
pts/graphics-magick-2.1.0
-operator all Noise-Gaussian 30%
Operation: Noise-Gaussian
pts/graphics-magick-2.1.0
-colorspace HWB
Operation: HWB Color Space
pts/svt-av1-2.6.0
--preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 4 - Input: Bosphorus 4K
pts/svt-av1-2.6.0
--preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 8 - Input: Bosphorus 4K
pts/svt-av1-2.6.0
--preset 10 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 10 - Input: Bosphorus 4K
pts/svt-av1-2.6.0
--preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 12 - Input: Bosphorus 4K
pts/svt-av1-2.6.0
--preset 4 -n 160 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
pts/svt-av1-2.6.0
--preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
pts/svt-av1-2.6.0
--preset 10 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 10 - Input: Bosphorus 1080p
pts/svt-av1-2.6.0
--preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
pts/compress-7zip-1.10.0
Test: Compression Rating
pts/compress-7zip-1.10.0
Test: Decompression Rating
pts/build-nodejs-1.2.0
Time To Compile
pts/build-php-1.6.0
Time To Compile
pts/build-python-1.0.0
Build Configuration: Default
pts/build-python-1.0.0
--enable-optimizations --with-lto
Build Configuration: Released Build, PGO + LTO Optimized
pts/primesieve-1.9.0
1e12
Length: 1e12
pts/primesieve-1.9.0
1e13
Length: 1e13
pts/build-erlang-1.2.0
Time To Compile
pts/build-wasmer-1.2.0
Time To Compile
pts/aircrack-ng-1.3.0
pts/node-web-tooling-1.0.1
pts/clickhouse-1.1.0
100M Rows Web Analytics Dataset, First Run / Cold Cache
pts/clickhouse-1.1.0
100M Rows Web Analytics Dataset, Second Run
pts/clickhouse-1.1.0
100M Rows Web Analytics Dataset, Third Run
pts/spark-1.0.0
-r 1000000 -p 100
Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 1000000 -p 100
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 1000000 -p 100
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 1000000 -p 100
Row Count: 1000000 - Partitions: 100 - Group By Test Time
pts/spark-1.0.0
-r 1000000 -p 100
Row Count: 1000000 - Partitions: 100 - Repartition Test Time
pts/spark-1.0.0
-r 1000000 -p 100
Row Count: 1000000 - Partitions: 100 - Inner Join Test Time
pts/spark-1.0.0
-r 1000000 -p 100
Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 1000000 -p 500
Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 1000000 -p 500
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 1000000 -p 500
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 1000000 -p 500
Row Count: 1000000 - Partitions: 500 - Group By Test Time
pts/spark-1.0.0
-r 1000000 -p 500
Row Count: 1000000 - Partitions: 500 - Repartition Test Time
pts/spark-1.0.0
-r 1000000 -p 500
Row Count: 1000000 - Partitions: 500 - Inner Join Test Time
pts/spark-1.0.0
-r 1000000 -p 500
Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 1000000 -p 1000
Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 1000000 -p 1000
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 1000000 -p 1000
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 1000000 -p 1000
Row Count: 1000000 - Partitions: 1000 - Group By Test Time
pts/spark-1.0.0
-r 1000000 -p 1000
Row Count: 1000000 - Partitions: 1000 - Repartition Test Time
pts/spark-1.0.0
-r 1000000 -p 1000
Row Count: 1000000 - Partitions: 1000 - Inner Join Test Time
pts/spark-1.0.0
-r 1000000 -p 1000
Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 1000000 -p 2000
Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 1000000 -p 2000
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 1000000 -p 2000
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 1000000 -p 2000
Row Count: 1000000 - Partitions: 2000 - Group By Test Time
pts/spark-1.0.0
-r 1000000 -p 2000
Row Count: 1000000 - Partitions: 2000 - Repartition Test Time
pts/spark-1.0.0
-r 1000000 -p 2000
Row Count: 1000000 - Partitions: 2000 - Inner Join Test Time
pts/spark-1.0.0
-r 1000000 -p 2000
Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 100
Row Count: 10000000 - Partitions: 100 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 10000000 -p 100
Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 10000000 -p 100
Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 10000000 -p 100
Row Count: 10000000 - Partitions: 100 - Group By Test Time
pts/spark-1.0.0
-r 10000000 -p 100
Row Count: 10000000 - Partitions: 100 - Repartition Test Time
pts/spark-1.0.0
-r 10000000 -p 100
Row Count: 10000000 - Partitions: 100 - Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 100
Row Count: 10000000 - Partitions: 100 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 500
Row Count: 10000000 - Partitions: 500 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 10000000 -p 500
Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 10000000 -p 500
Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 10000000 -p 500
Row Count: 10000000 - Partitions: 500 - Group By Test Time
pts/spark-1.0.0
-r 10000000 -p 500
Row Count: 10000000 - Partitions: 500 - Repartition Test Time
pts/spark-1.0.0
-r 10000000 -p 500
Row Count: 10000000 - Partitions: 500 - Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 500
Row Count: 10000000 - Partitions: 500 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 100
Row Count: 20000000 - Partitions: 100 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 20000000 -p 100
Row Count: 20000000 - Partitions: 100 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 20000000 -p 100
Row Count: 20000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 20000000 -p 100
Row Count: 20000000 - Partitions: 100 - Group By Test Time
pts/spark-1.0.0
-r 20000000 -p 100
Row Count: 20000000 - Partitions: 100 - Repartition Test Time
pts/spark-1.0.0
-r 20000000 -p 100
Row Count: 20000000 - Partitions: 100 - Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 100
Row Count: 20000000 - Partitions: 100 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 500
Row Count: 20000000 - Partitions: 500 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 20000000 -p 500
Row Count: 20000000 - Partitions: 500 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 20000000 -p 500
Row Count: 20000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 20000000 -p 500
Row Count: 20000000 - Partitions: 500 - Group By Test Time
pts/spark-1.0.0
-r 20000000 -p 500
Row Count: 20000000 - Partitions: 500 - Repartition Test Time
pts/spark-1.0.0
-r 20000000 -p 500
Row Count: 20000000 - Partitions: 500 - Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 500
Row Count: 20000000 - Partitions: 500 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 100
Row Count: 40000000 - Partitions: 100 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 40000000 -p 100
Row Count: 40000000 - Partitions: 100 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 40000000 -p 100
Row Count: 40000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 40000000 -p 100
Row Count: 40000000 - Partitions: 100 - Group By Test Time
pts/spark-1.0.0
-r 40000000 -p 100
Row Count: 40000000 - Partitions: 100 - Repartition Test Time
pts/spark-1.0.0
-r 40000000 -p 100
Row Count: 40000000 - Partitions: 100 - Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 100
Row Count: 40000000 - Partitions: 100 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 500
Row Count: 40000000 - Partitions: 500 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 40000000 -p 500
Row Count: 40000000 - Partitions: 500 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 40000000 -p 500
Row Count: 40000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 40000000 -p 500
Row Count: 40000000 - Partitions: 500 - Group By Test Time
pts/spark-1.0.0
-r 40000000 -p 500
Row Count: 40000000 - Partitions: 500 - Repartition Test Time
pts/spark-1.0.0
-r 40000000 -p 500
Row Count: 40000000 - Partitions: 500 - Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 500
Row Count: 40000000 - Partitions: 500 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 1000
Row Count: 10000000 - Partitions: 1000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 10000000 -p 1000
Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 10000000 -p 1000
Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 10000000 -p 1000
Row Count: 10000000 - Partitions: 1000 - Group By Test Time
pts/spark-1.0.0
-r 10000000 -p 1000
Row Count: 10000000 - Partitions: 1000 - Repartition Test Time
pts/spark-1.0.0
-r 10000000 -p 1000
Row Count: 10000000 - Partitions: 1000 - Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 1000
Row Count: 10000000 - Partitions: 1000 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 2000
Row Count: 10000000 - Partitions: 2000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 10000000 -p 2000
Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 10000000 -p 2000
Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 10000000 -p 2000
Row Count: 10000000 - Partitions: 2000 - Group By Test Time
pts/spark-1.0.0
-r 10000000 -p 2000
Row Count: 10000000 - Partitions: 2000 - Repartition Test Time
pts/spark-1.0.0
-r 10000000 -p 2000
Row Count: 10000000 - Partitions: 2000 - Inner Join Test Time
pts/spark-1.0.0
-r 10000000 -p 2000
Row Count: 10000000 - Partitions: 2000 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 1000
Row Count: 20000000 - Partitions: 1000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 20000000 -p 1000
Row Count: 20000000 - Partitions: 1000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 20000000 -p 1000
Row Count: 20000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 20000000 -p 1000
Row Count: 20000000 - Partitions: 1000 - Group By Test Time
pts/spark-1.0.0
-r 20000000 -p 1000
Row Count: 20000000 - Partitions: 1000 - Repartition Test Time
pts/spark-1.0.0
-r 20000000 -p 1000
Row Count: 20000000 - Partitions: 1000 - Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 1000
Row Count: 20000000 - Partitions: 1000 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 2000
Row Count: 20000000 - Partitions: 2000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 20000000 -p 2000
Row Count: 20000000 - Partitions: 2000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 20000000 -p 2000
Row Count: 20000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 20000000 -p 2000
Row Count: 20000000 - Partitions: 2000 - Group By Test Time
pts/spark-1.0.0
-r 20000000 -p 2000
Row Count: 20000000 - Partitions: 2000 - Repartition Test Time
pts/spark-1.0.0
-r 20000000 -p 2000
Row Count: 20000000 - Partitions: 2000 - Inner Join Test Time
pts/spark-1.0.0
-r 20000000 -p 2000
Row Count: 20000000 - Partitions: 2000 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 1000
Row Count: 40000000 - Partitions: 1000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 40000000 -p 1000
Row Count: 40000000 - Partitions: 1000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 40000000 -p 1000
Row Count: 40000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 40000000 -p 1000
Row Count: 40000000 - Partitions: 1000 - Group By Test Time
pts/spark-1.0.0
-r 40000000 -p 1000
Row Count: 40000000 - Partitions: 1000 - Repartition Test Time
pts/spark-1.0.0
-r 40000000 -p 1000
Row Count: 40000000 - Partitions: 1000 - Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 1000
Row Count: 40000000 - Partitions: 1000 - Broadcast Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 2000
Row Count: 40000000 - Partitions: 2000 - SHA-512 Benchmark Time
pts/spark-1.0.0
-r 40000000 -p 2000
Row Count: 40000000 - Partitions: 2000 - Calculate Pi Benchmark
pts/spark-1.0.0
-r 40000000 -p 2000
Row Count: 40000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
pts/spark-1.0.0
-r 40000000 -p 2000
Row Count: 40000000 - Partitions: 2000 - Group By Test Time
pts/spark-1.0.0
-r 40000000 -p 2000
Row Count: 40000000 - Partitions: 2000 - Repartition Test Time
pts/spark-1.0.0
-r 40000000 -p 2000
Row Count: 40000000 - Partitions: 2000 - Inner Join Test Time
pts/spark-1.0.0
-r 40000000 -p 2000
Row Count: 40000000 - Partitions: 2000 - Broadcast Inner Join Test Time
pts/dragonflydb-1.0.0
-c 50 --ratio=1:1
Clients: 50 - Set To Get Ratio: 1:1
pts/dragonflydb-1.0.0
-c 50 --ratio=1:5
Clients: 50 - Set To Get Ratio: 1:5
pts/dragonflydb-1.0.0
-c 50 --ratio=5:1
Clients: 50 - Set To Get Ratio: 5:1
pts/dragonflydb-1.0.0
-c 200 --ratio=1:1
Clients: 200 - Set To Get Ratio: 1:1
pts/dragonflydb-1.0.0
-c 200 --ratio=1:5
Clients: 200 - Set To Get Ratio: 1:5
pts/dragonflydb-1.0.0
-c 200 --ratio=5:1
Clients: 200 - Set To Get Ratio: 5:1
pts/redis-1.4.0
-t get -c 50
Test: GET - Parallel Connections: 50
pts/redis-1.4.0
-t set -c 50
Test: SET - Parallel Connections: 50
pts/redis-1.4.0
-t get -c 500
Test: GET - Parallel Connections: 500
pts/redis-1.4.0
-t lpop -c 50
Test: LPOP - Parallel Connections: 50
pts/redis-1.4.0
-t sadd -c 50
Test: SADD - Parallel Connections: 50
pts/redis-1.4.0
-t set -c 500
Test: SET - Parallel Connections: 500
pts/redis-1.4.0
-t get -c 1000
Test: GET - Parallel Connections: 1000
pts/redis-1.4.0
-t lpop -c 500
Test: LPOP - Parallel Connections: 500
pts/redis-1.4.0
-t lpush -c 50
Test: LPUSH - Parallel Connections: 50
pts/redis-1.4.0
-t sadd -c 500
Test: SADD - Parallel Connections: 500
pts/redis-1.4.0
-t set -c 1000
Test: SET - Parallel Connections: 1000
pts/redis-1.4.0
-t lpop -c 1000
Test: LPOP - Parallel Connections: 1000
pts/redis-1.4.0
-t lpush -c 500
Test: LPUSH - Parallel Connections: 500
pts/redis-1.4.0
-t sadd -c 1000
Test: SADD - Parallel Connections: 1000
pts/redis-1.4.0
-t lpush -c 1000
Test: LPUSH - Parallel Connections: 1000
pts/astcenc-1.4.0
-fast -repeats 120
Preset: Fast
pts/astcenc-1.4.0
-medium -repeats 20
Preset: Medium
pts/astcenc-1.4.0
-thorough -repeats 10
Preset: Thorough
pts/astcenc-1.4.0
-exhaustive -repeats 2
Preset: Exhaustive
system/inkscape-1.0.1
Operation: SVG Files To PNG
pts/memtier-benchmark-1.4.0
-P redis -c 50 --ratio=1:1
Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:1
pts/memtier-benchmark-1.4.0
-P redis -c 50 --ratio=1:5
Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5
pts/memtier-benchmark-1.4.0
-P redis -c 50 --ratio=5:1
Protocol: Redis - Clients: 50 - Set To Get Ratio: 5:1
pts/memtier-benchmark-1.4.0
-P redis -c 100 --ratio=1:1
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:1
pts/memtier-benchmark-1.4.0
-P redis -c 100 --ratio=1:5
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5
pts/memtier-benchmark-1.4.0
-P redis -c 100 --ratio=5:1
Protocol: Redis - Clients: 100 - Set To Get Ratio: 5:1
pts/memtier-benchmark-1.4.0
-P redis -c 50 --ratio=1:10
Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10
pts/memtier-benchmark-1.4.0
-P redis -c 500 --ratio=1:1
Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:1
pts/memtier-benchmark-1.4.0
-P redis -c 500 --ratio=1:5
Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5
pts/memtier-benchmark-1.4.0
-P redis -c 500 --ratio=5:1
Protocol: Redis - Clients: 500 - Set To Get Ratio: 5:1
pts/memtier-benchmark-1.4.0
-P redis -c 100 --ratio=1:10
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10
pts/memtier-benchmark-1.4.0
-P redis -c 500 --ratio=1:10
Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10
pts/mnn-2.1.0
Model: nasnet
pts/mnn-2.1.0
Model: mobilenetV3
pts/mnn-2.1.0
Model: squeezenetv1.1
pts/mnn-2.1.0
Model: resnet-v2-50
pts/mnn-2.1.0
Model: SqueezeNetV1.0
pts/mnn-2.1.0
Model: MobileNetV2_224
pts/mnn-2.1.0
Model: mobilenet-v1-1.0
pts/mnn-2.1.0
Model: inception-v3
pts/ncnn-1.4.0
-1
Target: CPU - Model: mobilenet
pts/ncnn-1.4.0
-1
Target: CPU-v2-v2 - Model: mobilenet-v2
pts/ncnn-1.4.0
-1
Target: CPU-v3-v3 - Model: mobilenet-v3
pts/ncnn-1.4.0
-1
Target: CPU - Model: shufflenet-v2
pts/ncnn-1.4.0
-1
Target: CPU - Model: mnasnet
pts/ncnn-1.4.0
-1
Target: CPU - Model: efficientnet-b0
pts/ncnn-1.4.0
-1
Target: CPU - Model: blazeface
pts/ncnn-1.4.0
-1
Target: CPU - Model: googlenet
pts/ncnn-1.4.0
-1
Target: CPU - Model: vgg16
pts/ncnn-1.4.0
-1
Target: CPU - Model: resnet18
pts/ncnn-1.4.0
-1
Target: CPU - Model: alexnet
pts/ncnn-1.4.0
-1
Target: CPU - Model: resnet50
pts/ncnn-1.4.0
-1
Target: CPU - Model: yolov4-tiny
pts/ncnn-1.4.0
-1
Target: CPU - Model: squeezenet_ssd
pts/ncnn-1.4.0
-1
Target: CPU - Model: regnety_400m
pts/ncnn-1.4.0
-1
Target: CPU - Model: vision_transformer
pts/ncnn-1.4.0
-1
Target: CPU - Model: FastestDet
pts/openvino-1.1.0
-m models/intel/face-detection-0206/FP16/face-detection-0206.xml -d CPU
Model: Face Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/person-detection-0106/FP16/person-detection-0106.xml -d CPU
Model: Person Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/person-detection-0106/FP32/person-detection-0106.xml -d CPU
Model: Person Detection FP32 - Device: CPU
pts/openvino-1.1.0
-m models/intel/vehicle-detection-0202/FP16/vehicle-detection-0202.xml -d CPU
Model: Vehicle Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/face-detection-0206/FP16-INT8/face-detection-0206.xml -d CPU
Model: Face Detection FP16-INT8 - Device: CPU
pts/openvino-1.1.0
-m models/intel/vehicle-detection-0202/FP16-INT8/vehicle-detection-0202.xml -d CPU
Model: Vehicle Detection FP16-INT8 - Device: CPU
pts/openvino-1.1.0
-m models/intel/weld-porosity-detection-0001/FP16/weld-porosity-detection-0001.xml -d CPU
Model: Weld Porosity Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/machine-translation-nar-en-de-0002/FP16/machine-translation-nar-en-de-0002.xml -d CPU
Model: Machine Translation EN To DE FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/weld-porosity-detection-0001/FP16-INT8/weld-porosity-detection-0001.xml -d CPU
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
pts/openvino-1.1.0
-m models/intel/person-vehicle-bike-detection-2004/FP16/person-vehicle-bike-detection-2004.xml -d CPU
Model: Person Vehicle Bike Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013.xml -d CPU
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/age-gender-recognition-retail-0013/FP16-INT8/age-gender-recognition-retail-0013.xml -d CPU
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
pts/natron-1.1.0
Natron_2.3.12_Spaceship/Natron_project/Spaceship_Natron.ntp
Input: Spaceship
pts/ai-benchmark-1.0.2
Device Inference Score
pts/ai-benchmark-1.0.2
Device Training Score
pts/ai-benchmark-1.0.2
Device AI Score