3800xt 2022 Suite
1.0.0
System
Test suite extracted from 3800xt 2022.
pts/kvazaar-1.2.0
-i Bosphorus_3840x2160.y4m --preset slow
Video Input: Bosphorus 4K - Video Preset: Slow
pts/kvazaar-1.2.0
-i Bosphorus_3840x2160.y4m --preset medium
Video Input: Bosphorus 4K - Video Preset: Medium
pts/kvazaar-1.2.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset slow
Video Input: Bosphorus 1080p - Video Preset: Slow
pts/kvazaar-1.2.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset medium
Video Input: Bosphorus 1080p - Video Preset: Medium
pts/kvazaar-1.2.0
-i Bosphorus_3840x2160.y4m --preset veryfast
Video Input: Bosphorus 4K - Video Preset: Very Fast
pts/kvazaar-1.2.0
-i Bosphorus_3840x2160.y4m --preset superfast
Video Input: Bosphorus 4K - Video Preset: Super Fast
pts/kvazaar-1.2.0
-i Bosphorus_3840x2160.y4m --preset ultrafast
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
pts/kvazaar-1.2.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset veryfast
Video Input: Bosphorus 1080p - Video Preset: Very Fast
pts/kvazaar-1.2.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset superfast
Video Input: Bosphorus 1080p - Video Preset: Super Fast
pts/kvazaar-1.2.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset ultrafast
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
pts/svt-av1-2.7.0
--preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 4 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 8 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 12 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 13 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--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-av1-2.7.0
--preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
pts/svt-av1-2.7.0
--preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
pts/svt-av1-2.7.0
--preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
pts/uvg266-1.0.0
-i Bosphorus_3840x2160.y4m --preset slow
Video Input: Bosphorus 4K - Video Preset: Slow
pts/uvg266-1.0.0
-i Bosphorus_3840x2160.y4m --preset medium
Video Input: Bosphorus 4K - Video Preset: Medium
pts/uvg266-1.0.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset slow
Video Input: Bosphorus 1080p - Video Preset: Slow
pts/uvg266-1.0.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset medium
Video Input: Bosphorus 1080p - Video Preset: Medium
pts/uvg266-1.0.0
-i Bosphorus_3840x2160.y4m --preset veryfast
Video Input: Bosphorus 4K - Video Preset: Very Fast
pts/uvg266-1.0.0
-i Bosphorus_3840x2160.y4m --preset superfast
Video Input: Bosphorus 4K - Video Preset: Super Fast
pts/uvg266-1.0.0
-i Bosphorus_3840x2160.y4m --preset ultrafast
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
pts/uvg266-1.0.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset veryfast
Video Input: Bosphorus 1080p - Video Preset: Very Fast
pts/uvg266-1.0.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset superfast
Video Input: Bosphorus 1080p - Video Preset: Super Fast
pts/uvg266-1.0.0
-i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset ultrafast
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
pts/openvkl-1.3.0
vklBenchmark --benchmark_filter=ispc
Benchmark: vklBenchmark ISPC
pts/openvkl-1.3.0
vklBenchmark --benchmark_filter=scalar
Benchmark: vklBenchmark Scalar
pts/build-linux-kernel-1.15.0
defconfig
Build: defconfig
pts/build-linux-kernel-1.15.0
allmodconfig
Build: allmodconfig
pts/onednn-3.0.0
--ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
pts/onednn-3.0.0
--ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
pts/onednn-3.0.0
--conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
pts/onednn-3.0.0
--deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-3.0.0
--deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-3.0.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
pts/onednn-3.0.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
pts/onednn-3.0.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
pts/onednn-3.0.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-3.0.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-3.0.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
pts/cockroach-1.0.2
movr --concurrency 128
Workload: MoVR - Concurrency: 128
pts/cockroach-1.0.2
kv --ramp 10s --read-percent 10 --concurrency 128
Workload: KV, 10% Reads - Concurrency: 128
pts/cockroach-1.0.2
kv --ramp 10s --read-percent 50 --concurrency 128
Workload: KV, 50% Reads - Concurrency: 128
pts/cockroach-1.0.2
kv --ramp 10s --read-percent 60 --concurrency 128
Workload: KV, 60% Reads - Concurrency: 128
pts/cockroach-1.0.2
kv --ramp 10s --read-percent 95 --concurrency 128
Workload: KV, 95% Reads - Concurrency: 128
pts/blender-3.4.0
-b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: BMW27 - Compute: CPU-Only
pts/blender-3.4.0
-b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: Fishy Cat - Compute: CPU-Only
pts/blender-3.4.0
-b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: Pabellon Barcelona - Compute: CPU-Only
pts/openvino-1.2.0
-m models/intel/face-detection-0206/FP16/face-detection-0206.xml -d CPU
Model: Face Detection FP16 - Device: CPU
pts/openvino-1.2.0
-m models/intel/person-detection-0106/FP16/person-detection-0106.xml -d CPU
Model: Person Detection FP16 - Device: CPU
pts/openvino-1.2.0
-m models/intel/person-detection-0106/FP32/person-detection-0106.xml -d CPU
Model: Person Detection FP32 - Device: CPU
pts/openvino-1.2.0
-m models/intel/vehicle-detection-0202/FP16/vehicle-detection-0202.xml -d CPU
Model: Vehicle Detection FP16 - Device: CPU
pts/openvino-1.2.0
-m models/intel/face-detection-0206/FP16-INT8/face-detection-0206.xml -d CPU
Model: Face Detection FP16-INT8 - Device: CPU
pts/openvino-1.2.0
-m models/intel/vehicle-detection-0202/FP16-INT8/vehicle-detection-0202.xml -d CPU
Model: Vehicle Detection FP16-INT8 - Device: CPU
pts/openvino-1.2.0
-m models/intel/weld-porosity-detection-0001/FP16/weld-porosity-detection-0001.xml -d CPU
Model: Weld Porosity Detection FP16 - Device: CPU
pts/openvino-1.2.0
-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-1.2.0
-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-1.2.0
-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-1.2.0
-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-1.2.0
-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/numenta-nab-1.1.1
-d knncad
Detector: KNN CAD
pts/numenta-nab-1.1.1
-d relativeEntropy
Detector: Relative Entropy
pts/numenta-nab-1.1.1
-d windowedGaussian
Detector: Windowed Gaussian
pts/numenta-nab-1.1.1
-d earthgeckoSkyline
Detector: Earthgecko Skyline
pts/numenta-nab-1.1.1
-d bayesChangePt
Detector: Bayesian Changepoint
pts/numenta-nab-1.1.1
-d contextOSE
Detector: Contextual Anomaly Detector OSE
pts/brl-cad-1.4.0
VGR Performance Metric