eee

2 x Intel Xeon Gold 5220R testing with a TYAN S7106 (V2.01.B40 BIOS) and ASPEED on Ubuntu 20.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2304025-NE-EEE49872408
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Timed Code Compilation 5 Tests
C/C++ Compiler Tests 9 Tests
CPU Massive 11 Tests
Creator Workloads 9 Tests
Cryptography 2 Tests
Database Test Suite 4 Tests
Encoding 4 Tests
Game Development 3 Tests
HPC - High Performance Computing 3 Tests
Common Kernel Benchmarks 4 Tests
Machine Learning 3 Tests
Multi-Core 15 Tests
Intel oneAPI 2 Tests
Programmer / Developer System Benchmarks 6 Tests
Python Tests 6 Tests
Server 7 Tests
Server CPU Tests 7 Tests
Video Encoding 4 Tests

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April 01 2023
  6 Hours, 3 Minutes
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April 01 2023
  3 Hours, 58 Minutes
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April 01 2023
  6 Hours, 7 Minutes
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eee Suite 1.0.0 System Test suite extracted from eee. pts/apache-3.0.0 -c 100 Concurrent Requests: 100 pts/apache-3.0.0 -c 200 Concurrent Requests: 200 pts/apache-3.0.0 -c 500 Concurrent Requests: 500 pts/apache-3.0.0 -c 1000 Concurrent Requests: 1000 pts/blender-3.5.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: BMW27 - Compute: CPU-Only pts/blender-3.5.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Classroom - Compute: CPU-Only pts/blender-3.5.0 -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-3.5.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Barbershop - Compute: CPU-Only pts/blender-3.5.0 -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/build2-1.2.0 Time To Compile pts/clickhouse-1.2.0 100M Rows Hits Dataset, First Run / Cold Cache pts/clickhouse-1.2.0 100M Rows Hits Dataset, Second Run pts/clickhouse-1.2.0 100M Rows Hits Dataset, Third Run pts/embree-1.4.0 pathtracer -c crown/crown.ecs Binary: Pathtracer - Model: Crown pts/embree-1.4.0 pathtracer_ispc -c crown/crown.ecs Binary: Pathtracer ISPC - Model: Crown pts/embree-1.4.0 pathtracer -c asian_dragon/asian_dragon.ecs Binary: Pathtracer - Model: Asian Dragon pts/embree-1.4.0 pathtracer -c asian_dragon_obj/asian_dragon.ecs Binary: Pathtracer - Model: Asian Dragon Obj pts/embree-1.4.0 pathtracer_ispc -c asian_dragon/asian_dragon.ecs Binary: Pathtracer ISPC - Model: Asian Dragon pts/embree-1.4.0 pathtracer_ispc -c asian_dragon_obj/asian_dragon.ecs Binary: Pathtracer ISPC - Model: Asian Dragon Obj pts/ffmpeg-6.0.0 --encoder=libx264 live Encoder: libx264 - Scenario: Live pts/ffmpeg-6.0.0 --encoder=libx265 live Encoder: libx265 - Scenario: Live pts/ffmpeg-6.0.0 --encoder=libx264 upload Encoder: libx264 - Scenario: Upload pts/ffmpeg-6.0.0 --encoder=libx265 upload Encoder: libx265 - Scenario: Upload pts/ffmpeg-6.0.0 --encoder=libx264 platform Encoder: libx264 - Scenario: Platform pts/ffmpeg-6.0.0 --encoder=libx265 platform Encoder: libx265 - Scenario: Platform pts/ffmpeg-6.0.0 --encoder=libx264 vod Encoder: libx264 - Scenario: Video On Demand pts/ffmpeg-6.0.0 --encoder=libx265 vod Encoder: libx265 - Scenario: Video On Demand pts/draco-1.6.0 -i lion.ply Model: Lion pts/draco-1.6.0 -i church.ply Model: Church Facade pts/john-the-ripper-1.8.0 --format=bcrypt Test: bcrypt pts/john-the-ripper-1.8.0 --format=wpapsk Test: WPA PSK pts/john-the-ripper-1.8.0 --format=bcrypt Test: Blowfish pts/john-the-ripper-1.8.0 --format=HMAC-SHA512 Test: HMAC-SHA512 pts/john-the-ripper-1.8.0 --format=md5crypt Test: MD5 pts/memcached-1.2.0 --ratio=1:5 Set To Get Ratio: 1:5 pts/memcached-1.2.0 --ratio=1:10 Set To Get Ratio: 1:10 pts/memcached-1.2.0 --ratio=1:100 Set To Get Ratio: 1:100 pts/deepsparse-1.3.2 zoo:nlp/document_classification/obert-base/pytorch/huggingface/imdb/base-none --scenario async Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:nlp/document_classification/obert-base/pytorch/huggingface/imdb/base-none --scenario sync Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:nlp/sentiment_analysis/bert-base/pytorch/huggingface/sst2/12layer_pruned90-none --scenario async Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:nlp/sentiment_analysis/bert-base/pytorch/huggingface/sst2/12layer_pruned90-none --scenario sync Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none --scenario async Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none --scenario sync Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario async Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario sync Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario async Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario sync Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario async Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario sync Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:cv/segmentation/yolact-darknet53/pytorch/dbolya/coco/pruned90-none --scenario async Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:cv/segmentation/yolact-darknet53/pytorch/dbolya/coco/pruned90-none --scenario sync Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --scenario async Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --scenario sync Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream pts/deepsparse-1.3.2 zoo:nlp/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario async Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.3.2 zoo:nlp/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario sync Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream pts/nginx-3.0.1 -c 100 Connections: 100 pts/nginx-3.0.1 -c 200 Connections: 200 pts/nginx-3.0.1 -c 500 Connections: 500 pts/nginx-3.0.1 -c 1000 Connections: 1000 pts/onednn-3.1.0 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/onednn-3.1.0 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/onednn-3.1.0 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.1.0 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.1.0 --ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.1.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.1.0 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/onednn-3.1.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/onednn-3.1.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/onednn-3.1.0 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.1.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.1.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.1.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/onednn-3.1.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-3.1.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.1.0 --conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.1.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.1.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.1.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.1.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.1.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/openssl-3.1.0 sha256 Algorithm: SHA256 pts/openssl-3.1.0 sha512 Algorithm: SHA512 pts/openssl-3.1.0 rsa4096 Algorithm: RSA4096 pts/openssl-3.1.0 -evp chacha20 Algorithm: ChaCha20 pts/openssl-3.1.0 -evp aes-128-gcm Algorithm: AES-128-GCM pts/openssl-3.1.0 -evp aes-256-gcm Algorithm: AES-256-GCM pts/openssl-3.1.0 -evp chacha20-poly1305 Algorithm: ChaCha20-Poly1305 pts/pgbench-1.13.0 -s 1 -c 50 -S Scaling Factor: 1 - Clients: 50 - Mode: Read Only pts/pgbench-1.13.0 -s 1 -c 50 -S Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 1 -c 50 Scaling Factor: 1 - Clients: 50 - Mode: Read Write pts/pgbench-1.13.0 -s 1 -c 50 Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 100 -c 50 -S Scaling Factor: 100 - Clients: 50 - Mode: Read Only pts/pgbench-1.13.0 -s 100 -c 50 -S Scaling Factor: 100 - Clients: 50 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 100 -c 50 Scaling Factor: 100 - Clients: 50 - Mode: Read Write pts/pgbench-1.13.0 -s 100 -c 50 Scaling Factor: 100 - Clients: 50 - Mode: Read Write - Average Latency pts/rocksdb-1.5.0 --benchmarks="fillrandom" Test: Random Fill pts/rocksdb-1.5.0 --benchmarks="readrandom" Test: Random Read pts/rocksdb-1.5.0 --benchmarks="updaterandom" Test: Update Random pts/rocksdb-1.5.0 --benchmarks="fillseq" Test: Sequential Fill pts/rocksdb-1.5.0 --benchmarks="fillsync" Test: Random Fill Sync pts/rocksdb-1.5.0 --benchmarks="readwhilewriting" Test: Read While Writing pts/rocksdb-1.5.0 --benchmarks="readrandomwriterandom" Test: Read Random Write Random pts/specfem3d-1.0.0 Mount_StHelens Model: Mount St. Helens pts/specfem3d-1.0.0 layered_halfspace Model: Layered Halfspace pts/specfem3d-1.0.0 tomographic_model Model: Tomographic Model pts/specfem3d-1.0.0 homogeneous_halfspace Model: Homogeneous Halfspace pts/specfem3d-1.0.0 waterlayered_halfspace Model: Water-layered Halfspace pts/svt-av1-2.7.2 --preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 4 - Input: Bosphorus 4K pts/svt-av1-2.7.2 --preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 8 - Input: Bosphorus 4K pts/svt-av1-2.7.2 --preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 12 - Input: Bosphorus 4K pts/svt-av1-2.7.2 --preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 13 - Input: Bosphorus 4K pts/svt-av1-2.7.2 --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-av1-2.7.2 --preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 8 - Input: Bosphorus 1080p pts/svt-av1-2.7.2 --preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 12 - Input: Bosphorus 1080p pts/svt-av1-2.7.2 --preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 13 - Input: Bosphorus 1080p pts/tensorflow-2.1.0 --device cpu --batch_size=16 --model=alexnet Device: CPU - Batch Size: 16 - Model: AlexNet pts/tensorflow-2.1.0 --device cpu --batch_size=32 --model=alexnet Device: CPU - Batch Size: 32 - Model: AlexNet pts/tensorflow-2.1.0 --device cpu --batch_size=64 --model=alexnet Device: CPU - Batch Size: 64 - Model: AlexNet pts/tensorflow-2.1.0 --device cpu --batch_size=256 --model=alexnet Device: CPU - Batch Size: 256 - Model: AlexNet pts/tensorflow-2.1.0 --device cpu --batch_size=512 --model=alexnet Device: CPU - Batch Size: 512 - Model: AlexNet pts/tensorflow-2.1.0 --device cpu --batch_size=16 --model=googlenet Device: CPU - Batch Size: 16 - Model: GoogLeNet pts/tensorflow-2.1.0 --device cpu --batch_size=16 --model=resnet50 Device: CPU - Batch Size: 16 - Model: ResNet-50 pts/tensorflow-2.1.0 --device cpu --batch_size=32 --model=googlenet Device: CPU - Batch Size: 32 - Model: GoogLeNet pts/tensorflow-2.1.0 --device cpu --batch_size=32 --model=resnet50 Device: CPU - Batch Size: 32 - Model: ResNet-50 pts/tensorflow-2.1.0 --device cpu --batch_size=64 --model=googlenet Device: CPU - Batch Size: 64 - Model: GoogLeNet pts/tensorflow-2.1.0 --device cpu --batch_size=64 --model=resnet50 Device: CPU - Batch Size: 64 - Model: ResNet-50 pts/tensorflow-2.1.0 --device cpu --batch_size=256 --model=googlenet Device: CPU - Batch Size: 256 - Model: GoogLeNet pts/tensorflow-2.1.0 --device cpu --batch_size=256 --model=resnet50 Device: CPU - Batch Size: 256 - Model: ResNet-50 pts/tensorflow-2.1.0 --device cpu --batch_size=512 --model=googlenet Device: CPU - Batch Size: 512 - Model: GoogLeNet pts/tensorflow-2.1.0 --device cpu --batch_size=512 --model=resnet50 Device: CPU - Batch Size: 512 - Model: ResNet-50 pts/build-ffmpeg-6.0.0 Time To Compile pts/build-godot-4.0.0 Time To Compile pts/build-llvm-1.5.0 Ninja Build System: Ninja pts/build-llvm-1.5.0 Build System: Unix Makefiles pts/build-nodejs-1.3.0 Time To Compile 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/vvenc-1.1.0 -i Bosphorus_3840x2160.y4m --preset fast Video Input: Bosphorus 4K - Video Preset: Fast pts/vvenc-1.1.0 -i Bosphorus_3840x2160.y4m --preset faster Video Input: Bosphorus 4K - Video Preset: Faster pts/vvenc-1.1.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset fast Video Input: Bosphorus 1080p - Video Preset: Fast pts/vvenc-1.1.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset faster Video Input: Bosphorus 1080p - Video Preset: Faster pts/compress-zstd-1.6.0 -b3 Compression Level: 3 - Compression Speed pts/compress-zstd-1.6.0 -b3 Compression Level: 3 - Decompression Speed pts/compress-zstd-1.6.0 -b8 Compression Level: 8 - Compression Speed pts/compress-zstd-1.6.0 -b8 Compression Level: 8 - Decompression Speed pts/compress-zstd-1.6.0 -b12 Compression Level: 12 - Compression Speed pts/compress-zstd-1.6.0 -b12 Compression Level: 12 - Decompression Speed pts/compress-zstd-1.6.0 -b19 Compression Level: 19 - Compression Speed pts/compress-zstd-1.6.0 -b19 Compression Level: 19 - Decompression Speed pts/compress-zstd-1.6.0 -b3 --long Compression Level: 3, Long Mode - Compression Speed pts/compress-zstd-1.6.0 -b3 --long Compression Level: 3, Long Mode - Decompression Speed pts/compress-zstd-1.6.0 -b8 --long Compression Level: 8, Long Mode - Compression Speed pts/compress-zstd-1.6.0 -b8 --long Compression Level: 8, Long Mode - Decompression Speed pts/compress-zstd-1.6.0 -b19 --long Compression Level: 19, Long Mode - Compression Speed pts/compress-zstd-1.6.0 -b19 --long Compression Level: 19, Long Mode - Decompression Speed