dfgg

Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus ICL GT2 16GB on Ubuntu 23.04 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 2312179-NE-DFGG1028382
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December 16 2023
  14 Hours, 49 Minutes
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December 17 2023
  14 Hours, 49 Minutes
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dfgg Suite 1.0.0 System Test suite extracted from dfgg. pts/webp2-1.2.1 -q 100 -effort 9 Encode Settings: Quality 100, Lossless Compression pts/xmrig-1.2.0 -a gr --bench=1M Variant: GhostRider - Hash Count: 1M pts/webp2-1.2.1 -q 95 -effort 7 Encode Settings: Quality 95, Compression Effort 7 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q22 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q21 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q20 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q19 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q18 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q17 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q16 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q15 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q14 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q13 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q12 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q11 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q10 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q09 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q08 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q07 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q06 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q05 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q04 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q03 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q02 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Q01 pts/spark-tpch-1.0.0 -s 10 Scale Factor: 10 - Geometric Mean Of All Queries pts/webp2-1.2.1 -q 75 -effort 7 Encode Settings: Quality 75, Compression Effort 7 pts/xmrig-1.2.0 -a cn-heavy/0 --bench=1M Variant: CryptoNight-Heavy - Hash Count: 1M pts/xmrig-1.2.0 -a cn/upx2 --bench=1M Variant: CryptoNight-Femto UPX2 - Hash Count: 1M pts/xmrig-1.2.0 --bench=1M Variant: Monero - Hash Count: 1M pts/xmrig-1.2.0 -a kawpow --bench=1M Variant: KawPow - Hash Count: 1M pts/xmrig-1.2.0 -a rx/wow --bench=1M Variant: Wownero - Hash Count: 1M pts/lczero-1.7.0 -b eigen Backend: Eigen pts/lczero-1.7.0 -b blas Backend: BLAS pts/svt-av1-2.11.1 --preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 4 - Input: Bosphorus 4K system/openssl-1.2.0 sha256 Algorithm: SHA256 system/openssl-1.2.0 -evp aes-128-gcm Algorithm: AES-128-GCM system/openssl-1.2.0 -evp chacha20-poly1305 Algorithm: ChaCha20-Poly1305 system/openssl-1.2.0 -evp aes-256-gcm Algorithm: AES-256-GCM system/openssl-1.2.0 -evp chacha20 Algorithm: ChaCha20 system/openssl-1.2.0 sha512 Algorithm: SHA512 pts/scylladb-1.0.0 WRITE Test: Writes pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q22 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q21 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q20 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q19 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q18 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q17 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q16 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q15 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q14 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q13 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q12 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q11 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q10 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q09 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q08 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q07 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q06 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q05 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q04 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q03 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q02 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Q01 pts/spark-tpch-1.0.0 -s 1 Scale Factor: 1 - Geometric Mean Of All Queries pts/svt-av1-2.11.1 --preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 8 - Input: Bosphorus 4K pts/deepsparse-1.6.0 zoo:nlp/question_answering/obert-large/pytorch/huggingface/squad/base-none --input_shapes='[1,128]' --scenario async Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.6.0 zoo:nlp/question_answering/obert-large/pytorch/huggingface/squad/base-none --input_shapes='[1,128]' --scenario sync Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream system/openssl-1.2.0 rsa4096 Algorithm: RSA4096 pts/deepsparse-1.6.0 zoo:nlp/question_answering/obert-large/pytorch/huggingface/squad/pruned97_quant-none --input_shapes='[1,128]' --scenario async Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.6.0 zoo:nlp/sentiment_analysis/oberta-base/pytorch/huggingface/sst2/pruned90_quant-none --input_shapes='[1,128]' --scenario async Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.6.0 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-1.6.0 zoo:nlp/sentiment_analysis/oberta-base/pytorch/huggingface/sst2/pruned90_quant-none --input_shapes='[1,128]' --scenario sync Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream pts/deepsparse-1.6.0 zoo:nlp/question_answering/obert-large/pytorch/huggingface/squad/pruned97_quant-none --input_shapes='[1,128]' --scenario sync Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream pts/deepsparse-1.6.0 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-1.6.0 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-1.6.0 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-1.6.0 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/deepsparse-1.6.0 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/svt-av1-2.11.1 --preset 4 -n 160 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 4 - Input: Bosphorus 1080p pts/deepsparse-1.6.0 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-1.6.0 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-1.6.0 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario async Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.6.0 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/pruned95_uniform_quant-none --scenario async Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.6.0 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario async Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.6.0 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/pruned85-none --scenario async Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.6.0 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-1.6.0 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario sync Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream pts/deepsparse-1.6.0 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/pruned85-none --scenario sync Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream pts/deepsparse-1.6.0 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-1.6.0 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario sync Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream pts/deepsparse-1.6.0 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/pruned95_uniform_quant-none --scenario sync Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream pts/webp2-1.2.1 -q 100 -effort 5 Encode Settings: Quality 100, Compression Effort 5 pts/java-scimark2-1.2.0 TEST_COMPOSITE Computational Test: Composite pts/svt-av1-2.11.1 --preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 8 - Input: Bosphorus 1080p pts/svt-av1-2.11.1 --preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 12 - Input: Bosphorus 4K pts/svt-av1-2.11.1 --preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 13 - Input: Bosphorus 4K pts/webp2-1.2.1 Encode Settings: Default pts/svt-av1-2.11.1 --preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 12 - Input: Bosphorus 1080p pts/svt-av1-2.11.1 --preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 13 - Input: Bosphorus 1080p pts/java-scimark2-1.2.0 TEST_SOR Computational Test: Jacobi Successive Over-Relaxation pts/java-scimark2-1.2.0 TEST_DENSE Computational Test: Dense LU Matrix Factorization pts/java-scimark2-1.2.0 TEST_SPARSE Computational Test: Sparse Matrix Multiply pts/java-scimark2-1.2.0 TEST_FFT Computational Test: Fast Fourier Transform pts/java-scimark2-1.2.0 TEST_MONTE Computational Test: Monte Carlo