2023 ryzen 5

AMD Ryzen 5 4500U testing with a LENOVO LNVNB161216 (EECN20WW BIOS) and AMD Renoir 512MB on Pop 22.04 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 2302063-NE-2023RYZEN21
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February 05 2023
  7 Hours, 14 Minutes
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February 06 2023
  7 Hours, 10 Minutes
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February 06 2023
  7 Hours, 17 Minutes
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  7 Hours, 13 Minutes

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2023 ryzen 5 Suite 1.0.0 System Test suite extracted from 2023 ryzen 5. pts/spark-1.0.1 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time pts/spark-1.0.1 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark pts/spark-1.0.1 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe pts/spark-1.0.1 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Group By Test Time pts/spark-1.0.1 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Repartition Test Time pts/spark-1.0.1 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Inner Join Test Time pts/spark-1.0.1 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time pts/spark-1.0.1 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time pts/spark-1.0.1 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark pts/spark-1.0.1 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe pts/spark-1.0.1 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Group By Test Time pts/spark-1.0.1 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Repartition Test Time pts/spark-1.0.1 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Inner Join Test Time pts/spark-1.0.1 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time pts/spark-1.0.1 -r 1000000 -p 1000 Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Time pts/spark-1.0.1 -r 1000000 -p 1000 Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark pts/spark-1.0.1 -r 1000000 -p 1000 Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe pts/spark-1.0.1 -r 1000000 -p 1000 Row Count: 1000000 - Partitions: 1000 - Group By Test Time pts/spark-1.0.1 -r 1000000 -p 1000 Row Count: 1000000 - Partitions: 1000 - Repartition Test Time pts/spark-1.0.1 -r 1000000 -p 1000 Row Count: 1000000 - Partitions: 1000 - Inner Join Test Time pts/spark-1.0.1 -r 1000000 -p 1000 Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Time pts/spark-1.0.1 -r 1000000 -p 2000 Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Time pts/spark-1.0.1 -r 1000000 -p 2000 Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark pts/spark-1.0.1 -r 1000000 -p 2000 Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe pts/spark-1.0.1 -r 1000000 -p 2000 Row Count: 1000000 - Partitions: 2000 - Group By Test Time pts/spark-1.0.1 -r 1000000 -p 2000 Row Count: 1000000 - Partitions: 2000 - Repartition Test Time pts/spark-1.0.1 -r 1000000 -p 2000 Row Count: 1000000 - Partitions: 2000 - Inner Join Test Time pts/spark-1.0.1 -r 1000000 -p 2000 Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Time 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/etlegacy-1.3.0 +set r_customwidth 1920 +set r_customheight 1080 Resolution: 1920 x 1080 pts/memcached-1.1.0 --ratio=1:5 Set To Get Ratio: 1:5 pts/memcached-1.1.0 --ratio=1:10 Set To Get Ratio: 1:10 pts/memcached-1.1.0 --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/openems-1.0.0 pyems/examples/coupler.py Test: pyEMS Coupler pts/openems-1.0.0 openEMS-Project/openEMS/python/Tutorials/MSL_NotchFilter.py Test: openEMS MSL_NotchFilter pts/pgbench-1.13.0 -s 1 -c 1 -S Scaling Factor: 1 - Clients: 1 - Mode: Read Only pts/pgbench-1.13.0 -s 1 -c 1 -S Scaling Factor: 1 - Clients: 1 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 1 -c 1 Scaling Factor: 1 - Clients: 1 - Mode: Read Write pts/pgbench-1.13.0 -s 1 -c 1 Scaling Factor: 1 - Clients: 1 - Mode: Read Write - Average Latency 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 100 -S Scaling Factor: 1 - Clients: 100 - Mode: Read Only pts/pgbench-1.13.0 -s 1 -c 100 -S Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 1 -c 250 -S Scaling Factor: 1 - Clients: 250 - Mode: Read Only pts/pgbench-1.13.0 -s 1 -c 250 -S Scaling Factor: 1 - Clients: 250 - 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 1 -c 500 -S Scaling Factor: 1 - Clients: 500 - Mode: Read Only pts/pgbench-1.13.0 -s 1 -c 500 -S Scaling Factor: 1 - Clients: 500 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 1 -c 800 -S Scaling Factor: 1 - Clients: 800 - Mode: Read Only pts/pgbench-1.13.0 -s 1 -c 800 -S Scaling Factor: 1 - Clients: 800 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 100 -c 1 -S Scaling Factor: 100 - Clients: 1 - Mode: Read Only pts/pgbench-1.13.0 -s 100 -c 1 -S Scaling Factor: 100 - Clients: 1 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 1 -c 100 Scaling Factor: 1 - Clients: 100 - Mode: Read Write pts/pgbench-1.13.0 -s 1 -c 100 Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 1 -c 250 Scaling Factor: 1 - Clients: 250 - Mode: Read Write pts/pgbench-1.13.0 -s 1 -c 250 Scaling Factor: 1 - Clients: 250 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 1 -c 500 Scaling Factor: 1 - Clients: 500 - Mode: Read Write pts/pgbench-1.13.0 -s 1 -c 500 Scaling Factor: 1 - Clients: 500 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 1 -c 800 Scaling Factor: 1 - Clients: 800 - Mode: Read Write pts/pgbench-1.13.0 -s 1 -c 800 Scaling Factor: 1 - Clients: 800 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 100 -c 1 Scaling Factor: 100 - Clients: 1 - Mode: Read Write pts/pgbench-1.13.0 -s 100 -c 1 Scaling Factor: 100 - Clients: 1 - 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 100 -S Scaling Factor: 100 - Clients: 100 - Mode: Read Only pts/pgbench-1.13.0 -s 100 -c 100 -S Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 100 -c 250 -S Scaling Factor: 100 - Clients: 250 - Mode: Read Only pts/pgbench-1.13.0 -s 100 -c 250 -S Scaling Factor: 100 - Clients: 250 - 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/pgbench-1.13.0 -s 100 -c 500 -S Scaling Factor: 100 - Clients: 500 - Mode: Read Only pts/pgbench-1.13.0 -s 100 -c 500 -S Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 100 -c 800 -S Scaling Factor: 100 - Clients: 800 - Mode: Read Only pts/pgbench-1.13.0 -s 100 -c 800 -S Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency pts/pgbench-1.13.0 -s 100 -c 100 Scaling Factor: 100 - Clients: 100 - Mode: Read Write pts/pgbench-1.13.0 -s 100 -c 100 Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 100 -c 250 Scaling Factor: 100 - Clients: 250 - Mode: Read Write pts/pgbench-1.13.0 -s 100 -c 250 Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 100 -c 500 Scaling Factor: 100 - Clients: 500 - Mode: Read Write pts/pgbench-1.13.0 -s 100 -c 500 Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency pts/pgbench-1.13.0 -s 100 -c 800 Scaling Factor: 100 - Clients: 800 - Mode: Read Write pts/pgbench-1.13.0 -s 100 -c 800 Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency pts/unvanquished-1.8.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/high.cfg Resolution: 1920 x 1080 - Effects Quality: High pts/unvanquished-1.8.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/ultra.cfg Resolution: 1920 x 1080 - Effects Quality: Ultra pts/unvanquished-1.8.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/medium.cfg Resolution: 1920 x 1080 - Effects Quality: Medium pts/vvenc-1.0.0 -i Bosphorus_3840x2160.y4m --preset fast Video Input: Bosphorus 4K - Video Preset: Fast pts/vvenc-1.0.0 -i Bosphorus_3840x2160.y4m --preset faster Video Input: Bosphorus 4K - Video Preset: Faster pts/vvenc-1.0.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset fast Video Input: Bosphorus 1080p - Video Preset: Fast pts/vvenc-1.0.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset faster Video Input: Bosphorus 1080p - Video Preset: Faster