decking

AMD Custom APU 0405 testing with a Valve Jupiter v1 (F7A0110 BIOS) and AMD Custom GPU 0405 1GB on SteamOS rolling via the Phoronix Test Suite.

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a
September 05 2023
  2 Hours, 1 Minute
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September 05 2023
  2 Hours, 1 Minute
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September 05 2023
  1 Hour, 47 Minutes
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decking AMD Custom APU 0405 testing with a Valve Jupiter v1 (F7A0110 BIOS) and AMD Custom GPU 0405 1GB on SteamOS rolling via the Phoronix Test Suite. ,,"a","b","c" Processor,,AMD Custom APU 0405 @ 2.80GHz (4 Cores / 8 Threads),AMD Custom APU 0405 @ 2.80GHz (4 Cores / 8 Threads),AMD Custom APU 0405 @ 2.80GHz (4 Cores / 8 Threads) Motherboard,,Valve Jupiter v1 (F7A0110 BIOS),Valve Jupiter v1 (F7A0110 BIOS),Valve Jupiter v1 (F7A0110 BIOS) Chipset,,AMD VanGogh Root Complex,AMD VanGogh Root Complex,AMD VanGogh Root Complex Memory,,16GB,16GB,16GB Disk,,512GB Phison ESMP512GKB4C3-E13TS + 1000GB RTL9210B-CG,512GB Phison ESMP512GKB4C3-E13TS + 1000GB RTL9210B-CG,512GB Phison ESMP512GKB4C3-E13TS + 1000GB RTL9210B-CG Graphics,,AMD Custom GPU 0405 1GB (1600/400MHz),AMD Custom GPU 0405 1GB (1600/400MHz),AMD Custom GPU 0405 1GB (1600/400MHz) Audio,,AMD Rembrandt Radeon HD Audio,AMD Rembrandt Radeon HD Audio,AMD Rembrandt Radeon HD Audio Monitor,,ANX7530 U,ANX7530 U,ANX7530 U Network,,Realtek RTL8822CE 802.11ac PCIe,Realtek RTL8822CE 802.11ac PCIe,Realtek RTL8822CE 802.11ac PCIe OS,,SteamOS rolling,SteamOS rolling,SteamOS rolling Kernel,,5.13.0-valve36-1-neptune (x86_64),5.13.0-valve36-1-neptune (x86_64),5.13.0-valve36-1-neptune (x86_64) Desktop,,KDE Plasma 5.26.1,KDE Plasma 5.26.1,KDE Plasma 5.26.1 Display Server,,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3 OpenGL,,4.6 Mesa 22.2.0 (git-17e5312102) (LLVM 14.0.6 DRM 3.45),4.6 Mesa 22.2.0 (git-17e5312102) (LLVM 14.0.6 DRM 3.45),4.6 Mesa 22.2.0 (git-17e5312102) (LLVM 14.0.6 DRM 3.45) Vulkan,,1.3.238,1.3.238,1.3.238 Compiler,,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0 File-System,,ext4,ext4,ext4 Screen Resolution,,1280x800,1280x800,1280x800 ,,"a","b","c" "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.1122,2.1213,2.3264 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,940.7032,940.4732,853.076 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,2.1732,2.1968,2.3847 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,460.1402,455.1871,419.3245 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,53.703,53.3204,58.1446 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,37.1925,37.4598,34.3521 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,50.1845,50.2327,55.6174 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,19.9099,19.8905,17.9622 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,21.3085,21.0947,22.179 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,93.8248,94.7494,90.1375 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream (items/sec)",HIB,18.1783,18.1777,19.4976 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream (ms/batch)",LIB,54.9957,54.9971,51.2707 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,6.423,6.4754,7.3794 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,311.1324,308.5592,270.324 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,6.0942,6.1143,6.6652 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,164.0752,163.5343,150.0141 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,26.9902,26.6504,29.4727 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,74.0619,75.0032,67.8272 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (items/sec)",HIB,25.1393,24.9051,27.0662 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (ms/batch)",LIB,39.7569,40.1323,36.9295 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,188.9603,188.3105,203.5527 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,10.5418,10.5794,9.7887 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,170.8681,170.4127,184.0044 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.8323,5.8481,5.4147 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,12.9044,12.961,13.9757 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,154.7848,154.1224,143.0633 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,12.3337,12.3783,13.1751 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,81.0533,80.7619,75.8765 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.7457,, "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,724.8871,, "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (items/sec)",HIB,2.6313,, "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (ms/batch)",LIB,380.0204,, "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,26.5799,28.872,29.5078 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,75.1762,69.2135,67.7439 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,24.5736,26.9723,26.9725 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,40.6737,37.0593,37.0592 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,13.1293,14.2177,14.2805 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,152.0727,140.6311,140.0128 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,12.5215,13.509,13.5048 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,79.8452,74.0106,74.033 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,18.1143,19.2761,19.6773 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,110.3133,103.5922,101.6061 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,15.6395,16.377,16.4839 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,63.922,61.0449,60.6503 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.2637,2.6289,2.5672 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,878.3129,760.724,778.4706 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (items/sec)",HIB,2.3648,2.556,2.5558 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (ms/batch)",LIB,422.8352,391.2056,391.2325 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,27.7184,29.8442,29.8109 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,72.108,66.9637,67.0376 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,25.7729,28.554,28.7074 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,38.7851,35.0067,34.8195 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,9.9683,11.0097,10.9375 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,200.4555,181.6241,182.6961 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,8.7687,9.4427,9.4377 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,114.0271,105.8874,105.9419 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.1364,2.2798,2.342 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,932.3056,877.2339,850.6684 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,2.2291,2.3896,2.3825 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,448.6054,418.4656,419.7098 "vkpeak - fp32-scalar (GFLOPS)",HIB,1638.24,1638.72,1639.27 "vkpeak - fp32-vec4 (GFLOPS)",HIB,1626.08,1626.6,1628.05 "vkpeak - fp16-scalar (GFLOPS)",HIB,1638.6,1639.31,1639.19 "vkpeak - fp16-vec4 (GFLOPS)",HIB,2618.33,2618.49,2619.64 "vkpeak - fp64-scalar (GFLOPS)",HIB,102.02,102.01,102.03 "vkpeak - int32-scalar (GIOPS)",HIB,279.05,279.13,279.16 "vkpeak - int32-vec4 (GIOPS)",HIB,326.93,326.95,327.27 "vkpeak - int16-scalar (GIOPS)",HIB,1638.31,1638.91,1639.04 "vkpeak - int16-vec4 (GIOPS)",HIB,2620,2619.45,2621.89 "vkpeak - fp64-vec4 (GFLOPS)",HIB,,102.03,102.06 "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 ()",,,, "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 (point/sec)",HIB,711045.2,, "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 (Latency)",LIB,56.1,, "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 ()",,,, "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 ()",,,, "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 ()",,,, "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 ()",,,, "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 ()",,,, "Apache IoTDB - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 ()",,,, "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200 ()",,,, "Apache IoTDB - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500 ()",,,, "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 ()",,,, "Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 ()",,,, "Apache Cassandra - Test: Writes (Op/s)",HIB,31081,29616,