stress extra AMD EPYC 7763 64-Core testing with a AMD DAYTONA_X (RYM1009B BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite. AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X: Processor: AMD EPYC 7763 64-Core @ 2.45GHz (64 Cores / 128 Threads), Motherboard: AMD DAYTONA_X (RYM1009B BIOS), Chipset: AMD Starship/Matisse, Memory: 256GB, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: ASPEED, Monitor: VE228, Network: 2 x Mellanox MT27710 OS: Ubuntu 22.04, Kernel: 5.15.0-47-generic (x86_64), Desktop: GNOME Shell 42.4, Display Server: X Server 1.21.1.3, Vulkan: 1.2.204, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080 BRL-CAD 7.36 VGR Performance Metric VGR Performance Metric > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 735105 |====================== Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 681.49 |====================== Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 46.48 |======================= Apache Cassandra 4.1.3 Test: Writes Op/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 227576 |====================== NCNN 20230517 Target: CPU - Model: FastestDet ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 11.87 |======================= NCNN 20230517 Target: CPU - Model: vision_transformer ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 47.5 |======================== NCNN 20230517 Target: CPU - Model: regnety_400m ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 36.69 |======================= NCNN 20230517 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 13.92 |======================= NCNN 20230517 Target: CPU - Model: yolov4-tiny ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 21.04 |======================= NCNN 20230517 Target: CPU - Model: resnet50 ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 15.48 |======================= NCNN 20230517 Target: CPU - Model: alexnet ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 5.25 |======================== NCNN 20230517 Target: CPU - Model: resnet18 ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 8.57 |======================== NCNN 20230517 Target: CPU - Model: vgg16 ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 23.78 |======================= NCNN 20230517 Target: CPU - Model: googlenet ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 14.39 |======================= NCNN 20230517 Target: CPU - Model: blazeface ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 4.92 |======================== NCNN 20230517 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 9.96 |======================== NCNN 20230517 Target: CPU - Model: mnasnet ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 5.87 |======================== NCNN 20230517 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 8.88 |======================== NCNN 20230517 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 6.94 |======================== NCNN 20230517 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 6.3 |========================= NCNN 20230517 Target: CPU - Model: mobilenet ms < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 14.09 |======================= Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 55.53 |======================= Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 575.44 |====================== Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10 Ops/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 2450822.55 |================== Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5 Ops/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 2318759.53 |================== Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 Ops/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 2223166.07 |================== Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5 Ops/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 2233880.23 |================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 222.07 |====================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 143.97 |====================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 596.06 |====================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 53.66 |======================= Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 65.62 |======================= Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 487.36 |====================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 191.49 |====================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 166.70 |====================== Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 842.27 |====================== Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 37.60 |======================= Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 838.07 |====================== Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 37.63 |======================= Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 28.99 |======================= Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 1102.88 |===================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 97.31 |======================= Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 328.07 |====================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 139.57 |====================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 228.64 |====================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 142.02 |====================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 224.75 |====================== Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 68.44 |======================= Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 467.08 |====================== Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 68.31 |======================= Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 467.51 |====================== Stress-NG 0.16.04 Test: IO_uring Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 6295021.37 |================== Stress-NG 0.16.04 Test: CPU Cache Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 1414607.05 |================== Stress-NG 0.16.04 Test: Atomic Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 206.31 |====================== Stress-NG 0.16.04 Test: Futex Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 2343496.22 |================== Stress-NG 0.16.04 Test: Fused Multiply-Add Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 49433147.11 |================= Stress-NG 0.16.04 Test: MEMFD Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 437.04 |====================== Stress-NG 0.16.04 Test: Malloc Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 186568211.34 |================ Stress-NG 0.16.04 Test: Cloning Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 7463.78 |===================== Stress-NG 0.16.04 Test: MMAP Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 1233.47 |===================== Stress-NG 0.16.04 Test: Zlib Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 6210.36 |===================== Stress-NG 0.16.04 Test: SENDFILE Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 839871.86 |=================== Stress-NG 0.16.04 Test: Pthread Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 108230.65 |=================== Stress-NG 0.16.04 Test: Memory Copying Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 13220.97 |==================== Stress-NG 0.16.04 Test: Glibc Qsort Data Sorting Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 1272.64 |===================== Stress-NG 0.16.04 Test: Socket Activity Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 9049.41 |===================== Stress-NG 0.16.04 Test: Matrix 3D Math Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 5709 |======================== Stress-NG 0.16.04 Test: NUMA Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 291.55 |====================== Stress-NG 0.16.04 Test: Function Call Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 38065.86 |==================== Stress-NG 0.16.04 Test: Floating Point Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 17129.98 |==================== Stress-NG 0.16.04 Test: System V Message Passing Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 8956860.19 |================== Stress-NG 0.16.04 Test: Vector Floating Point Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 156275.9 |==================== Stress-NG 0.16.04 Test: AVL Tree Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 558.18 |====================== Stress-NG 0.16.04 Test: Mutex Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 36913960.47 |================= Stress-NG 0.16.04 Test: Context Switching Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 7733688.1 |=================== Stress-NG 0.16.04 Test: Mixed Scheduler Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 53645.16 |==================== Stress-NG 0.16.04 Test: Vector Shuffle Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 36503.49 |==================== Stress-NG 0.16.04 Test: Semaphores Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 140637012.03 |================ Stress-NG 0.16.04 Test: Forking Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 61808.18 |==================== Stress-NG 0.16.04 Test: Poll Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 7893061.95 |================== Stress-NG 0.16.04 Test: Glibc C String Functions Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 45614430.99 |================= Stress-NG 0.16.04 Test: Wide Vector Math Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 2104650.98 |================== Stress-NG 0.16.04 Test: x86_64 RdRand Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 17319858.87 |================= Stress-NG 0.16.04 Test: AVX-512 VNNI Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 3797236.44 |================== Stress-NG 0.16.04 Test: Vector Math Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 341516.25 |=================== Stress-NG 0.16.04 Test: Matrix Math Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 223038.42 |=================== Stress-NG 0.16.04 Test: CPU Stress Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 128172.34 |=================== Stress-NG 0.16.04 Test: Crypto Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 123450.01 |=================== Stress-NG 0.16.04 Test: Pipe Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 37830030.68 |================= Stress-NG 0.16.04 Test: Hash Bogo Ops/s > Higher Is Better AMD EPYC 7763 64-Core - ASPEED - AMD DAYTONA_X . 11144840.42 |================= Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10 Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5 Neural Magic DeepSparse 1.5 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better