Alveo U55C High Performance Compute Card - Alveo U55C High Performance Compute Card - 2.5 English - UG1354

Vitis AI Library User Guide (UG1354)
Document_ID
UG1354
Release_Date
2022-06-15
Version
2.5 English

The Xilinx® Alveo™ U55C high performance compute card provides optimized acceleration for workloads in high performance computing (HPC), big data analytics and search, financial computing, computational storage and machine learning. In this release, the DPU is implemented in program logic for deep learning inference acceleration.

U55C Performance with 11PE300 MHz DPUCAHX8H-DWC

Refer to the following table for the throughput performance (in frames/sec or fps) for various neural network samples on U55C with DPUCAHX8H-DWC running at 11PE@300 MHz.

Table 1. U55C Performance with 11PE300 MHz DPUCAHX8H-DWC
No Neural Network Input Size GOPS DPU Frequency (MHz) Performance (fps) (Multiple thread)
1 bcc_pt 800x1000 269 300 37.4299
2 densebox_320_320 320x320 0.49 300 4900.28
3 densebox_640_360 360x640 1.1 300 2205.27
4 efficientNet-edgetpu-M_tf 240x240 7.34 300 1204.68
5 efficientNet-edgetpu-S_tf 224x224 4.72 300 2000.42
6 ENet_cityscapes_pt 512x1024 8.6 300 147.291
7 face_landmark 96x72 0.14 300 2205.27
8 face-quality 80x60 0.06 300 30651.4
9 face-quality_pt 80x60 0.06 300 30918.6
10 facerec_resnet20 112x96 3.5 300 2424.61
11 facerec-resnet20_mixed_pt 112x96 3.5 300 2423.09
12 facerec_resnet64 112x96 11 300 896.009
13 facereid-large_pt 96x96 0.5 300 15138.2
14 facereid-small_pt 80x80 0.09 300 32819.6
15 fpn 256x512 8.9 300 721.096
16 FPN_Res18_Medical_segmentation 320x320 45.3 300 179.581
17 FPN-resnet18_covid19-seg_pt 352x352 22.7 300 401.981
18 FPN-resnet18_Endov 240x320 13.8 300 652.217
19 hourglass-pe_mpii 256x256 10.2 300 604.947
20 inception_resnet_v2_tf 299x299 26.4 300 298.634
21 inception_v1 224x224 3.2 300 2101.57
22 inception_v1_tf 224x224 3 300 2185.25
23 inception_v2 224x224 4 300 1688.47
24 inception_v2_tf 224x224 3.88 300 672.69
25 inception_v3 299x299 11.4 300 690.495
26 inception_v3_pt 299x299 5.7 300 690.401
27 inception_v3_tf 299x299 11.5 300 691.406
28 inception_v3_tf2 299x299 11.5 300 709.433
29 inception_v4 299x299 24.5 300 324.079
30 inception_v4_2016_09_09_tf 299x299 24.6 300 324.683
31 medical_seg_cell_tf2 128x128 5.3 300 1972.68
32 MLPerf_resnet50_v1.5_tf 224x224 8.19 300 1012.03
33 mlperf_ssd_resnet34_tf 1200x1200 433 300 25.8372
34 mobilenet_1_0_224_tf2 224x224 1.1 300 5305.78
35 mobilenet_edge_0_75_tf 224x224 0.62 300 4716.44
36 mobilenet_edge_1_0_tf 224x224 0.99 300 3834.4
37 mobilenet_v1_0_25_128_tf 128x128 0.03 300 18873.8
38 mobilenet_v1_0_5_160_tf 160x160 0.15 300 12862.5
39 mobilenet_v1_1_0_224_tf 224x224 1.1 300 5305.64
40 mobilenet_v2 224x224 0.6 300 5323.56
41 MT-resnet18_mixed_pt 512x320 13.7 300 511.942
42 multi_task 288x512 14.8 300 542.182
43 multi_task_v3_pt 320x512 25.4 300 291.268
44 openpose_pruned_0_3 368x368 49.9 300 57.9091
45 personreid-res18_pt 176x80 1.1 300 6648.41
46 personreid-res50_pt 256x128 5.4 300 1611.62
47 plate_detection 320x320 0.49 300 7824.46
48 plate_num 96x288 1.75 300 2297.66
49 pmg_pt 224x224 2.28 300 1989.61
50 pointpainting_nuscenes_pt 40000x64x16 112 300 20.1126
51 pointpillars_nuscenes_pt 40000x64x5 108 300 39.9327
52 rcan_pruned_tf 360x640 87 300 80.0572
53 refinedet_baseline 480x360 123 300 93.8894
54 RefineDet-Medical_EDD_tf 320x320 9.8 300 789.952
55 refinedet_pruned_0_8 360x480 25 300 327.715
56 refinedet_pruned_0_92 360x480 10.1 300 707.408
57 refinedet_pruned_0_96 360x480 5.1 300 992.461
58 refinedet_VOC_tf 320x320 81.9 300 138.342
59 reid 80x160 0.95 300 6983.54
60 resnet18 224x224 3.7 300 2603.77
61 resnet50 224x224 7.7 300 1174.56
62 resnet50_pt 224x224 4.1 300 1012.4
63 resnet50_tf2 224x224 7.7 300 1174.21
64 resnet_v1_101_tf 224x224 14.4 300 610.351
65 resnet_v1_152_tf 224x224 21.8 300 407.059
66 resnet_v1_50_tf 224x224 7 300 1175.61
67 retinaface 360x640 1.11 300 1732.13
68 salsanext_pt 64x2048 20.4 300 153.159
69 salsanext_v2_pt 64x2048 32 300 58.4121
70 SemanticFPN_cityscapes_pt 256x512 10 300 803.504
71 SemanticFPN_Mobilenetv2_pt 512x1024 5.4 300 228.29
72 semantic_seg_citys_tf2 512x1024 54 300 90.0321
73 sp_net 128x224 0.55 300 5639.48
74 squeezenet 227x227 0.76 300 6171.87
75 squeezenet_pt 224x224 0.82 350 6398.41
76 ssd_adas_pruned_0_95 360x480 6.3 300 981.077
77 ssd_inception_v2_coco_tf 300x300 9.6 300 329.922
78 ssdlite_mobilenet_v2_coco_tf 300x300 1.5 300 2061.95
79 ssd_mobilenet_v1_coco_tf 300x300 2.5 300 2115.8
80 ssd_mobilenet_v2 360x480 6.6 300 717.919
81 ssd_mobilenet_v2_coco_tf 300x300 3.8 300 1458.46
82 ssd_pedestrian_pruned_0_97 360x640 5.9 300 890.03
83 ssd_resnet_50_fpn_coco_tf 640x640 178 300 58.9891
84 ssd_traffic_pruned_0_9 360x480 11.6 300 666.004
85 tiny_yolov3_vmss 416x416 5.46 300 1631.58
86 unet_chaos-CT_pt 512x512 23.3 300 136.798
87 vgg_16_tf 224x224 31 300 283.803
88 vgg_19_tf 224x224 39.3 300 238.409
89 vpgnet_pruned_0_99 480x640 2.5 300 934.319
90 yolov2_voc 448x448 34 300 317.894
91 yolov2_voc_pruned_0_66 448x448 11.6 300 779.019
92 yolov2_voc_pruned_0_71 448x448 9.9 300 905.845
93 yolov2_voc_pruned_0_77 448x448 7.8 300 1091.31
94 yolov3_adas_pruned_0_9 256x512 5.5 300 1223.77
95 yolov3_bdd 288x512 53.7 300 147.071
96 yolov3_voc 416x416 65.4 300 152.429
97 yolov3_voc_tf 416x416 65.6 300 152.75
98 yolov4_leaky_spp_m 416x416 60.1 300 155.946
99 yolov4_leaky_spp_m_pruned_0_36 416x416 38.2 300 166.494
100 ultrafast_pt 288x800 8.4 300 474.242
101 drunet_pt 528x608 2.59 300 469.205
102 person-orientation_pruned_558m_pt 224x112 0.56 300 11379.5
103 ofa_resnet50_0_9B_pt 160x160 0.9 300 2922
104 SESR_S_pt 360x640 7.48 300 282.558
105 c2d2_lite 512x512 6.86 300 28.2529
106 ofa_depthwise_res50_pt 176x176 1.25 300 2887.1
107 FairMot_pt 640x480 36 300 239.285
108 tsd_yolox_pt 640x640 73 300 131.889
109 ssr_pt 256x256 39.7 300 62.0193
110 chen_color_resnet18_pt 224x224 3.63 300 2645.11
111 face_mask_detection_pt 512x512 0.59 300 1581.35
112 ofa_rcan_latency_pt 360x640 45.7 300 65.5305
113 vehicle_make_resnet18_pt 224x224 3.63 300 2634.76
114 vehicle_type_resnet18_pt 224x224 3.63 300 2642.15
115 ofa_yolo_pt 640x640 48.9 300 178.7
116 ofa_yolo_pruned_0_30_pt 640x640 34.7 300 223.187
117 ofa_yolo_pruned_0_50_pt 640x640 24.6 300 283.17
118 yolov3-coco_tf2 416x416 65.9 300 150.588