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星空X9加速卡

Nebula Accelerator X9

High-performance AI Inference Accelerator
星空X9加速卡
四核CAISA引擎 四核CAISA引擎
Quad-Engine CAISA Accelerator
高算力性价比 高算力性价比
High Cost Efficiency
延时低至3ms 延时低至3ms
3 ms Latency
Specifications
Chip:
CAISA
Power Supply:
PSU
Architecture:
Custom AI Streaming Accelerator (CAISA) Architecture 3.0
Power Consumption:
TDP 230 W
Chip Utilization Ratio:
Up to 95.7%
Cooling:
Passive Cooling
Peak Performance:
43.6 TOPS
Temperature:
0℃ ~ 45℃
PCIe:
PCI Express3.0 x 16
Humidity:
<95%
Memory:
32 GB DDR4
Dimension:
313.9 mm x 106.7 mm(standard full-length, full-height, double-slot)
Benchmark
ResNet-50

3.06 ms

5235.59 FPS

ResNet-152

8.67 ms

1846.06 FPS

YOLOv3

31.30 ms

511.24 FPS

SSD-ResNet50

21.83 ms

733.13 FPS

U-Net Industrial

73.18 ms

218.65 FPS

Note:Batch=16,INT8.The above CNN models are created by TensorFlow framework.

Benchmark Comparison
Left Slip
3.28x
92.5%
X9
28.22%
GPU
ResNet-50
11.79x
83.7%
X9
7.1%
GPU
YOLOv3
10.33x
77.5%
X9
7.5%
GPU
SSD-ResNet50
5.52x
65.7%
X9
11.9%
GPU
U-Net Industrial
X9 VS GPU Chip Utilization Ratio
1.07x
5235.5
X9
4879.00
GPU
ResNet-50
3.97x
511.24
X9
128.80
GPU
YOLOv3
3.46x
733.13
X9
212.00
GPU
SSD-ResNet50
1.85x
218.65
X9
118.00
GPU
U-Net Industrial
X9 VS GPU Performance(FPS)
0.12x
3.06
X9
26.23
GPU
ResNet-50
0.03x
31.30
X9
993.78
T3
YOLOv3
0.14x
21.83
X9
150.94
GPU
SSD-ResNet50
0.54x
73.18
X9
135.59
GPU
U-Net Industrial
X9 VS GPU Latency(ms)

Accelerate AI Deployment with Next-Gen Computing Platform

4009-606-596

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