Atlas 500 AI edge station Model 3000/3010 Atlas 300 AI accelerator card Model 3000 Atlas 200 AI accelerator module Model 3000 Atlas 800 AI server Model 3000/3010 Ascend 910 AI processor Atlas 300 AI accelerator card Model 9000 Atlas 800 AI server Model 9000/9010 Atlas 900 AI cluster
Convolution Full-mesh 10% Vector operation Pooling Relu AI computing characteristics • The GPU is not designed for AI computing. Therefore, it is inefficient in matrix multiply computing. Da Vinci architecture: best-fit for AI computing • The Da Vinci architecture is specially designed for AI computing. • Provides cube, vector, and scalar computing units for AI computing • The Da Vinci architecture has a large proportion of cubes, enabling high matrix multiply computing efficiency, and optimal area-to-efficiency ratio. 16 x 16 x 16 cubes Vector Scalar Other AI Chip Architectures Da Vinci Architecture Chip area (12nm) 5.x mm2 13.x mm2 Computing power 1.7 TOPS FP16 8 TOPS FP16 Area-to-efficiency ratio ~0.3 ~0.6 ~90% are matrix multiply operation • AI computing is mainly based on the convolutional neural network (CNN) model. • About 90% of the CNN model is based on matrix multiply operations. • The cube computing unit is the most suitable. GPU NPU Applicab le only to HPC, not AI Scalar 4 x 4 x 4 cubes 2x area-to- efficiency ratio On the same area, the Da Vinci architecture delivers 2x computing power.
310 AI processor Atlas 800 AI server – Model 3010 Intel Xeon Host CPU Backbone Iter 1 Head Iter 1 Backbone Iter 2 Backbone Iter 3 Head Iter 2 Backbone Iter N Head Iter N-1 Data Data Data Inference of backbone model on Ascend using ACL Inference of head model on CPU using Intel OpenVINO
25,00 30,00 35,00 40,00 Inference Time(ms), batch=8 Full MobileNetV2-SSD (CPU) MobileNetV2-SSD backbon only (Ascend) MobileNetV2-SSD head only (CPU) MobileNetV2 Backbone (Ascend) + SSD Head (CPU) Parallel MobileNetV2-SSD Batch = 8 Average time, ms (per iter) Full model (CPU) 36,80 Backbon only (Ascend) 24,06 Head only (CPU) 17,12 Backbone (Ascend) + SSD Head (CPU) Parallel 26,69
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