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Atlas 800 Deep Learning System

Tailored toward AI developers and data researchers, Huawei Atlas 800 provides end-to-end capabilities for data labeling, model generation, model training, and model inference services. With integrated software and hardware, this appliance reduces the technical entry requirements for AI applications and enables quick development and rollout of AI services for customers.

Huawei Atlas 800 AI appliance provides a Deep Learning Service (DLS) component as a one-stop deep learning platform. It integrates a large number of optimized network model algorithms to help users easily use deep learning technologies in a convenient and efficient manner, and provides users with model training, evaluation, and inference services through flexible scheduling and on-demand services.

Huawei

Specifications

Parameters Model
Model Atlas 800
Cluster Maximum nodes 128
Users 1,000
Recommended Jobs (per user) Training 10
Inference 5
Visualization 5
Code development 4
Web UI and Services
Processing Capability
Maximum online users 30
Maximum concurrent requests 30 per second
Request processing latency 3 seconds
API Processing Capability Maximum online users 30
Maximum concurrent requests 30 per second
Request processing latency 3 seconds
Hardware Specifications AI accelerator card Each full-width AI accelerator card:
8 full-height full-length AI accelerator cards (PCIe or NVLink)
Server Each full-width 2-socket compute node:
2 Xeon® Scalable® processors, 24 DDR4 DIMMs
Hard drives 2 x 2.5-inch SAS/SATA + 6 x 2.5-inch NVMe
PCIe model: scalable to 8 x 3.5-inch SAS/SATA
NVLink model: scalable to 8 x 2.5-inch SAS/SATA
RAID RAID 0, 1, 10, 5, 50, 6, or 60
I/O 4 x PCIe x16 LP + 2 x 10 GE LOM
Power supply units 4 hot-swappable 2,200W AC or 240V HVDC PSUs, with support for N+N redundancy
Fan modules 6 hot-swappable fan modules, with support for N+1 redundancy
Temperature 5°C to 35°C (41°F to 95°F)
Dimensions (H x W x D) 175 mm x 447 mm x 790 mm (6.89 in. x 17.60 in. x 31.10 in.)

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