Accelerate Everything

Supermicro Edge AI

Edge Video Transcoding, Edge Inference, Edge Training
Across industries, businesses whose employees and customers engage at edge locations - in cities, factories, retail stores,
hospitals, and many more - are increasingly investing in deploying AI at the edge. By processing data and utilizing AI and ML
algorithms at the edge, businesses overcome bandwidth and latency limitations, enabling real-time analytics for timely decision
making, predictive care and personalized services, and streamlined business operations.
Purpose-built, environment-optimized Supermicro Edge AI servers with various compact form factors deliver the performanceneeded for low-latency, open architecture with pre-integrated components, diverse hardware and software stack compatibility,and privacy and security feature set required for complex edge deployments out of the box.

Systems
Short-Depth 5G/Edge & Hyper E

Fanless and Wallmount Edge

Compute and AI Performance at the Edge

Compact Systems for the Intelligent Edge

Large Workload:
Compact System

Extra Large Workload:
2U Hyper-E• 3 NVIDIA H100 PCIe
• 6 NVMe drives• 32 DIMMs DDR5-4800

SYS-221HE-FTNR /SYS-221HE-FTNRD

Medium Workload:
Short-Depth Multi-GPU Edge
Server• Powerful expandable server for theEdge• 1 NVIDIA L40S or 2 L4
• 8 DIMMs DDR5-4800• 4 NVMe Drives

SYS-E403-13E

Small Workload:
Embedded System• 1U Compact Edge/5G Server• 2 NVIDIA L4• 2 Internal drive bays
• 8 DIMMs DDR5-4800

SYS-111E-FWTR• Compact Mini-1U Server• NVIDIA A2 or T1000• Up to 64GB DDR4
• M.2 M/E-Key

SYS-E300-13AD

Medium Workload:
1U Embedded Server

Small Workload:
Fanless System• 1U Compact Edge/Embedded Server• Intel® Core™ processor• 1 NVIDIA L40 or RTX A4500• 4 DIMMs DDR5-4400• Ultra-compact fanless edge server• CPU (or ASIC) based Inference• Up to 64GB DDR5
• M.2 M/B/E-Key with Nano SIM card slot

SYS-111AD-WRN2SYS-E100-13AD

Recommended NVIDIA GPUs

L4L40SL40

RTX 6000 Ada• HHHL SW• PCIe 4.0 x16• 72W• 24GB GDDR6• FHFL DW• PCIe 4.0 x16• 350W• 48GB GDDR6• FHFL DW• PCIe 4.0 x16• 300W• 48GB GDDR6• FHFL DW• PCIe 4.0 x16• 300W• 48GB GDDR3© Copyright Super Micro Computer, Inc. All rights reserved

May 2024

Supermicro Edge AI

Accelerate Edge AI Workloads

Edge Video Transcoding, Edge Inference, Edge Training
Opportunities and Challenges:• Space and weight limitation, power constraints• Balancing data throughput for video and audio requirements with cost of storage and bandwidth constraints• Latency impacting response time and service quality• Data privacy and security, regulatory compliance• Resiliency in face of network outages• Long product lifecycle requirements
Key Technologies:• CPU or GPU-based Edge AI Inferencing, GPU-based Edge AI training, and video transcoding/encoding/decoding• NVIDIA L4, L40S, L40, A30, A40, T4, A2 GPUs
• Short-depth chassis design for edge locations with AC or DC power supply options• Front I/O with broad range of expansion and I/O port for flexibility and serviceability• Ruggedized systems designed to be placed outside of the data center
Solution Stack:• NVIDIA® TensorRT™ and Triton Inference Server• NVIDIA DeepStream, Clara, Merlin, Metropolis, Morpheus, Omniverse, and Riva
• NVIDIA Fleet Command• Intel® OpenVINO
Use Cases:• Video processing: decode, encode, and transcode• Edge inference: vision, speech, anomaly detection, etc.
• Markets: security and surveillance, retail, manufacturing, healthcare, and medical devices

GPU Acceleration for Complete Range of Workloads

Go to www.supermicro.com/ai or scan the QR code to
download the AI Workload Solution Brochure:©Copyright Super Micro Computer, Inc. Specifications subject to change without notice. All other brands and names are the property of theirrespective owners. All logos, brand names, campaign statements and product images contained herein are copyrighted and may not bereprinted and/or reproduced, in whole or in part, without express written permission by Supermicro Corporate Marketing.