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Accelerate AI Inference and Fine-Tuning with SuperNODE

SuperNODE is the world’s most powerful and energy-efficient scale-up AI computing platform.

SuperNODE’s AI-optimized infrastructure delivers cutting-edge inference performance and seamless fine-tuning capabilities — bringing state-of-the-art AI directly to your applications.

 

In the data center: SuperNODE

Performance Metrics

Record-Breaking Results

46,755 Tokens per second for
Llama 2 70B inference

12% Higher throughput
than competing solutions

99.7% Scaling efficiency

Key Features

Simplified Infrastructure

Connect up to 32 AMD or NVIDIA GPUs to a single node
Same latency as physically integrated GPUs
No code changes required

Revolutionary Architecture

Powered by GigaIO's AI fabric
Seamless device-to-node communication
Lowest possible latency and highest effective bandwidth

Testimonials

“This is an incredible platform for HPC and ML/AI. It is really wild to see 32 GPUs appear on ROCm SMI!”

Nick Malaya,
AMD Fellow, HPC

“The SuperNODE means less time messing with infrastructure and faster time to running and optimizing LLMs”

Greg Diamos,
Co-founder & CTO, Lamini

SuperNODE

Technical Specifications

System Configuration

Supports NVIDIA and non-NVIDIA GPUs and inference cards
Seamless AI fabric integration
Unified VRAM architecture

Ready to Accelerate Your AI Inferencing?

Schedule a demo today to see why SuperNODE is the world’s most powerful and energy-efficient scale-up AI computing platform.

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Curious to see how it works? Check out this 15-minute demo on how to liberate your compute resources.

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Niraj Mathur

Niraj has over 20 years of industry experience in strategic and product marketing, product management, business development, customer applications and advanced silicon engineering. He has held senior leadership roles and led global, cross-functional teams to support these disciplines. Niraj was instrumental in driving numerous successful networking products at Nortel Networks, Quake Technologies, AppliedMicro, Snowbush, Gennum, Semtech and Rambus. He has defined, developed and supported carrier grade hardware and software for the world’s leading telecom, enterprise and cloud customers. His past projects include Ethernet PHYs, core Internet switches, metro optical routers, high-speed silicon IPs and PCI Express products. Niraj holds a Bachelor of Computer Engineering from McGill University and an MBA from Cornell University.

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