4 x NVIDIA V100 32GB GPUs AI Workstation AW-V128 for More AI Models

Product Overview

The ALNETS AW-V128 is a state-of-the-art AI workstation designed specifically for heavy-duty AI computing needs across various industries. Equipped with advanced hardware, it is capable of supporting AI models with up to 100 billion parameters, making it an ideal choice for scientific research, finance, medical, and industrial applications.

Highlights

• High Computing Power: Equipped with 4 NVIDIA V100 GPUs for unparalleled processing capabilities.
• Large Memory Capacity: Supports extensive AI model parameters with a total of 128GB video memory.
• Stable Operation: Features dual liquid coolers for efficient thermal management.

Technical Specifications

• Model: ALNETS AW-V128
• GPU: 4 x NVIDIA Tesla V100 32GB
• GPU Memory: 128GB HBM2
• Supported AI Model Parameters: Up to 100 billion parameters
• Server Platform: Supermicro 7048 dual-socket chassis with integrated IPMI remote management module
• Processor: Intel Xeon E5-2680 v4 (14 cores, 28 threads) x 2
• Memory: 64GB DDR4 ECC (16GB × 4)
• Storage: 512GB SSD (extendable)
• Power Supply: 2 x 1600W 80Plus Gold or higher efficiency redundant power supplies
• Cooling Solution: 2 sets of 360mm split-type aluminum alloy liquid cooling systems
• Warranty: One-year warranty with installation and technical support

Application Scenarios

The ALNETS AW-V128 is designed for local deployment and can efficiently support the deployment and operation of large AI models. Core application scenarios include:

• Scientific Research & Education: Ideal for AI development and large model training.
• Finance: Supports risk control models, anti-fraud solutions, and data mining.
• Medical & Health: Facilitates image diagnosis and clinical support.
• Industrial Manufacturing: Enhances simulations, predictive maintenance, and production optimization.

AI Models Suitable for ALNETS AW-V128 Workstation

• GPT Series: Up to 175 billion parameters
• BERT: Up to 340 million parameters
• ResNet: Up to 152 layers
• YOLO: 6 to over 200 million parameters
• Deep Reinforcement Learning: Millions of parameters
• StyleGAN: Over 30 million parameters
• CycleGAN: Around 40 million parameters
• VAEs: Hundreds of thousands to millions of parameters
• Wav2Vec: Up to 300 million parameters
• DeepSeek: Optimized for large datasets
• Qwen: Extensive parameterization for nuanced responses

The ALNETS AW-V128, with its ability to support models with up to 100 billion parameters, excels in training and inference for these demanding AI applications.