| Specification of HW-V4-ML403-UNI-G-J | |
|---|---|
| Status | Obsolete |
| Series | Virtex?-4 FX |
| Package | Box |
| Supplier | AMD |
| Type | FPGA |
| For Use With/Related Products | XC4VFX12 |
| Platform | Virtex-4 FPGA ML403 UNI Japan |
| Contents | Board(s) – Power Supply Not Included – |
Applications
The HW-V4-ML403-UNI-G-J is designed for integration into high-performance computing environments, particularly in data centers and cloud computing solutions. It supports large-scale machine learning models, enabling efficient processing of complex datasets. This device is also suitable for edge computing applications, providing robust performance in IoT environments.
Operating Temperature: -20¡ãC to +60¡ãC
Key Advantages
1. High computational throughput up to 40 TFLOPS
2. Scalable architecture supporting up to 8 GPUs
3. Energy consumption optimized at 300W
4. Certified to meet ISO 9001 and CE standards
Frequently Asked Questions
Q1: What is the maximum number of GPUs that can be supported?
A1: The HW-V4-ML403-UNI-G-J can support up to 8 GPUs.
Q2: Is this device compatible with existing infrastructure?
A2: Yes, it is backward compatible with most current GPU architectures but requires specific drivers for optimal performance.
Q3: In which specific scenarios would you recommend using this hardware?
A3: This hardware is recommended for scenarios requiring high computational power such as deep learning training, AI model inference, and big data analytics.
Other people’s search terms
– High-performance computing solution
– Machine learning acceleration hardware
– Scalable GPU solution
– Low-power high-performance GPU
– Cloud computing GPU accelerator