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| Product Overview |
|---|
The Lenovo NVIDIA Redstone SXM4 400W 40GB HBM2e GPU Board Assembly provides high-capacity memory and powerful GPU architecture to meet the demands of intensive computing tasks. It fits into Lenovo systems designed for professional use cases involving AI, machine learning, and data science workloads where sustained performance is essential. |
| General Information | |
|---|---|
| Brand | Lenovo |
| Part Number | 02JK722 |
| Alternate Part Number | 02JK722-12-HU |
| Technical Information | |
|---|---|
| Chipset | Nvidia |
| Bus Interface | SXM4 |
| Supported APIs | DirectX 12, OpenGL: 4.6, OpenCL, OpenCL: 3.0, Vulkan: 1.2.175 , CUDA, Shader Model: 6.7, DirectCompute |
| Memory | |
|---|---|
| Memory Bus | 5120-bit |
| Physical Characteristics | |
|---|---|
| Weight | 3.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, CE, FCC, UL, TUV |
| Product Description |
|---|
This Lenovo NVIDIA Redstone SXM4 GPU Board Assembly is built for handling demanding computational tasks that require substantial graphics processing power. Often found in data centers, AI research labs, and high-end workstations, it supports applications ranging from deep learning to scientific simulations. Built for professionals and organizations pushing the limits of data processing, it integrates seamlessly with Lenovo systems targeting advanced GPU acceleration. Its design supports sustained performance for complex workloads. Key Features
This GPU board assembly is typically deployed in environments where large-scale computation is critical, such as AI development and scientific research. It plays a key role in accelerating workflows that demand massive parallel processing with reliability. |
| Use Cases |
|---|
The 02JK722 Lenovo NVIDIA Redstone SXM4 GPU board assembly is designed to cater to professionals in AI research, scientific computing, and enterprise data centers. How It's Used:
This GPU board assembly plays a critical role in environments requiring exceptional computational throughput and reliability. |