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| Product Overview |
|---|
The Dell NVIDIA A30 Tensor Core 24GB GPU card provides specialized acceleration for AI, data analytics, and HPC applications within server environments. It fits into high-performance Dell systems to enhance processing speed and efficiency for demanding computational tasks. |
| General Information | |
|---|---|
| Brand | Dell |
| Part Number | W3C1G |
| Technical Information | |
|---|---|
| Chipset | Nvidia |
| Bus Interface | PCIe 4.0 x16 |
| Supported APIs | DirectX 12, OpenGL: 4.6, OpenCL, Vulkan: 1.2.175 , CUDA, Shader Model: 6.7, DirectCompute |
| Output Interface | None |
| Memory | |
|---|---|
| Memory Size | 24GB |
| Interface | HBM2 |
| Physical Characteristics | |
|---|---|
| Slot Width | Dual-slot |
| Weight | 3.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, cURus, CE, FCC, CCC, UL, TUV, cULus, CSA, cUL |
| Product Description |
|---|
The Dell NVIDIA A30 Tensor Core GPU is built to accelerate demanding workloads such as AI training, machine learning, and high-performance computing. It is often found in data centers and enterprise servers where processing speed and efficiency are critical. Engineered for professionals and organizations working with large datasets and complex algorithms, this graphics card helps reduce compute times and improve throughput in intensive applications. Key Features
This GPU is typically deployed in AI research labs, cloud computing infrastructures, and enterprise analytics platforms. Its role is to accelerate complex computations that traditional CPUs cannot handle efficiently. Users benefit from faster model training times and improved scalability in their computing environments. |
| Use Cases |
|---|
The Dell NVIDIA A30 Tensor Core GPU is primarily deployed in enterprise data centers and high-performance computing clusters where accelerated AI and data analytics workloads are critical. It benefits IT professionals and data scientists requiring robust computational power for server and workstation environments. How It's Used:
By integrating this GPU accelerator, organizations can improve throughput and reduce latency in demanding workloads, allowing scalable performance in dense server rack deployments and advanced edge computing scenarios. |