
Subscribe To Our Newsletter!
Subscribe to the newsletter to stay up to date with the latest news and most useful
Newsletter
↑
Back to Top
| Product Overview |
|---|
The M44NW Dell NVIDIA Tesla C2075 video graphics card delivers dedicated GPU computing power aimed at professionals handling intensive scientific and engineering applications. It fits into PCI Express slots and is designed to enhance computational throughput in workstations and servers that require robust parallel processing capabilities. |
| General Information | |
|---|---|
| Brand | Dell |
| Part Number | M44NW |
| Technical Information | |
|---|---|
| Chipset | Nvidia |
| Bus Interface | PCI Express 2.0 x16 |
| Supported APIs | OpenCL, CUDA, DirectCompute |
| Output Interface | None (no display outputs) |
| Suggested PSU | 600W |
| Power Connectors | 2 x 6-pin PCIe |
| Memory | |
|---|---|
| Memory Size | 6GB |
| Interface | GDDR5 |
| Memory Bus | 384-bit |
| Physical Characteristics | |
|---|---|
| Slot Width | Dual-slot |
| Weight | 5.00 |
| 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 M44NW Dell NVIDIA Tesla C2075 is built for demanding computational workloads, focusing on scientific simulations and complex data analysis. It is commonly found in research labs, engineering firms, and data centers where parallel processing power is a priority. Engineered to accelerate GPU computing tasks, this graphics card serves professionals working with large datasets or simulations that benefit from GPU acceleration. Key Features
This card is typically installed in workstations or servers where GPU acceleration is needed for tasks like physics simulations, computational fluid dynamics, or machine learning research. It helps reduce processing times and improve workflow efficiency in these specialized fields. |
| Use Cases |
|---|
The M44NW Dell NVIDIA Tesla C2075 is utilized in environments where accelerated computing and parallel processing are critical. How It's Used:
This card is integral to workflows demanding robust GPU acceleration to improve computational speed and efficiency. |