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Product Overview |
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The HP Nvidia Tesla C2075 is a GPU accelerator designed to boost computational workloads in professional environments. It fits into PCI-Express 2.0 slots and is tailored to accelerate tasks that benefit from parallel processing, commonly used in scientific research, engineering simulations, and data analysis applications. |
General Information |
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| Brand | HP |
| Part Number | QE209AV |
Technical Information |
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| Chipset | Nvidia |
| Bus Interface | PCI-Express 2.0 x16 |
| Supported APIs | OpenCL, CUDA |
| Output Interface | None (compute accelerator - no display outputs) |
Memory |
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| Memory Size | 6GB |
| Interface | GDDR5 |
| Memory Bus | 384-bit |
Physical Characteristics |
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| Slot Width | Dual-slot |
| Weight | 5.00 |
| Condition | Refurbished |
Miscellaneous |
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| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, CE, FCC, UL, TUV |
Product Description |
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The HP Nvidia Tesla C2075 GPU accelerator card is built for demanding computational tasks that benefit from parallel processing power. Often found in workstations and servers, it accelerates scientific calculations, simulations, and complex data workloads. Engineers, researchers, and data scientists commonly use this card to speed up applications that require intense floating-point calculations or GPU computing. Its integration into systems is aimed at enhancing performance in areas like physics modeling, financial analytics, and large-scale data processing. Key Features
This GPU card is typically deployed in research labs, engineering firms, and data centers where high-throughput computation is essential. It plays a critical role in reducing processing times for complex models and simulations, making it easier for professionals to handle large-scale problems without extensive wait times. |
Use Cases |
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The HP NVIDIA Tesla C2075 graphics card is predominantly utilized in high-performance computing environments where parallel processing is essential. It is well-suited for research laboratories, engineering firms, and data centers executing complex simulations or data-intensive analyses that require accelerated GPU computation. How It's Used:
By integrating the Tesla C2075 GPU accelerator, organizations can leverage substantial improvements in computational performance and scalability. This results in reduced processing times and increased throughput for workloads that depend heavily on parallel computations, enhancing overall operational efficiency in demanding IT infrastructures. |