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Product Overview |
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The Lenovo Xeon Phi 7120P accelerator card offers a solid balance of high core count and memory capacity to tackle demanding parallel processing tasks. It fits well into setups focused on HPC, scientific research, or machine learning, providing the extra processing power needed for complex workloads without overwhelming the main CPU. |
General Information |
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| Brand | Lenovo |
| Part Number | 90Y2362 |
| Series | Intel Xeon Phi 7120P (Knights Corner) |
| Alternate Part Number | 90Y2362-13-CT |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Product Description |
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The Lenovo Xeon Phi 7120P accelerator card is built for heavy computational workloads, especially those that benefit from parallel processing. It is often found in data centers and research labs where complex simulations and data analytics are essential. Engineered for professionals in scientific computing, engineering, and machine learning, this card helps speed up performance by offloading demanding tasks from the CPU. Its many cores and fast memory make it a practical choice for those needing reliable acceleration in their workflows. Key Features
This accelerator card is typically deployed in environments where large-scale computations are routine, like weather modeling or financial simulations. It plays a crucial role in reducing processing times and improving efficiency without requiring significant changes to existing infrastructure. |
Use Cases |
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The Lenovo Xeon Phi 7120P accelerator card is tailored for environments requiring substantial parallel processing capabilities, such as high-performance computing clusters and scientific research labs. It benefits users who manage compute-intensive workloads, particularly in multi-node systems aiming to accelerate complex calculations without burdening the central CPU. How It's Used:
By integrating the Xeon Phi 7120P, organizations can improve operational efficiency by distributing parallel workloads across many cores, facilitating scalable performance in demanding compute environments. This focused acceleration helps maintain throughput and responsiveness in intensive data processing scenarios. |