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Product Overview |
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The AMD EPYC 8124P is a 16-core server processor designed for single-socket systems requiring efficient yet powerful compute performance. It fits well in data centers where parallel processing and memory throughput are important for tasks such as virtualization and large-scale data handling. |
General Information |
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| Brand | AMD |
| Part Number | 100-000001135 |
Technical Information |
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| # Of Cores | 16 Core |
| Total Threads | 32 |
| Base Clock Speed | 2.45 GHz |
| PCIe Version | PCIe 4.0 |
| Lithography | 7 nm |
| Socket Type | SP3 |
Memory Specifications |
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| Memory Types | DDR4 |
| Max Memory Channels | 8 |
Physical Characteristics |
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| Weight | 5.00 |
| Condition | Refurbished |
Miscellaneous |
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| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, cURus, CE, FCC, CCC, UL, TUV, cULus, CSA, cUL |
Product Description |
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The AMD EPYC 8124P is a powerful server-grade processor designed to handle demanding data center workloads. Often found in enterprise servers, it supports multi-threaded applications, virtualization, and cloud computing environments. Built for IT professionals and organizations needing reliable compute power, this processor balances performance and energy efficiency. Key Features
This processor is typically deployed in enterprise servers, cloud infrastructures, and high-performance computing setups where reliable and scalable processing is essential. Its combination of core count and memory support helps handle complex workloads without excessive power draw. |
Use Cases |
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The AMD EPYC 8124P processor is optimized for single-socket server environments demanding high memory throughput and efficient multi-threaded performance. It is particularly suited for enterprise IT infrastructures and data centers that require robust compute capabilities without multi-socket complexity. How It's Used:
By leveraging its 16-core architecture and 8-channel DDR4 support, the EPYC 8124P delivers scalable and efficient processing power tailored for environments where operational consistency and memory performance directly impact workload execution and resource utilization. |