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Product Overview |
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The Dell TN59Y EPYC 7763 processor is a high-core-count CPU designed to provide robust performance for server and data center applications. It fits well into environments where large-scale processing and multi-threading are essential, supporting demanding workloads in enterprise and cloud settings. |
General Information |
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| Brand | AMD |
| Part Number | TN59Y |
Technical Information |
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| Processor Family | EPYC Milan |
| # Of Cores | 64 Core |
| Total Threads | 128 |
| Max Turbo Frequency | 3.5 GHz |
| Base Clock Speed | 2.45 GHz |
| PCIe Version | PCIe 4.0 |
| Lithography | 7 nm |
| Socket Type | SP3 |
| Cache | 256 MB |
| Thermal Design Power | 280 W |
Memory Specifications |
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| Max Memory Size | 4 TB |
| Memory Types | DDR4-3200 |
| Max Memory Channels | 8 |
| Bandwidth | 204.8 GB/s |
Physical Characteristics |
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| Weight | 5.00 |
| Condition | Refurbished |
Miscellaneous |
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| Compliance Standards | RoHS |
Product Description |
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The AMD EPYC 7763 processor delivers powerful multi-threaded performance ideal for demanding server and data center environments. Often found in enterprise servers, it handles heavy virtualization, database management, and large-scale computing tasks with ease. Built for IT professionals and organizations needing reliable, scalable processing power, this CPU supports workloads that require parallel processing and high bandwidth memory access. Key Features
This processor is typically deployed in large-scale cloud infrastructure, high-performance computing clusters, and enterprise servers where reliability and throughput are critical. It plays a key role in accelerating data-intensive tasks without compromising stability. |
Use Cases |
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The AMD EPYC 7763 processor is optimized for environments requiring substantial parallel processing power and memory bandwidth. It is particularly suited for data centers, cloud service providers, and enterprises managing large-scale virtualized workloads or complex computational tasks. How It's Used:
This processor's architecture allows IT teams to scale infrastructure efficiently while maintaining high performance under intensive multi-threaded workloads. It provides a foundation for handling demanding computational tasks with improved operational throughput and resource utilization. |