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Product Overview |
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The HPE P39062-001 EPYC 7763 processor offers robust multi-core performance tailored for enterprise server environments. It fits well in data centers and high-demand computing setups where its cores and power capacity support complex workloads without compromise. |
General Information |
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| Brand | HPE |
| Part Number | P39062-001 |
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 |
| Max Memory Channels | 8 |
| Bandwidth | 204.8 GB/s |
Physical Characteristics |
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| Weight | 5.00 |
| Condition | Refurbished |
Product Description |
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This HPE processor packs 64 cores running at 2.45GHz, making it ideal for demanding computing environments. It’s commonly used in servers where processing large volumes of data quickly is critical. IT professionals and system architects often rely on this chip to enhance the performance of cloud services, virtualization, and complex data analytics. Key Features
These processors are typically deployed in data centers powering enterprise applications and large-scale servers. Their ability to manage multiple tasks concurrently helps organizations maintain efficiency and reliability under heavy load conditions. |
Use Cases |
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The HPE P39062-001 EPYC 7763 processor is engineered for demanding enterprise server environments where high core count and multi-threading capabilities are critical. It is best suited for data centers and IT operations that require intensive computational workloads, such as virtualization and large-scale application hosting. How It's Used:
This processor’s architecture and power profile allow organizations to optimize performance while maintaining operational efficiency. Its scalability and multi-core design ensure it can handle evolving workloads in dynamic enterprise environments. |