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Product Overview |
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The AMD EPYC 7H12 processor offers 64 cores at a 2.6GHz clock speed, making it suitable for demanding data center and HPC applications. It fits into server environments that require robust multi-threading and efficient power use, providing a reliable foundation for complex computational tasks. |
General Information |
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| Brand | AMD |
| Part Number | 100-000000055 |
Technical Information |
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| # Of Cores | 64 Core |
| Total Threads | 128 |
| Max Turbo Frequency | 3.3 GHz |
| Base Clock Speed | 2.6 GHz |
| Socket Type | SP3 |
| Cache | 256 MB |
| Thermal Design Power | 240 W |
Memory Specifications |
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| Max Memory Size | 4 TB |
| Memory Types | DDR4-3200, DDR4, Registered ECC |
| 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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The AMD EPYC 7H12 is a powerful 64-core processor built for heavy computational tasks. It is commonly used in data centers, cloud servers, and high-performance computing environments where parallel processing and reliability are essential. This processor often finds its place in workloads like virtualization, scientific simulations, and large-scale databases, benefiting IT professionals and system architects who need dependable and scalable computing power. Key Features
Typically deployed in enterprise-grade servers or cloud infrastructure, this processor helps deliver consistent performance under heavy loads. Its design supports critical workloads where stability and processing capacity are priorities. |
Use Cases |
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The AMD EPYC 7H12 processor is optimized for high-density server environments requiring extensive parallel processing capabilities. It is particularly suited for organizations handling large-scale simulations, data analytics, and virtualization workloads that demand consistent multi-threaded performance. How It's Used:
This processor supports operational efficiency through its high core count and energy-efficient design, enabling scalable deployments that meet the increasing computational demands of modern data centers and HPC facilities without compromising on power consumption. |