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HPE 835617-001 Intel Xeon E5-2698V4 2.2GHz 20-Core processor
SKU:
835617-001
Weight: 5.00 lbs
Condition: Refurbished
- Intel Xeon E5-2698V4 with 20 cores at 2.2GHz clock speed
- Built on Broadwell architecture for improved performance
- Supports multi-threading to handle heavy workloads
- Compatible with HPE systems for enterprise computing
In stock
$285.59
| Product Overview |
|---|
The HPE 835617-001 Intel Xeon E5-2698V4 is a 20-core server processor designed for demanding enterprise workloads. It fits into HPE server systems to provide a balance of core count and clock speed, supporting multitasking and virtualization in professional IT environments. |
| General Information | |
|---|---|
| Brand | HPE |
| Part Number | 835617-001 |
| Technical Information | |
|---|---|
| # Of Cores | 20 Core |
| Total Threads | 40 |
| Max Turbo Frequency | 3.60 GHz |
| Base Clock Speed | 2.20 GHz |
| PCIe Version | PCIe 3.0 |
| Lithography | 14 nm |
| Socket Type | LGA 2011 |
| Cache | 50 MB Intel Smart Cache |
| Thermal Design Power | 135 W |
| Memory Specifications | |
|---|---|
| Max Memory Size | 1 TB |
| Memory Types | DDR4-1600,DDR4-1866,DDR4-2133 |
| Max Memory Channels | 4 |
| Bandwidth | 68.3 GB/s (DDR4-2133, quad-channel) |
| Physical Characteristics | |
|---|---|
| Weight | 5.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Eco Friendly | Yes |
| Compliance Standards | RoHS, CE, FCC |
| Product Description |
|---|
This Intel Xeon E5-2698V4 processor is designed to deliver powerful computing performance for servers and workstations. It is commonly used in data centers and enterprise environments where high core-count and efficient processing are essential. IT professionals and system administrators often rely on this CPU to run virtualization, database management, and intensive analytics applications. Key Features
These processors are frequently deployed in enterprise server racks, providing the backbone for cloud services, data analytics, and virtualization platforms. Their multi-core setup allows organizations to efficiently handle simultaneous tasks without performance bottlenecks. |
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