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Product Overview |
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The HPE Alveo U50 8GB HBM PCIe 4.0 Accelerator Card serves as a hardware accelerator designed to offload specific compute tasks in enterprise IT setups. It features 8GB of High Bandwidth Memory to support data-intensive operations and utilizes the PCIe 4.0 interface for improved throughput compared to earlier PCIe versions. |
General Information |
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| Brand | HPE |
Technical Information |
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| Chipset | AMD |
| Interface / PCIe Slot | PCIe 4.0 x16 |
| Supported Frameworks | OpenCL |
| Supported Precisions | FP32, FP16, INT8 |
| ECC Memory | Yes — Full ECC |
| Cooling Type | Active Fan |
| Power Connector | None (slot-powered) |
Memory |
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| Memory Size | 8GB |
| Interface | HBM2 |
| Memory Bus | 1024-bit |
Miscellaneous |
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| Assembly Required | No |
| Compliance Standards | WEEE, RoHS, CE, FCC |
Physical Characteristics |
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| Slot Width | Single-slot |
| Form Factor | Full-Height Full-Length (FHFL) |
| Weight | 3.00 |
| Condition | Refurbished |
Product Description |
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The HPE Alveo U50 8GB HBM PCIe 4.0 Accelerator Card is engineered to accelerate compute-intensive workloads by providing dedicated hardware resources. It leverages 8GB of High Bandwidth Memory to facilitate rapid data access and transfer, addressing demands in data center and enterprise IT environments. This card is typically used by IT professionals and system administrators looking to enhance specific applications through hardware acceleration. Key Features
This accelerator card plays an important role in boosting computational workloads where additional processing power is required beyond standard CPU capabilities. It is particularly applicable in environments requiring efficient data movement and accelerated processing, contributing to enhanced overall system performance. |
Use Cases |
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This accelerator card is generally deployed in enterprise data centers and IT environments where accelerated computing is necessary. It is suited for workloads that benefit from high memory bandwidth and fast PCIe connectivity, particularly in tasks involving data analytics, machine learning, or other compute-intensive applications. How It's Used:
Overall, the card contributes to optimizing computational workloads by providing dedicated acceleration resources. It helps enhance specific processing tasks while maintaining integration within enterprise server infrastructure. |
FAQ's |
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