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Product Overview |
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The NVIDIA A30 Tensor Core 24GB GPU accelerates AI and data analytics workloads, fitting seamlessly into server environments needing powerful computation and memory capacity. It delivers a solid balance of performance for both training and inference, making it a reliable choice for organizations working with complex machine learning models and large-scale data processing. |
General Information |
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| Brand | Nvidia |
| Part Number | 699-21001-0205-601 |
Technical Information |
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| Chipset | Nvidia |
Memory |
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| Memory Size | 24GB |
| Interface | HBM2 |
Miscellaneous |
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| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, CE, FCC, UL, TUV |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Product Description |
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The NVIDIA A30 Tensor Core GPU is built for demanding AI and data-intensive tasks, offering substantial computational power and memory bandwidth. It’s often found in enterprise data centers and research environments where machine learning model training and inference require fast, reliable acceleration. This GPU is commonly used in servers that handle large datasets and complex algorithms, making it ideal for professionals in AI development, scientific computing, and analytics. Its design supports efficient parallel processing to speed up workflows. Key Features
The NVIDIA A30 is typically deployed in high-performance computing clusters and AI research labs, where its ability to accelerate neural network training and inference significantly reduces processing time. Its role in these environments is pivotal for advancing AI models and handling data-heavy computations effectively. |
Use Cases |
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The NVIDIA A30 Tensor Core 24GB GPU is primarily utilized in high-performance computing environments such as enterprise data centers and AI research labs. It benefits organizations requiring robust GPU acceleration for complex machine learning models and extensive data analytics, particularly within virtualized or containerized server infrastructures. How It's Used:
By integrating the NVIDIA A30 GPU, organizations can improve computational throughput and memory efficiency, enabling scalable AI workloads with reduced latency. This results in optimized operational performance across diverse server configurations and workload types. |