Name: 0RV08M Dell NVIDIA A30 Tensor Core 24GB HBM2 Accelerator GPU Graphics Card
Brand: Dell
SKU: 0RV08M
Price: 3450.00 USD
Availability: InStock
Rating: 4.8 (119 reviews)

Product Overview
The Dell NVIDIA A30 Tensor Core GPU Accelerator serves as a powerful graphics card designed for AI and HPC tasks. It fits into data center servers where high performance and memory capacity are necessary to manage large-scale computations efficiently.

General Information
Brand	Dell
Part Number	0RV08M

Technical Information
Chipset	Nvidia

Memory
Memory Size	24GB
Interface	HBM2

Miscellaneous
Assembly Required	Yes
Eco Friendly	Yes
Compliance Standards	WEEE, RoHS, cURus, CE, FCC, CCC, UL, TUV, cULus, CSA, cUL

Physical Characteristics
Weight	3.00
Condition	Refurbished

Product Description
The Dell NVIDIA A30 Tensor Core GPU Accelerator is built for demanding computational tasks like AI training, deep learning inference, and high-performance computing. It packs 24GB of high-bandwidth memory (HBM2) and advanced Tensor Cores to handle large datasets and complex calculations efficiently. Often found in data centers and enterprise servers, this GPU is tailored for professionals working on machine learning models, data analytics, and scientific simulations. Its design prioritizes performance per watt and scalability in multi-GPU configurations. Key Features 24GB HBM2 memory delivers fast data access for intensive workloads Tensor Cores accelerate AI and deep learning computations Supports multi-instance GPU for flexible resource allocation Compatible with leading deep learning frameworks and libraries Efficient thermal design suited for dense server environments This accelerator is commonly deployed in enterprise-level servers where large-scale AI projects and complex simulations require robust computation. Its real-world role is to speed up tasks that benefit from parallel processing and high memory bandwidth, helping researchers and developers reduce turnaround times.

Use Cases
The Dell NVIDIA A30 Tensor Core GPU Accelerator is predominantly utilized in high-density data center environments where AI model training and inference, as well as HPC simulations, require substantial computational throughput and memory bandwidth. Enterprises running complex machine learning workloads or scientific computing benefit from its integration in server racks optimized for parallel processing. How It's Used: Accelerating large-scale AI training tasks in enterprise data centers to reduce model development time. Enhancing inference performance in cloud service provider environments to support real-time analytics. Powering HPC simulations in research institutions that demand high memory capacity and compute precision. Supporting virtualization platforms in multi-tenant data centers requiring secure GPU sharing. Enabling edge data centers to perform AI workloads locally with minimized latency and bandwidth use. By deploying the Dell NVIDIA A30 GPU in these scenarios, organizations can achieve improved operational efficiency and scalability for demanding compute workloads. Its architecture ensures sustained performance across diverse AI and HPC applications, aligning with the rigorous demands of modern data center infrastructures.