NVIDIA A30: Unleashing AI and HPC Power for Enterprise Workloads
The NVIDIA A30 Tensor Core GPU redefines what enterprise-level performance means for AI inference, high-performance computing (HPC), and data analytics. Built on the NVIDIA Ampere architecture, it is engineered to accelerate workloads of all scales, offering a powerful combination of performance, flexibility, and efficiency. Whether it's deep learning, video processing, or AI-driven analytics, the A30 delivers unmatched capabilities, making it a game-changer for data centres and enterprise environments.
NVIDIA Ampere Architecture
The NVIDIA A30 GPU leverages the power of the Ampere architecture, providing versatile capabilities to handle diverse acceleration needs. From partitioning tasks using Multi-Instance GPU (MIG) to connecting multiple GPUs via NVIDIA NVLink for large-scale workloads, the A30 ensures consistent, reliable performance across data centre applications. This architecture allows IT managers to maximise GPU utility and operational efficiency around the clock.
Third-Generation Tensor Cores
The A30 is equipped with third-generation Tensor Cores, delivering 165 TFLOPS of TF32 deep learning performance. This translates to 20x higher AI training throughput and over 5x more inference performance compared to previous-generation GPUs like the NVIDIA T4. For HPC applications, the A30 provides 10.3 TFLOPS of performance, making it a robust solution for AI-driven and compute-heavy operations.
| GPU Chipset Manufacturer | NVIDIA |
| RAM Bus Width | 3072 |
| Render Ouput Units (ROPs) | 96 |
| Texture Mapping Units (TMUs) | 224 |
| GPU Cores | 3584 |
| Cooling Component | Heatsink only |
| TDP | 160W |
| GPU Memory Size | 24 GB |
| GPU Memory Type | HBM2 |
| Compatible Port | PCI Express 4.0 x16 |
| Card Form Factor | Full Height |
| Power Cable Requirement | 8-Pin CPU EPS |
Full technical specifications can be found on the NVIDIA A30 data sheet.
Multi-Instance GPU (MIG)
With Multi-Instance GPU capabilities, an A30 GPU can be partitioned into up to four separate GPU instances, each with dedicated high-bandwidth memory, cache, and compute cores. This allows organisations to optimise GPU usage and meet the needs of both large and small workloads, providing flexible and secure quality of service.
High-Bandwidth Memory (HBM2)
Featuring up to 24GB of HBM2 memory and delivering a memory bandwidth of 933 GB/s, the A30 is optimised for a wide array of AI and HPC workloads. This high-bandwidth memory ensures rapid data access, making it highly effective for large datasets and intensive computing tasks.
Next-Generation NVLink
NVIDIA’s next-gen NVLink allows for up to 2x higher throughput compared to previous iterations. Two A30 GPUs can be paired using NVLink to achieve 330 TFLOPS of deep learning performance, ensuring seamless scalability for demanding applications.
Performance Capabilities
The A30 GPU boasts impressive performance capabilities tailored for enterprise workloads, operating within a low 165W power envelope. With support for various floating-point and integer precision levels, including FP16, FP32, and TF32, it accommodates a diverse range of workloads seamlessly.
The combination of MIG technology and third-generation Tensor Cores provides secure quality of service and elasticity for data center applications. Whether you’re running AI models, complex simulations, or enterprise analytics, the A30 delivers consistent, reliable performance tailored to your unique needs.
Supporting PCIe Gen4 and third-generation NVLink interconnects, it ensures fast data transfer rates and seamless multi-GPU connectivity for large-scale deployments. The A30’s ability to run multiple GPU instances, each with its own memory and compute cores, offers unparalleled flexibility for scaling applications and workloads.
Shop the NVIDIA A30 Tensor Core 24GB GPU.
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Learn More
NVIDIA A30 Tensor Core GPU Data Sheet PDF
Official NVIDIA A30 webpage