DESCRIPTION
NVIDIA A30 Tensor Core GPU: Redefining Enterprise Applications
As an advanced accelerator, the NVIDIA A30 Tensor Core GPU is built to deliver superior performance and energy efficiency in enterprise applications. Leveraging the NVIDIA Ampere architecture, the A30 excels in AI inference, deep learning training, high-performance computing (HPC), and data analytics.
AI Performance That Delivers
With up to 3x higher throughput for AI training compared to the V100 and a staggering 6x improvement over the T4, the NVIDIA A30 is a game-changer for handling large AI models like conversational AI systems. Its support for Tensor Float (TF32) and automatic mixed precision further enhance training speeds, making it ideal for businesses scaling their AI operations. This substantial increase in throughput leads to faster training times and more efficient resource use.
Unmatched Inference Power
Accelerating workloads across a broad range of precision levels, from FP64 to INT4, the NVIDIA A30 supports up to four simultaneous Multi-Instance GPU (MIG) instances. This ability to partition resources enables real-time AI inference in diverse, scalable enterprise environments. With MIG, enterprises can maximize GPU utilization while ensuring quality of service (QoS) across various AI and data-intensive tasks.
Streamlined AI Deployments
Low-latency, high-throughput AI deployments are made easy with NVIDIA Triton Inference Server and TensorRT. These tools, optimized for deep learning models, allow the NVIDIA A30 to integrate seamlessly into AI-driven workflows, reducing complexity and deployment times. This ensures that AI models are delivered with speed and accuracy, helping businesses to innovate faster while reducing overhead.
HPC and Memory Muscle
Supporting FP64 Tensor Cores, the NVIDIA A30 is ideal for double-precision calculations required in scientific simulations, making it a go-to choice for research institutions and enterprises running compute-heavy tasks. With 24GB of HBM2 memory and 933GB/s of memory bandwidth, it can handle large datasets and solve complex problems with ease, enabling faster insights and results in fields such as medical research, climate modeling, and financial simulations.
Scalability That Grows With You
The NVIDIA A30 offers flexible partitioning with up to four isolated GPU instances, each with dedicated resources for AI workloads. Combined with next-gen NVLink technology, which doubles the bandwidth between multiple A30 GPUs, this architecture delivers unmatched scalability for large AI and HPC tasks. The A30’s ability to scale with enterprise demands makes it a perfect fit for dynamic environments that require flexible, on-demand computing power.
Efficiency Without Compromise
Designed for energy efficiency and enterprise-grade reliability, the NVIDIA A30 integrates with NVIDIA AI Enterprise and VMware vSphere to provide seamless operation in virtualized environments. With a power draw of just 165W and a passive cooling system, it ensures efficient operation without compromising performance. The A30’s reliability and low power consumption make it suitable for large-scale deployments where operational costs and sustainability are key considerations.
Specifications That Matter
Supporting both Linux (R460.65+) and Windows (R461.98+) drivers, alongside CUDA 11.3+, the NVIDIA A30 ensures broad software compatibility. Its dual-slot form factor with passive cooling allows for easy integration into standard data center setups, while its CPU 8-pin auxiliary power connector and programmable power management offer flexibility. This level of adaptability ensures that the A30 can meet the needs of both current and future infrastructure setups.
Built for Compatibility
The NVIDIA A30 integrates smoothly into existing enterprise infrastructures, making it a versatile choice for standard server environments. With support from NVIDIA AI Enterprise, it aligns effortlessly with modern virtualized and cloud-native architectures, reducing downtime and enhancing operational efficiency. Whether for on-premise data centers or hybrid cloud setups, the A30’s compatibility ensures businesses can future-proof their AI and HPC investments.
Certified for Compliance
Globally recognized certifications such as WHQL, EU RoHS, and CE ensure that the NVIDIA A30 meets strict standards for safety and reliability in international markets. This means that enterprises deploying the A30 can confidently operate, knowing that it complies with regulatory requirements for sustainability, safety, and environmental impact. Additionally, the A30’s agency approvals, including FCC and UL, further reinforce its commitment to high operational standards.
NVIDIA A30: The Enterprise Powerhouse
For AI and HPC-heavy data centers, the NVIDIA A30 offers a powerful, efficient solution designed to help enterprises scale and optimize their operations. With its balance of performance, scalability, and energy efficiency, the A30 is a versatile tool for businesses looking to push the boundaries of AI and computational power. Whether accelerating AI workloads or handling complex simulations, the A30 delivers the performance that modern enterprises need.
SPECIFICATIONS
A30 GPU Product Specifications
- SKU: P1001 SKU 205
- NVPN: 699-21001-0205-xxx
- Power: 165 W (total board power)
- Thermal Solution: Passive (requires system airflow)
- Form Factor: Full-height, full-length (10.5″), dual-slot
PCI Express Interface
- PCI Express Version: PCIe 4.0 ×16
- Lane and Polarity Reversal: Supported
GPU Clocks
- Base Clock: 930 MHz
- Boost Clock: 1440 MHz
VBIOS and UEFI
- VBIOS Size: 8 Mbit EEPROM
- UEFI Support: Yes
Multi-Instance GPU (MIG) Support
- MIG Support: Yes, up to four instances
Power Connector
- Connector Type: One CPU 8-pin auxiliary power connector
Security and Zero Power Support
- NEBS Readiness: Supported
Memory Specifications
- Memory Type: HBM2 (High Bandwidth Memory)
- Memory Size: 24 GB
- Memory Bandwidth: 933 GB/s
- Memory Bus Width: 3072 bits
- Memory Clock: 1215 MHz
Software Specifications
- SR-IOV Support: Yes, up to 8 virtual functions (VFs)
- BAR Address (Physical Function): BAR0: 16 MiB, BAR1: 32 GiB, BAR3: 32 MiB
- BAR Address (Virtual Function): BAR0: 2 MiB, BAR1: 32 GiB (4 GiB per VF), BAR3: 256 MiB (32 MiB per VF)
- Driver Support (Linux): R460.65 or later
- Driver Support (Windows): R461.98 or later
- CUDA Support: Version 11.3 or later
- Virtual GPU Support: Supports vGPU 13.0 or later (NVIDIA Virtual Compute Server Edition)
- AI Enterprise: Supported with VMware
- Secure Boot: Supported
Environmental and Reliability Specifications
- Operating Temperature: 0 °C to 55 °C
- Short-Term Operating Temperature: -5 °C to 55 °C for up to 96 hours
- Storage Temperature: -40 °C to 75 °C
- Operating Humidity: 5% to 85% relative humidity
- Short-Term Operating Humidity: 5% to 93%
- Storage Humidity: 5% to 95% relative humidity
- MTBF (Mean Time Between Failures) – Uncontrolled Environment: 1,116,869 hours at 35 °C
- MTBF (Mean Time Between Failures) – Controlled Environment: 1,293,630 hours at 35 °C
Airflow Specifications
- Airflow Direction: Bidirectional heat sink supports airflow from either left-to-right or right-to-left
Resources
INCLUDED
WARRANTY
- 1-Year BrightStar warranty for end user customers
- 90-Day BrightStar Warranty for resellers
SHIPPING
- Free FedEx Ground shipping within the United States
- FedEx Overnight shipping available as well
- FedEx International Shipping available for customers outside of the United States
FAQS
The NVIDIA A30 Tensor Core GPU is an enterprise-grade accelerator designed for AI inference, deep learning, high-performance computing (HPC), and data analytics. Built on NVIDIA’s Ampere architecture, it offers superior energy efficiency and scalability, making it ideal for enterprise data centers handling diverse workloads.
The NVIDIA A30 features 24GB of HBM2 memory, providing a high memory bandwidth of 933GB/s, which is essential for handling large datasets and complex AI models.
Yes, the NVIDIA A30 supports next-generation NVLink, which doubles the bandwidth between GPUs, enabling seamless scaling and improved performance for multi-GPU setups in AI and HPC environments.
The NVIDIA A30X is a higher-end variant designed for more specialized tasks, offering additional features or performance boosts over the standard A30 model, although it’s not a widely recognized configuration as of the current product lineup.
The NVIDIA A30 delivers up to 3x higher AI training throughput compared to the V100, while also providing energy efficiency and support for features like Multi-Instance GPU (MIG), making it more suitable for scalable enterprise workloads.
The Nvidia A2 is designed for low-power edge inference, whereas the NVIDIA A30 is suited for high-performance enterprise workloads. The A30’s advanced Tensor Core technology and larger memory make it ideal for complex AI models and large-scale analytics.
The T4 is built for lighter workloads and edge computing, while the NVIDIA A30 performs significantly better in AI training, inference, and data center environments, with support for MIG and greater memory bandwidth.
The NVIDIA A10 targets mainstream AI inference, while the NVIDIA A30 excels in AI training and HPC, offering features like Multi-Instance GPU (MIG) and higher memory bandwidth, making it better for diverse enterprise workloads.
Compared to Nvidia14 models, the NVIDIA A30 is specialized for enterprise AI and HPC needs. Its Tensor Core architecture and high memory bandwidth provide an edge in data center performance.
The A40 is optimized for professional visualization, whereas the NVIDIA A30 is more focused on AI, HPC, and data analytics. Although both support NVLink, the A30 is more efficient for AI-heavy environments.
The A100 is designed for extreme AI and HPC workloads. The NVIDIA A30 strikes a balance between power efficiency and computational power, ideal for enterprises that need strong AI capabilities without the full power of the A100.
Yes, the NVIDIA A30 is suitable for SMEs, offering a balanced mix of performance and energy efficiency. Its scalability via MIG and support for AI and HPC workloads make it accessible for businesses with growing computational needs.
Yes, the NVIDIA A30 supports integration with virtualized environments such as VMware vSphere and works seamlessly with NVIDIA AI Enterprise, enabling smooth deployment in hybrid cloud and virtualized data centers.
The NVIDIA A30 has a power draw of 165 watts and relies on passive cooling, making it energy efficient for large data centers. It requires a CPU 8-pin auxiliary power connector and airflow through the system for proper cooling.
The NVIDIA A30 excels in AI inference, deep learning training, high-performance computing (HPC), and data analytics. It’s optimized for workloads that require scalability, high memory bandwidth, and double-precision calculations, making it ideal for enterprise data centers.
Key benefits of the NVIDIA A30 include superior AI and HPC performance, energy efficiency, scalability via MIG, and support for NVLink. It integrates seamlessly with AI software, making it highly versatile for enterprise data centers.
