NVIDIA A10G Graphics Card 24 GB

The A10G is a professional graphics card by NVIDIA, launched on April 12th, 2021. Built on the 8 nm process, and based on the GA102 graphics processor, in its GA102-890-A1 variant, the card supports DirectX 12 Ultimate. The GA102 graphics processor is a large chip with a die area of 628 mm² and 28,300 million transistors. Unlike the fully unlocked GeForce RTX 3090 Ti, which uses the same GPU but has all 10752 shaders enabled, NVIDIA has disabled some shading units on the A10G to reach the product’s target shader count. It features 9216 shading units, 288 texture mapping units, and 96 ROPs. Also included are 288 tensor cores which help improve the speed of machine learning applications. The card also has 72 raytracing acceleration cores. NVIDIA has paired 24 GB GDDR6 memory with the A10G, which are connected using a 384-bit memory interface. The GPU is operating at a frequency of 1320 MHz, which can be boosted up to 1710 MHz, memory is running at 1563 MHz (12.5 Gbps effective).

Being a single-slot card, the NVIDIA A10G draws power from an 8-pin EPS power connector, with power draw rated at 150 W maximum. This device has no display connectivity, as it is not designed to have monitors connected to it. A10G is connected to the rest of the system using a PCI-Express 4.0 x16 interface. The card measures 267 mm in length, 112 mm in width, and features a single-slot cooling solution.

Key Features:

1. Ampere Architecture

• CUDA Cores

• • The A10G features thousands of CUDA Cores (the exact number varies by model), delivering significant parallel processing power for HPC tasks, rendering, and large-scale AI computations.

• Second-Generation RT Cores

• • Delivers accelerated real-time ray tracing, improving the fidelity of lighting, shadows, and reflections for design visualization, media production, and simulation.

• Third-Generation Tensor Cores

• • Provides advanced AI and deep learning capabilities, enabling higher-speed training and inference for tasks like image recognition, natural language processing, and advanced analytics.

2. 24GB GDDR6 Memory (ECC)

• High-Capacity VRAM
  • 24GB of GDDR6 ensures ample memory for large datasets, 3D assets, or multi-stream 4K workloads, especially important for design, media, and AI tasks.
• Error Correction Code (ECC)
  • ECC memory ensures data reliability and accuracy during mission-critical computations, essential in enterprise and scientific environments.

3. AI and Data Science Optimization

• Mixed-Precision Computing
  • Tensor Cores support FP16, BF16, INT8, and TF32, delivering faster computations in training and inferencing while maintaining model accuracy.
• NVIDIA AI Ecosystem
  • Compatible with NVIDIA’s AI software stack (CUDA-X AI, cuBLAS, cuDNN, TensorRT, and more), simplifying model development and deployment across HPC or AI clusters.

4. Professional Visualization and HPC

• Real-Time Ray Tracing
  • Photorealistic rendering for architectural walkthroughs, product design, or VFX workflows, enabling immediate feedback on lighting and shadows.
• HPC-Ready
  • Good double-precision performance (FP64) for scientific simulations in climate modeling, physics research, or molecular dynamics, making it suitable for HPC environments.

5. Data Center and Enterprise Integration

• PCI Express 4.0
  • High-bandwidth interface ensures efficient communication between the GPU and server CPU, reducing data bottlenecks in HPC or AI tasks.
• Virtualization & vGPU
  • Supports virtualization technologies (e.g., NVIDIA vGPU), allowing multiple users to share a single GPU resource in a data center or cloud environment.

6. Energy Efficiency and Thermal Management

• Data Center–Optimized
  • Designed for 24/7 continuous operation, the A10G typically features robust cooling solutions or passively cooled designs in server enclosures.
• Moderate TDP
  • Operates at a balanced TDP, offering powerful performance for HPC and AI with minimal power overhead.

7. Enterprise Reliability & Software Support

• Long-Lifecycle Drivers
  • Enterprise-grade drivers and security patches maintain consistent performance and reliability, crucial for mission-critical or multi-user deployments.
• NVIDIA NGC Compatibility
  • Access to HPC, AI, and data science containers from NVIDIA GPU Cloud (NGC) for streamlined software stacks, easing cluster management and updates.

Applications:

1. Artificial Intelligence & Machine Learning

1. • Deep Learning: Speeds up training large neural networks, leveraging Tensor Cores for mixed-precision computing.
   • Inference: Delivers real-time predictions for recommendation engines, speech recognition, or computer vision tasks.

2. High-Performance Computing (HPC)

1. • Scientific Simulations: Enhances parallel computation in areas like weather modeling, molecular dynamics, or astrophysics.
   • Research Labs: Academic and commercial institutions benefit from faster code execution and shorter iteration cycles.

3. Professional Visualization & Rendering

1. • Real-Time Ray Tracing: Ideal for VR, architectural design, product visualization, and film production, allowing near-instant feedback on lighting and shading.
   • Collaboration: Large memory aids in managing expansive 3D scenes, multi-layered video projects, or massive point-cloud data sets.

4. Enterprise Virtualization

1. • vGPU or Remote Workflows: Partition the A10G among multiple users, delivering GPU-accelerated desktops or containerized applications in data center or hybrid cloud environments.
   • VDI Solutions: Offloads heavy graphics workloads from client endpoints, enabling smooth 3D or AI experiences on thin clients or remote devices.

5. Data Analytics & Edge Computing

1. • Big Data Processing: Amplifies analytics pipelines, harnessing GPU acceleration for real-time insight generation.
   • Edge Inference: Deploy the A10G at the network edge for accelerated local inferencing tasks, reducing latency and bandwidth usage to central data centers.

Why Choose the NVIDIA A10G Graphics Card 24 GB?

1. Robust AI & HPC Performance

1. • Combines Ampere architecture’s advanced CUDA, Tensor, and RT Cores with a significant 24GB memory pool, ensuring top-tier acceleration for broad workloads.

2. Versatile Data Center Integration

1. • Standard PCIe form factor and enterprise driver support let you insert the A10G seamlessly into existing server infrastructures, HPC clusters, or cloud-based systems.

3. 24GB ECC Memory for Complex Workloads

1. • Enough capacity to handle large neural network training sets, HPC simulations, or multi-4K video streams without frequent memory constraints.

4. Enterprise Reliability & Security

1. • Managed via stable, long-lifecycle driver branches, the A10G meets enterprise demands for continuous operation and minimal downtime.

5. Future-Ready Architecture

1. • Ampere-based features, including second-gen ray tracing and advanced mixed-precision AI, keep the A10G relevant as data center workloads continue evolving.