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NVIDIA RTX A6000
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Users say:
This product has been praised for its performance and cooling capabilities, with many customers noting that it is perfect for deep learning and 3D rendering. It is also praised for its high price and large batch sizes, making it a great value for the money. However, some customers have noted that the NVLINK bridge is not ideal for inference tasks.
NVIDIA Ampere Architecture-based CUDA Cores - Double-speed processing for single-precision floating point (FP32) operations and improved power efficiency provide significant performance improvements for graphics and simulation workflows, such as complex 3D computer-aided design (CAD) and computer-aided engineering …
NVIDIA Ampere Architecture-based CUDA Cores - Double-speed processing for single-precision floating point (FP32) operations and improved power efficiency provide significant performance improvements for graphics and simulation workflows, such as complex 3D computer-aided design (CAD) and computer-aided engineering (CAE), on the desktop. Second-Generation RT Cores - With up to 2X the throughput over the previous generation and the ability to concurrently run ray tracing with either shading or denoising capabilities, second-generation RT Cores deliver massive speedups for workloads like photorealistic rendering of movie content, architectural design evaluations, and virtual prototyping of product designs. This technology also speeds up the rendering of ray-traced motion blur for faster results with greater visual accuracy. Third-Generation Tensor Cores - New Tensor Float 32 (TF32) precision provides up to 5X the training throughput over the previous generation to accelerate AI and data science model training without requiring any code changes. Hardware support for structural sparsity doubles the throughput for inferencing. Tensor Cores also bring AI to graphics with capabilities like DLSS, AI denoising, and enhanced editing for select applications. Third-Generation NVIDIA NVLink - Increased GPU-to-GPU interconnect bandwidth provides a single scalable memory to accelerate graphics and compute workloads and tackle larger datasets. 48 Gigabytes (GB) of GPU Memory - Ultra-fast GDDR6 memory, scalable up to 96 GB with NVLink, gives data scientists, engineers, and creative professionals the large memory necessary to work with massive datasets and workloads like data science and simulation.
Review summary
AI-generated content
This product has been praised for its performance and cooling capabilities, with many customers noting that it is perfect for deep learning and 3D rendering. It is also praised for its high price and large batch sizes, making it a great value for the money. However, some customers have noted that the NVLINK bridge is not ideal for inference tasks.
Pros
- Excellent for 3D rendering
- Large batch sizes
- Quiet operation
- Good for AI/ML research
- Energy efficient
Cons
- Overheating issues
- Requires two VGA power feeds
- No instructions included
- Expensive
Read original reviews
Description
NVIDIA Ampere Architecture-based CUDA Cores - Double-speed processing for single-precision floating point (FP32) operations and improved power efficiency provide significant performance improvements for graphics and simulation workflows, such as complex 3D computer-aided design (CAD) and computer-aided engineering (CAE), on the desktop. Second-Generation RT Cores - With up to 2X the throughput over the previous generation and the ability to concurrently run ray tracing with either shading or denoising capabilities, second-generation RT Cores deliver massive speedups for workloads like photorealistic rendering of movie content, architectural design evaluations, and virtual prototyping of product designs. This technology also speeds up the rendering of ray-traced motion blur for faster results with greater visual accuracy. Third-Generation Tensor Cores - New Tensor Float 32 (TF32) precision provides up to 5X the training throughput over the previous generation to accelerate AI and data science model training without requiring any code changes. Hardware support for structural sparsity doubles the throughput for inferencing. Tensor Cores also bring AI to graphics with capabilities like DLSS, AI denoising, and enhanced editing for select applications. Third-Generation NVIDIA NVLink - Increased GPU-to-GPU interconnect bandwidth provides a single scalable memory to accelerate graphics and compute workloads and tackle larger datasets. 48 Gigabytes (GB) of GPU Memory - Ultra-fast GDDR6 memory, scalable up to 96 GB with NVLink, gives data scientists, engineers, and creative professionals the large memory necessary to work with massive datasets and workloads like data science and simulation.
Specifications
| Brand | Nvidia |
| Model | Vcnrtxa6000-pb |
| Memory Size | 48 Gb |
| Output Ports | Hdmi |
| Graphics Card Ram Size | 48 Gb |
| Item Weight | 2.6 Pounds |
| Graphics Processor Manufacturer | Nvidia |
| Product Dimensions | 15 X 3.3 X 9.5 Inches |
| Item Dimensionslxwxh | 15 X 3.3 X 9.5 Inches |
| Date First Available | July 16, 2021 |
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