NVIDIA A2
Features:
- The NVIDIA A2 Tensor Core GPU provides entry-level inference with low power, a small footprint, and high performance for NVIDIA AI at the edge. Featuring a low-profile PCIe Gen4 card and a low 40-60 watt (W) configurable thermal design power (TDP) capability, the A2 brings adaptable inference acceleration to any server.
- A2's versatility, compact size, and low power exceed the demands for edge deployments at scale, instantly upgrading existing entrylevel CPU servers to handle inference. Servers accelerated with A2 GPUs deliver higher inference performance versus CPUs and more efficient intelligent video analytics (IVA) deployments than previous GPU generations—all at an entry-level price point.
- PNY provides unsurpassed service and commitment to its professional graphics customers offering: 3 year warranty, pre- and post-sales support, dedicated Quadro Field Application engineers and direct tech support hot lines.
Specifications:
- Architecture Ampere
- Use Case Universal Deep Learning Acccelerator
- NVIDIA GPU GA107
- GPU Clocks 1440 MHz Base | 1770 MHz Boost
- NVIDIA CUDA Cores 1280
- Tensor Cores 40 | Gen 3
- RT Cores 10 | Gen 2
- Peak FP32 4.5 TFLOPS
- Peak TF32 Tensor Core 9 TFLOPS | 18 TFLOPS Sparsity
- Peak FP16 Tensor Core 18 TFLOPS | 36 TFLOPS Sparsity
- INT8 36 TOPS | 72 TOPS Sparsity
- INT4 72 TOPS | 144 TOPS Sparsity
- GPU Memory 16 GB GDDR6 ECC
- ECC On by Default
- Memory Inferface 128-bit
- Memory Clock 6251 MHz
- Memory Bandwidth 200 GB/s
- Video Encode | Decode 1x Video Encoder | 2x Video Decoder
- CODECs Supported H.265 | H.265| VP9 | AV1 Decode
- Thermal Solution Passive
- Operating Temperature 0 to 50 degrees Centigrade
- Operating Humidity 5% to 85% Relative Humidity
- Maximum Power Consumption 40-60 W | Configurable
- System Interface PCIe Gen 4.0 x8
- Form Factor Low-Profile PCIe | Single Slot
- Physical Dimensions 6.61” L x 2.71” H
- Hardware Root of Trust Yes
- NEBS Ready Level 3
- NVIDIA CUDA Support 11.1 or later
- vGPU Software Revision 14.0 or later
- Virtual GPU (vGPU) Software Support NVIDIA vApps, vPC, vWS, vCS, NVIDIA AI Enterprise
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