| Place of Origin: | China |
|---|---|
| Brand Name: | Leadtek |
| Model Number: | RTX A6000 |
| Minimum Order Quantity: | 1pcs |
| Price: | USD5250-USD5270\PCS |
| Packaging Details: | 2.713”H x 6.6”L Dual Slot |
| Delivery Time: | 15-30 word days |
| Payment Terms: | L/C, D/A, D/P, T/T |
| Supply Ability: | 20pcs |
| NAME: | 256bit 48G Deep Learning GDDR6 Nvidia RTX A6000 GPU Graphics Cards For Workstations | Keyword: | 256bit 48G Deep Learning GDDR6 Nvidia RTX A6000 GPU Graphics Cards For Workstations |
|---|---|---|---|
| Model: | NVIDIA Quadro RTX A6000 | GPU Architecture: | NVIDIA Ampere Architecture |
| CUDA Parallel Processing Cores: | 10,752 | GPU Memory: | 48 GB GDDR6 With ECC |
| Max Power Consumption: | 300 W | Power Connector: | 1x 8-pin CPU |
| Display Connectors: | DP 1.4 (4) | Memory Interface: | 384-bit |
| Form Factor: | 4.4" H X 10.5" L Dual Slot | Product Weight: | 1.179 Kg |
| Graphics Bus: | PCI Express 4.0 X16 | ||
| High Light: | 256 Bit Gpu Graphics Cards,48G Gpu Graphics Cards,Nvidia RTX A6000 Gddr6 Graphics Cards |
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256bit 48G Deep learning GDDR6 Nvidia RTX A6000 GPU Graphics Cards For Workstations
NVIDIA RTX A6000 48GB Gpu Graphics Cards
A6000 Gpu Graphics Cards for deep learning
The NVIDIA Ampere architecture’s CUDA cores bring up to 2X the single-precision floating point (FP32) throughput compared to the previous generation, providing significant performance improvements for graphics workflows such as 3D model development and compute for workloads such as desktop simulation for computer-aided engineering (CAE). The RTX A6000 enables two FP32 primary data paths, doubling the peak FP32 operations.
Third-Generation Tensor Cores
Purpose-built for deep learning matrix arithmetic at the heart of neural network training and inferencing functions, the RTX A6000 includes enhanced Tensor Cores that accelerate more datatypes, and includes a new Fine-Grained Structured Sparsity feature that delivers up to 2X throughput for tensor matrix operations compared to the previous generation. New Tensor Cores will accelerate two new TF32 and BFloat16 precision modes. Independent floating-point and integer data paths allow more efficient execution of workloads using a mix of computation and addressing calculations.
Scale Application Performance with NVLink Technology
NVIDIA RTX A6000 Gpu Graphics Cards Specification
|
GPU Architecture |
Ampere |
|
CUDA Parallel Processing cores |
10,752 |
|
NVIDIA Tensor Cores |
336 |
|
NVIDIA RT Cores |
84 |
|
GPU Memory |
48 GB GDDR6 with ECC |
|
NVENC | NVDEC |
1x | 2x (+AV1 decode) |
|
Single-Precision Performance |
38.7 TFLOPS |
|
RT Core Performance |
75.6 TFLOPS |
|
Tensor Performance |
309.7 TFLOPS |
|
Memory Interface |
384-bit |
|
Memory Bandwidth |
768 GB/s |
|
Max Power Consumption |
300 W |
|
NVLink Interconnect |
112.5 GB/s (bidirectional) |
|
Graphics Bus |
PCI Express 4.0 x16 |
|
Form Factor |
4.4" H x 10.5" L Dual Slot |
|
Product Weight |
1.179 kg |
|
Thermal Solution |
Active |
|
vGPU Profiles Supported |
1 GB, 2 GB, 3 GB, 4 GB, 6 GB, 8 GB, 12 GB, 16 GB, 24 GB, 48 GB |
|
Power Connector |
1x 8-pin CPU |
|
Frame lock |
Compatible (with Quadro Sync II) |
