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256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations
256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations
256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations
256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations
Specifications
Brand Name :
Leadtek
Model Number :
RTX A6000
Place of Origin :
China
MOQ :
1pcs
Price :
USD5250-USD5270\PCS
Payment Terms :
L/C, D/A, D/P, T/T
Supply Ability :
20pcs
Delivery Time :
15-30 word days
Packaging Details :
2.713”H x 6.6”L Dual Slot
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
Description

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

256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations

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)

Product tags

pc2 4200 ram

,

pc 2700 ram

,

pc2 3200 ram
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256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations

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Product Detail
Brand Name :
Leadtek
Model Number :
RTX A6000
Place of Origin :
China
MOQ :
1pcs
Price :
USD5250-USD5270\PCS
Payment Terms :
L/C, D/A, D/P, T/T
Contact Supplier
256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations
256 Bit 48G Gpu Graphics Cards Deep Learning GDDR6 Nvidia RTX A6000 For Workstations

Beijing Plink AI Technology Co., Ltd

Active Member
3 Years
beijing, beijing
Since 2009
Business Type :
Manufacturer, Agent, Importer, Exporter, Trading Company
Main Products :
IPC Embedded, Rugged Embedded Computer, Embedded PC Board
Total Annual :
1500000-2000000
Employee Number :
10~30
Certification Level :
Active Member
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