Free Shipping upto 10LBS|
30 day return policy|
Customer support
For support call us at
0
No products in cart
Nvidia 900-2G179-2720-101 Ampere Tesla A2 PCIe Graphics 16G Computing Card Deep Learning AI
Expert team support
Bulk InquiryWe accept POs from fortune 1000 companies, government agencies, defense, schools and hospitals.
Description
Specification
Related Products
Reviews
Description
Nvidia 900-2G179-2720-101 Ampere Tesla A2 PCIe Graphics 16G Computing Card Deep Learning AI
NVIDIA 900-2G179-2720-101 Ampere Tesla A2 Pcie Graphics 16g Computing Card Deep Learning Ai Features
Specification
Features
Third-generation Tensor Cores
The Third-generation Tensor Cores In A2 Support Integer Math, Down To Int4, And Floating Point Math, Up To Fp32, To Deliver High Ai Training And Inference Performance. The NVIDIA Ampere Architecture Also Supports Tf32 And NVIDIAS Automatic Mixed Precision (amp) Capabilities.
Root Of Trust Security
Providing Security In Edge Deployments And End-points Is Critical For Enterprise Business Operations. A2 Offers Secure Boot Through Trusted Code Authentication And Hardened Rollback Protections To Protect Against Malicious Malware Attacks.
Second-generation Rt Cores
A2 Includes Dedicated Rt Cores For Ray Tracing That Enable Groundbreaking Technologies At Breakthrough Speed. With Up To 2x The Throughput Over The Previous Generation And The Ability To Concurrently Run Ray Tracing With Either Shading Or Denoising Capabilities.
Hardware Transcoding Performance
Exponential Growth In Video Applications Demand Real-time Scalable Performance, Requiring The Latest In Hardware Encode And Decode Capabilities. A2 Gpus Use Dedicated Hardware To Fully Accelerate Video Decoding And Encoding For The Most Popular Codecs, Including H.265, H.264, Vp9, And Av1 Decode.
Gpu Architecture
NVIDIA Ampere
NVIDIA Rt Cores
10 Rt Cores
Double-precision Performance (fp64)
Not Applicable
Single-precision Performance (tensor Float 32, Tf32)
9 Tflops, 18 Tflops
Half-precision Performance
Fp16: 18 Tflops, 36 Tflops
Bfloat16
18 Tflops, 36 Tflops
Integer Performance
Int8: 36 Tops, 72 Tops, Int4: 72 Tops, 144 Tops
Gpu Memory
16 Gb Gddr6
Memory Bandwidth
200 Gb/sec
Ecc
yes
Interconnect Bandwidth
Not Applicable
System Interface
Pcie Gen 4, X8 Lanes
Form Factor
Pcie Low Profile, Single Width
Multi-instance Gpu (mig)
Not Applicable
Max Power Consumption
40-60 W
Thermal Solution
Passive
Compute Apis
Cuda, Directcompute, Opencl, Openacc