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6/30/2021
6/28/2021
CUDA_ARCH_BIN Table for gpu type
CUDA_ARCH_BIN Table for gpu type
Jetson Products
| GPU | Compute Capability |
|---|---|
| Jetson AGX Xavier | 7.2 |
| Jetson Nano | 5.3 |
| Jetson TX2 | 6.2 |
| Jetson TX1 | 5.3 |
| Tegra X1 | 5.3 |
Tesla Workstation Products
| GPU | Compute Capability |
|---|---|
| Tesla K80 | 3.7 |
| Tesla K40 | 3.5 |
| Tesla K20 | 3.5 |
| Tesla C2075 | 2.0 |
| Tesla C2050/C2070 | 2.0 |
Tesla NVIDIA Data Center Products
| GPU | Compute Capability |
|---|---|
| NVIDIA A100 | 8.0 |
| NVIDIA T4 | 7.5 |
| NVIDIA V100 | 7.0 |
| Tesla P100 | 6.0 |
| Tesla P40 | 6.1 |
| Tesla P4 | 6.1 |
| Tesla M60 | 5.2 |
| Tesla M40 | 5.2 |
| Tesla K80 | 3.7 |
| Tesla K40 | 3.5 |
| Tesla K20 | 3.5 |
| Tesla K10 | 3.0 |
Quadro Desktop Products
| GPU | Compute Capability |
|---|---|
| Quadro RTX 8000 | 7.5 |
| Quadro RTX 6000 | 7.5 |
| Quadro RTX 5000 | 7.5 |
| Quadro RTX 4000 | 7.5 |
| Quadro GV100 | 7.0 |
| Quadro GP100 | 6.0 |
| Quadro P6000 | 6.1 |
| Quadro P5000 | 6.1 |
| Quadro P4000 | 6.1 |
| Quadro P2200 | 6.1 |
| Quadro P2000 | 6.1 |
| Quadro P1000 | 6.1 |
| Quadro P620 | 6.1 |
| Quadro P600 | 6.1 |
| Quadro P400 | 6.1 |
| Quadro M6000 24GB | 5.2 |
| Quadro M6000 | 5.2 |
| Quadro K6000 | 3.5 |
| Quadro M5000 | 5.2 |
| Quadro K5200 | 3.5 |
| Quadro K5000 | 3.0 |
| Quadro M4000 | 5.2 |
| Quadro K4200 | 3.0 |
| Quadro K4000 | 3.0 |
| Quadro M2000 | 5.2 |
| Quadro K2200 | 3.0 |
| Quadro K2000 | 3.0 |
| Quadro K2000D | 3.0 |
| Quadro K1200 | 5.0 |
| Quadro K620 | 5.0 |
| Quadro K600 | 3.0 |
| Quadro K420 | 3.0 |
| Quadro 410 | 3.0 |
| Quadro Plex 7000 | 2.0 |
Quadro Mobile Products
| GPU | Compute Capability |
|---|---|
| RTX 5000 | 7.5 |
| RTX 4000 | 7.5 |
| RTX 3000 | 7.5 |
| T2000 | 7.5 |
| T1000 | 7.5 |
| P620 | 6.1 |
| P520 | 6.1 |
| Quadro P5200 | 6.1 |
| Quadro P4200 | 6.1 |
| Quadro P3200 | 6.1 |
| Quadro P5000 | 6.1 |
| Quadro P4000 | 6.1 |
| Quadro P3000 | 6.1 |
| Quadro P2000 | 6.1 |
| Quadro P1000 | 6.1 |
| Quadro P600 | 6.1 |
| Quadro P500 | 6.1 |
| Quadro M5500M | 5.2 |
| Quadro M2200 | 5.2 |
| Quadro M1200 | 5.0 |
| Quadro M620 | 5.2 |
| Quadro M520 | 5.0 |
| Quadro K6000M | 3.0 |
| Quadro K5200M | 3.0 |
| Quadro K5100M | 3.0 |
| Quadro M5000M | 5.0 |
| Quadro K500M | 3.0 |
| Quadro K4200M | 3.0 |
| Quadro K4100M | 3.0 |
| Quadro M4000M | 5.0 |
| Quadro K3100M | 3.0 |
| Quadro M3000M | 5.0 |
| Quadro K2200M | 3.0 |
| Quadro K2100M | 3.0 |
| Quadro M2000M | 5.0 |
| Quadro K1100M | 3.0 |
| Quadro M1000M | 5.0 |
| Quadro K620M | 5.0 |
| Quadro K610M | 3.5 |
| Quadro M600M | 5.0 |
| Quadro K510M | 3.5 |
| Quadro M500M | 5.0 |
NVS Desktop Products
| GPU | Compute Capability |
|---|---|
| NVIDIA NVS 810 | 5.0 |
| NVIDIA NVS 510 | 3.0 |
| NVIDIA NVS 315 | 2.1 |
| NVIDIA NVS 310 | 2.1 |
NVS Mobile Products
GeForce and TITAN Products
GeForce Notebook Products
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* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm... -
CUDA_ARCH_BIN Table for gpu type Jetson Products GPU Compute Capability Jetson AGX Xavier 7.2 Jetson Nano 5.3 Jetson TX2 6.2 Jetson TX1 5.3 ...
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make well divided linear coordinate And make pair coordinate Please see code for detail explanation. import numpy as np import cv2 ... -
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