# CUDA_3D

**Repository Path**: stophin/CUDA_3D

## Basic Information

- **Project Name**: CUDA_3D
- **Description**: CUDA 3D using Nvidia GPU
- **Primary Language**: C++
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2018-06-02
- **Last Updated**: 2020-12-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# CUDA_3D  
  
#### 项目介绍  
CUDA 3D using Nvidia GPU  
  
NOTE:    
When using double instead of float, there will be less noise. Remember to set nvcc to sm_60 to support double.    
Supported SM and Gencode variations  
Supported on CUDA 7 and later  
Fermi (CUDA 3.2 and later, deprecated from CUDA 9):  
SM20 or SM_20, compute_30 – Older cards such as GeForce 400, 500, 600, GT-630  
Kepler (CUDA 5 and later):  
SM30 or SM_30, compute_30 – Kepler architecture (generic – Tesla K40/K80, GeForce 700, GT-730)  
Adds support for unified memory programming  
SM35 or SM_35, compute_35 – More specific Tesla K40  
Adds support for dynamic parallelism. Shows no real benefit over SM30 in my experience.  
SM37 or SM_37, compute_37 – More specific Tesla K80  
Adds a few more registers. Shows no real benefit over SM30 in my experience  
Maxwell (CUDA 6 and later):  
SM50 or SM_50, compute_50 – Tesla/Quadro M series  
SM52 or SM_52, compute_52 – Quadro M6000 , GeForce 900, GTX-970, GTX-980, GTX Titan X  
SM53 or SM_53, compute_53 – Tegra (Jetson) TX1 / Tegra X1  
Pascal (CUDA 8 and later)  
SM60 or SM_60, compute_60 – GP100/Tesla P100 – DGX-1 (Generic Pascal)  
SM61 or SM_61, compute_61 – GTX 1080, GTX 1070, GTX 1060, GTX 1050, GTX 1030, Titan Xp, Tesla P40, Tesla P4  
SM62 or SM_62, compute_62 – Drive-PX2, Tegra (Jetson) TX2, Denver-based GPU  
Volta (CUDA 9 and later)  
SM70 or SM_70, compute_70 – Tesla V100  
SM71 or SM_71, compute_71 – probably not implemented  
SM72 or SM_72, compute_72 – currently unknown