Meilleures alternatives à NVIDIA CUDA GL les mieux notées
Avis sur 39 NVIDIA CUDA GL
Unified Virtual Memory and scattered reads were the features I believe give CUDA GL an edge over other competitors like OpenCL. Avis collecté par et hébergé sur G2.com.
Nothing in particlular, however it would be better if hardware other than NVDIA is also supported. Avis collecté par et hébergé sur G2.com.
faster computing performance. For Cuda programming, NVIDIA CUDA GL is significantly faster than Open CL. Avis collecté par et hébergé sur G2.com.
Some times it suffers from compatibility issues with TensorFlow. Very regress installation process for 3rd party softwares. Avis collecté par et hébergé sur G2.com.
The speed and performance of cuda libs and reliability. Avis collecté par et hébergé sur G2.com.
Nothing but it might help to make the usage more easier for beginners especially for synchronised parallel computing on multiple gpus. Avis collecté par et hébergé sur G2.com.
It is easy to use and reliable. It is also backward compatible. Avis collecté par et hébergé sur G2.com.
None. It is fantastic to use and easy for integration. Maybe accelerating model training speed helps Avis collecté par et hébergé sur G2.com.
Now you can use opengl through cuda. This was long overdue feature Avis collecté par et hébergé sur G2.com.
Cannot comment on performance since I didn't do comparitive analysys. Avis collecté par et hébergé sur G2.com.
Easy to work with and lightweight library. Avis collecté par et hébergé sur G2.com.
Setup is too tiresome. Support for older versions should be present. Cross platform dependency is issue. Avis collecté par et hébergé sur G2.com.
The fact that computing performance is starkly increased when we make use of CUDA GL. It was also very easy to use in a production stack. Avis collecté par et hébergé sur G2.com.
It is not possible to limit GPU resources taken by a container or share GPU between multiple containers. Avis collecté par et hébergé sur G2.com.