GPU for deep learning
A GPU is a special processor designed to efficiently handle parallel computing tasks. GPUs are widely used especially in deep learning because deep learning algorithms involve a large number of matrix operations and require huge computing power.
Deep learning models consist of many interconnected layers that perform computations on large amounts of data. GPUs can parallelize these calculations, processing many data points simultaneously, significantly speeding up the training process. In contrast, CPUs (Central Processing Units) are optimized for sequential processing and are not as efficient as GPUs for parallel computing tasks.
Using GPUs in deep learning has significantly increased the speed and efficiency of training deep neural networks, enabling the development of more complex and sophisticated models. Many deep learning frameworks, such as TensorFlow, PyTorch, and Keras, are designed to run on GPUs and take advantage of their parallel computing capabilities.
What if we don't have a GPU
But what if we want to learn deep learning modeling without a GPU in our computer?
Google Colab provides us with a solution.
Google Colab provides free and decent GPUs.
So how to get a free GPU for nothing?
1. Login to Google Colab
First log in to Google Colab ( https://colab.research.google.com/ )
2. Create a new notebook
On the notebook, select "Modify" - "Notebook Settings"
Select GPU, then save
In this way, Google Colab can give you a free GPU
3. Check the GPU information through the command
We can see that:
GPU model--Tesla T4
GPU memory---15360MiB
If we want to use SensoFlow or PyTorch to build a deep learning model, to determine whether it has been connected to this GPU, then use the following code to confirm
How to insert code or text: We can choose "Insert" -- "Code Cell" or "Text Cell", as follows
4. Check if TensorFlow and PyTorch are connected to the GPU
Above we have successfully connected tensorflow and PyTorch to the GPU, and queried the GPU information, indicating that we have successfully owned this GPU called Tesla T4!
The next step is to build our model!
