Deep Learning: Introduction and Scaling on HPC Systems
This course is a repetition of the corresponding module of the HiPerCH 11 workshop from September 23-24. It is aimed at researchers and students in academia who are interested in incorporating Deep Learning concepts into their research, and who want to learn how to execute Deep Learning algorithms on HPC clusters.
Please bring your own laptop. The course will be in held English.
The workshop is free of charge. Participants organize their own refreshments during breaks.
The registration is limited to 20 participants.
Update October 4: The course is fully booked. The registration is closed.
9:00 - 13:00 The first half of the course will introduce the concepts of Deep Learning. We will discuss the methods behind neural networks and how to use them set up non-linear models for solving e.g. classification tasks. The basic ideas involved in the process of training neural nets (backpropagation, minimization of loss functions by optimization methods) are treated. We shall further focus on the model evaluation and how to effectively train the model. The course will also cover advanced features of neural networks such as convolutional layers. In the hands-on session participants will train their own neural network using the Keras API of TensorFlow on a classical example of image recognition.
13:00 - 14:00 Break
14:00 - 18:00 In the second part of the course we will treat the basics of parallelizing computations with deep neural networks. Distributing the computational workload allows scaling of deep learning models. We will discuss different scaling approaches that are common when working with large deep learning models or big datasets. Participants will scale their own neural network (using the Keras API of Tensorflow and the distributed deep learning framework Hovorod) over multiple nodes on the Lichtenberg cluster. We will use an introductory example of speech recognition in order to demonstrate the scaling capability of a HPC cluster.
Target group and requirements
- Beginners, basic Python knowlege will be of advantage.
- Familiarity with working on an HPC cluster is desirable.
- Participants are expected to bring their own laptop with either Linux/MacOS or Windows with MobaXterm installed (see downloads for instructions). The workshop includes a hands-on session that will be carried out through an SSH connection.
- For the WiFi connection Eduroam is necessary.
Before registering: Please read the detailed information of the course!
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