Paolo Rech will discuss the reliability of Machine Learning systems at the NSREC 2023 short course entitled “Experimental Evaluation of Artificial Neural Networks Reliability: from GPUs to low-power accelerators”. In this course, Prof. Paolo Rech will review fundamental concepts of Artificial Intelligence, Artificial Neural Networks, and parallel computing devices.
Then, the course will detail the experimental setup required to have a deep and accurate reliability evaluation of an Artificial Neural Networks system. In particular, the guidelines for a successful neutron or heavy ion test of Graphics Processing Units (GPUs) and low-power accelerators, such as Tensor Processing Unit (TPU) or Systolic Arrays, will be provided. Specific attention will be given to the choice of the software, the neural network configuration, the input dataset, and to the experimental results analysis.
See you at NSREC in Kansas City on Monday July 22nd!
If you want a preview, or wish to catch up with what has been presented, you can download the slide set:
