Previous Summer Computing Academies
Summer Computing Academy (2017)
Texas A&M High Performance Research Computing (HPRC) held its first HPRC Summer Computing Academy from July 24 to July 28, 2017. Twenty-one high school students from College Station, its surrounding areas, and even as far as Florida, learned how to program on a Raspberry Pi computer, experimented with cool Pi sensors such as buzzers and LED lights, and even built a computing cluster using the Raspberry Pis. The participants also enjoyed tours of the A&M campus and some of its facilities. To cap it all off there was a reception with cake, ice cream, and sodas for the participants and their parents.
HPRC would like to thank the TAMU community for all their support:
- Texas A&M University Division of Research
- Laboratory for Molecular Simulation
- Texas A&M University Information Technology
- Texas A&M University Engineering Information Technology
We would like to acknowledge the support from NSF project 1730695.
Summer Computing Academy (2018)
We taught 22 high-schoolers programing patterns with a focus on cybersecurity, cryptography and using machine learning for image recognition, We used different pedagogical approaches to teach these topics. We also introduced the students to a virtual reality data center simulation that emphasizes aspects of physical, networking and software cybersecurity.
In terms of successes, we had a few. The maker-space aspects of exercises with image-recognition were a tremendous success with both male and female participants. The participants rapidly went from applying the program to finding ways to throw it off, showing a grasp of the core concepts. We also had a few experiences that will guide us the next time we try to do this again. Overall, it was a fantastic experience Interestingly, our greatest accomplishment may have been of a technical nature. We successfully ran a complete Keras/Tensorflow workflow on a Jupyter notebook on a Raspberry Pi! This includes the training iterations. We think that may well have been the first of its kind. This platform reduces the barrier to machine learning and all the hands-on activities that come with it. At $35 it is affordable for schools and on-the-site training. An extended abstract describing our experiments with different pedagogical approaches has been accepted by the SigHPC workshop at SuperComputing18. The complete paper will appear in the Journal of Computational Science and Education later this year.
