Deep learning changed the landscape of many applications like computer vision, natural language processing, etc. On the other hand, deep learning require gigantic computing power offered by modern hardware. As a result data scientists rely on powerful hardware resources offered by shared high-performance computing (HPC) clusters or the cloud. Due to the long-running times of deep learning …
Supervisors: Pınar Tözün, Ehsan Yousefzadeh-Asl-Miandoab
Semester: Fall 2023
Tags: machine learning systems, checkpointing, scheduling, resource management

Today many data sources are small low-powered and hardware-constrained devices such as mobile phones, wearable or self-driving smart platforms, etc. Edge computing is a broad term that refers to computations performed on such edge devices. It becomes increasingly important to enable techniques that get more value out of data at the edge rather than always sending the data to a remote and more …
Supervisors: Pınar Tözün, Robert Bayer
Semester: Fall 2023
Tags: resource-constrained hardware, data management, resource management, tinyML