The Different Scales of Resource-Aware Deep Learning & How to Tackle Them

Ouvert au grand public Colloque / Congrès / Forum
04.12.2023 11:00

Today, deep learning runs at various scales of hardware resources from the cloud and high-performance computing (HPC) centers to edge and Internet-of-Things (IoT) devices. To achieve resource-aware deep learning, we must understand the needs and challenges of deep learning applications at these different scales. In this talk, we will first investigate ways of improving hardware utilization on modern and powerful CPU-GPU co-processors, which serve as the commodity hardware for deep learning in the cloud and HPC, using workload collocation. Then, we will investigate performance and power trade-offs for deep-learning-based image analysis in space using resource-constrained edge/IoT devices.

Quand? 04.12.2023 11:00
Où? PER 21 E040
Bd de Pérolles 90
1700 Fribourg
Intervenants Prof. Pinar Tözün, IT University of Copenhagen, Denmark
Contact Departement d'informatique
Stephanie Fasel
Bd de Pérolles 90
1700 Fribourg
0263008322 90
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