13 citations · 25 across the 3 of their papers we have counts for
3 papers
cs.AR2023★ 10 cited
VEDLIoT -- Next generation accelerated AIoT systems and applications
Kevin Mika, René Griessl, Nils Kucza +29
The VEDLIoT project aims to develop energy-efficient Deep Learning methodologies for distributed Artificial Intelligence of Things (AIoT) applications. During our project, we propo…
cs.AR2022★ 13 cited
VEDLIoT: Very Efficient Deep Learning in IoT
Martin Kaiser, Rene Griessl, Nils Kucza +33
The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also deali…
cs.DC2019★ 2 cited
LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing
B. Salami, K. Parasyris, A. Cristal +42
The LEGaTO project leverages task-based programming models to provide a software ecosystem for Made in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engi…