4 citations · 9 across the 7 of their papers we have counts for
5 papers · 1 filter
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models
Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler +4
The increasing size of language models necessitates a thorough analysis across multiple dimensions to assess trade-offs among crucial hardware metrics such as latency, energy consu…
Multi-objective Differentiable Neural Architecture Search
Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler +3
Pareto front profiling in multi-objective optimization (MOO), i.e., finding a diverse set of Pareto optimal solutions, is challenging, especially with expensive objectives that req…
Bag of Tricks for Neural Architecture Search
Thomas Elsken, Benedikt Staffler, Arber Zela +2
While neural architecture search methods have been successful in previous years and led to new state-of-the-art performance on various problems, they have also been criticized for…
Bosch Deep Learning Hardware Benchmark
Armin Runge, Thomas Wenzel, Dimitrios Bariamis +3
The widespread use of Deep Learning (DL) applications in science and industry has created a large demand for efficient inference systems. This has resulted in a rapid increase of a…
Meta-Learning of Neural Architectures for Few-Shot Learning
Thomas Elsken, Benedikt Staffler, Jan Hendrik Metzen +1
The recent progress in neural architecture search (NAS) has allowed scaling the automated design of neural architectures to real-world domains, such as object detection and semanti…