137 citations · 331 across the 17 of their papers we have counts for
4 papers · 1 filter
Towards making the most of NLP-based device mapping optimization for OpenCL kernels
Petros Vavaroutsos, Ioannis Oroutzoglou, Dimosthenis Masouros +1
Nowadays, we are living in an era of extreme device heterogeneity. Despite the high variety of conventional CPU architectures, accelerator devices, such as GPUs and FPGAs, also app…
Hardware Approximate Techniques for Deep Neural Network Accelerators: A Survey
Giorgos Armeniakos, Georgios Zervakis, Dimitrios Soudris +1
Deep Neural Networks (DNNs) are very popular because of their high performance in various cognitive tasks in Machine Learning (ML). Recent advancements in DNNs have brought beyond…
Cross-Layer Approximation For Printed Machine Learning Circuits
Giorgos Armeniakos, Georgios Zervakis, Dimitrios Soudris +2
Printed electronics (PE) feature low non-recurring engineering costs and low per unit-area fabrication costs, enabling thus extremely low-cost and on-demand hardware. Such low-cost…
AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch
Dimitrios Danopoulos, Georgios Zervakis, Kostas Siozios +2
Current state-of-the-art employs approximate multipliers to address the highly increased power demands of DNN accelerators. However, evaluating the accuracy of approximate DNNs is…