2 papers
cs.AR2026
Exploiting temporal parallelism for LSTM Autoencoder acceleration on FPGA
Aimilios Leftheriotis, Dimosthenis Masouros, Dimitrios Soudris +1
Recurrent Neural Networks (RNNs) are vital for sequential data processing. Long Short-Term Memory Autoencoders (LSTM-AEs) are particularly effective for unsupervised anomaly detect…
cs.LG2024
TF2AIF: Facilitating development and deployment of accelerated AI models on the cloud-edge continuum
Aimilios Leftheriotis, Achilleas Tzenetopoulos, George Lentaris +2
The B5G/6G evolution relies on connect-compute technologies and highly heterogeneous clusters with HW accelerators, which require specialized coding to be efficiently utilized. The…