5 papers
DeVIT: Low-Power Vision Transformer Acceleration Using Delta Computation
Reyhaneh Hosseinzadeh, Parham Zilouchian Moghaddam, Mehdi Modarressi
The emergence of transformer-based deep learning models has brought unprecedented performance across various domains, particularly in natural language processing and computer visio…
Reducing the Complexity of Deep Learning Models for EEG Analysis on Wearable Devices
Farough Shayeste Roodi, Parham Zilouchian Moghaddam, Mahdi Mohammadi-nasab +3
Wearable healthcare devices are the fastest-growing Internet of Things (IoT) sector. Many automated healthcare services rely on two crucial biological signals, namely ECG and EEG,…
Ultra Low-Power SDM-based Circuit-Switching for Networks-on-Chip
Meysam Zaeemi, Mehdi Modarressi
In many modern AI chips and multicore systems-on-chip, embedded applications exhibit predictable inter-core traffic behavior that can be characterized at design time. For such appl…
AxLLM: accelerator architecture for large language models with computation reuse capability
Soroush Ahadi, Mehdi Modarressi, Masoud Daneshtalab
Large language models demand massive computational power and memory resources, posing significant challenges for efficient deployment. While quantization has been widely explored t…
A Customized Memory-aware Architecture for Biological Sequence Alignment
Nasrin Akbari, Mehdi Modarressi, Alireza Khadem
Sequence alignment is a fundamental process in computational biology which identifies regions of similarity in biological sequences. With the exponential growth in the volume of da…