8 papers
Non-frontal face recognition using GANs and memristor-based classifiers
Semih Vazgecen, Cristian Sestito, Spyros Stathopoulos +1
Face recognition systems have advanced significantly through deep learning techniques, delivering high performance and robustness in complex scenarios. However, these approaches in…
D-Legion: A Scalable Many-Core Architecture for Accelerating Matrix Multiplication in Quantized LLMs
Ahmed J. Abdelmaksoud, Cristian Sestito, Shiwei Wang +1
The performance gains obtained by large language models (LLMs) are closely linked to their substantial computational and memory requirements. Quantized LLMs offer significant advan…
ADiP: Adaptive-Precision Systolic Array for Matrix Multiplication Acceleration
Ahmed J. Abdelmaksoud, Cristian Sestito, Shiwei Wang +1
Transformers are at the core of modern AI nowadays. They rely heavily on matrix multiplication and require efficient acceleration due to their substantial memory and computational…
A flexible language model-assisted electronic design automation framework
Cristian Sestito, Panagiota Kontou, Pratibha Verma +5
Large language models (LLMs) are transforming electronic design automation (EDA) by enhancing design stages such as schematic design, simulation, netlist synthesis, and place-and-r…
TrIM, Triangular Input Movement Systolic Array for Convolutional Neural Networks: Dataflow and Analytical Modelling
Cristian Sestito, Shady Agwa, Themis Prodromakis
In order to follow the ever-growing computational complexity and data intensity of state-of-the-art AI models, new computing paradigms are being proposed. These paradigms aim at ac…
3D-TrIM: A Memory-Efficient Spatial Computing Architecture for Convolution Workloads
Cristian Sestito, Ahmed J. Abdelmaksoud, Shady Agwa +1
The Von Neumann bottleneck, which relates to the energy cost of moving data from memory to on-chip core and vice versa, is a serious challenge in state-of-the-art AI architectures,…