4 citations · 4 across the 5 of their papers we have counts for
5 papers
GCN-ABFT: Low-Cost Online Error Checking for Graph Convolutional Networks
Christodoulos Peltekis, Giorgos Dimitrakopoulos
Graph convolutional networks (GCNs) are popular for building machine-learning application for graph-structured data. This widespread adoption led to the development of specialized…
Floating-Point Multiply-Add with Approximate Normalization for Low-Cost Matrix Engines
Kosmas Alexandridis, Christodoulos Peltekis, Dionysios Filippas +1
The widespread adoption of machine learning algorithms necessitates hardware acceleration to ensure efficient performance. This acceleration relies on custom matrix engines that op…
Error Checking for Sparse Systolic Tensor Arrays
Christodoulos Peltekis, Dionysios Filippas, Giorgos Dimitrakopoulos
Structured sparsity is an efficient way to prune the complexity of modern Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. In such cases,…
Reusing Softmax Hardware Unit for GELU Computation in Transformers
Christodoulos Peltekis, Kosmas Alexandridis, Giorgos Dimitrakopoulos
Transformers have improved drastically the performance of natural language processing (NLP) and computer vision applications. The computation of transformers involves matrix multip…
DeMM: A Decoupled Matrix Multiplication Engine Supporting Relaxed Structured Sparsity
Christodoulos Peltekis, Vasileios Titopoulos, Chrysostomos Nicopoulos +1
Deep Learning (DL) has achieved unprecedented success in various application domains. Meanwhile, model pruning has emerged as a viable solution to reduce the footprint of DL models…