activity
20172022
most citedPerformance Analysis and Optimization of Sparse Matrix-Vector Multiplication on Modern Multi- and Many-Core Processors

39 citations · 46 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AR20221 cited

Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems

Christina Giannoula, Ivan Fernandez, Juan Gómez-Luna +3

Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks a…

cs.AR2021

SynCron: Efficient Synchronization Support for Near-Data-Processing Architectures

Christina Giannoula, Nandita Vijaykumar, Nikela Papadopoulou +7

Near-Data-Processing (NDP) architectures present a promising way to alleviate data movement costs and can provide significant performance and energy benefits to parallel applicatio…

cs.LG20206 cited

Weight Pruning via Adaptive Sparsity Loss

George Retsinas, Athena Elafrou, Georgios Goumas +1

Pruning neural networks has regained interest in recent years as a means to compress state-of-the-art deep neural networks and enable their deployment on resource-constrained devic…

cs.LG2019

RecNets: Channel-wise Recurrent Convolutional Neural Networks

George Retsinas, Athena Elafrou, Georgios Goumas +1

In this paper, we introduce Channel-wise recurrent convolutional neural networks (RecNets), a family of novel, compact neural network architectures for computer vision tasks inspir…

cs.PF201739 cited

Performance Analysis and Optimization of Sparse Matrix-Vector Multiplication on Modern Multi- and Many-Core Processors

Athena Elafrou, Georgios Goumas, Nektarios Koziris

This paper presents a low-overhead optimizer for the ubiquitous sparse matrix-vector multiplication (SpMV) kernel. Architectural diversity among different processors together with…