39 citations · 69 across the 20 of their papers we have counts for
20 papers
Sparse Computations in Deep Learning Inference
Ioanna Tasou, Panagiotis Mpakos, Angelos Vlachos +25
The computational demands of modern Deep Neural Networks (DNNs) are immense and constantly growing. While training costs usually capture public attention, inference demands are als…
Spira: Exploiting Voxel Data Structural Properties for Efficient Sparse Convolution in Point Cloud Networks
Dionysios Adamopoulos, Anastasia Poulopoulou, Georgios Goumas +1
Sparse Convolution (SpC) powers 3D point cloud networks widely used in autonomous driving and augmented/virtual reality. SpC builds a kernel map that stores mappings between input…
Probabilistic Links Between Quantum Classification of Patterns of Boolean Functions and Hamming Distance
Theodore Andronikos, Constantinos Bitsakos, Konstantinos Nikas +2
This article investigates the probabilistic relationship between quantum classification of Boolean functions and their Hamming distance. By integrating concepts from quantum comput…
Quantum Shadows: The Dining Information Brokers
Theodore Andronikos, Constantinos Bitsakos, Konstantinos Nikas +2
This article introduces the innovative Quantum Dining Information Brokers Problem, presenting a novel entanglement-based quantum protocol to address it. The scenario involves i…
Quantum Classification Outside the Promised Class
Theodore Andronikos, Constantinos Bitsakos, Konstantinos Nikas +2
This paper studies the important problem of quantum classification of Boolean functions from a entirely novel perspective. Typically, quantum classification algorithms allow us to…
A Quantum Algorithm for the Classification of Patterns of Boolean Functions
Theodore Andronikos, Constantinos Bitsakos, Konstantinos Nikas +2
This paper introduces a novel quantum algorithm that is able to classify a hierarchy of classes of imbalanced Boolean functions. The fundamental characteristic of imbalanced Boolea…
Squeezy: Rapid VM Memory Reclamation for Serverless Functions
Orestis Lagkas Nikolos, Chloe Alverti, Stratos Psomadakis +2
Resource elasticity is one of the key defining characteristics of the Function-as-a-Service (FaaS) serverless computing paradigm. While compute resources assigned to VM-sandboxed f…
eBPF-mm: Userspace-guided memory management in Linux with eBPF
Konstantinos Mores, Stratos Psomadakis, Georgios Goumas
We leverage eBPF in order to implement custom policies in the Linux memory subsystem. Inspired by CBMM, we create a mechanism that provides the kernel with hints regarding the bene…
SmartPQ: An Adaptive Concurrent Priority Queue for NUMA Architectures
Christina Giannoula, Foteini Strati, Dimitrios Siakavaras +2
Concurrent priority queues are widely used in important workloads, such as graph applications and discrete event simulations. However, designing scalable concurrent priority queues…
Feature-based SpMV Performance Analysis on Contemporary Devices
Panagiotis Mpakos, Dimitrios Galanopoulos, Petros Anastasiadis +3
The SpMV kernel is characterized by high performance variation per input matrix and computing platform. While GPUs were considered State-of-the-Art for SpMV, with the emergence of…
Architectural Support for Efficient Data Movement in Disaggregated Systems
Christina Giannoula, Kailong Huang, Jonathan Tang +4
Resource disaggregation offers a cost effective solution to resource scaling, utilization, and failure-handling in data centers by physically separating hardware devices in a serve…
DaeMon: Architectural Support for Efficient Data Movement in Disaggregated Systems
Christina Giannoula, Kailong Huang, Jonathan Tang +4
Resource disaggregation offers a cost effective solution to resource scaling, utilization, and failure-handling in data centers by physically separating hardware devices in a serve…
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…
SparseP: 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…
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…
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…
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…
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…
Improving virtual host efficiency through resource and interference aware scheduling
Evangelos Angelou, Konstantinos Kaffes, Athanasia Asiki +2
Modern Infrastructure-as-a-Service Clouds operate in a competitive environment that caters to any user's requirements for computing resources. The sharing of the various types of r…
A lightweight optimization selection method for Sparse Matrix-Vector Multiplication
Athena Elafrou, Georgios Goumas, Nectarios Koziris
In this paper, we propose an optimization selection methodology for the ubiquitous sparse matrix-vector multiplication (SpMV) kernel. We propose two models that attempt to identify…