activity
20162020
most citedTransparent Compiler and Runtime Specializations for Accelerating Managed Languages on FPGAs

5 citations · 6 across the 2 of their papers we have counts for

collaborators

5 papers

cs.PL20205 cited

Transparent Compiler and Runtime Specializations for Accelerating Managed Languages on FPGAs

Michail Papadimitriou, Juan Fumero, Athanasios Stratikopoulos +2

In recent years, heterogeneous computing has emerged as the vital way to increase computers? performance and energy efficiency by combining diverse hardware devices, such as Graphi…

cs.LG20201 cited

Towards High Performance Java-based Deep Learning Frameworks

Athanasios Stratikopoulos, Juan Fumero, Zoran Sevarac +1

The advent of modern cloud services along with the huge volume of data produced on a daily basis, have set the demand for fast and efficient data processing. This demand is common…

cs.CV2018

Navigating the Landscape for Real-time Localisation and Mapping for Robotics and Virtual and Augmented Reality

Sajad Saeedi, Bruno Bodin, Harry Wagstaff +23

Visual understanding of 3D environments in real-time, at low power, is a huge computational challenge. Often referred to as SLAM (Simultaneous Localisation and Mapping), it is cent…

cs.PL2018

Tornado: A Practical And Efficient Heterogeneous Programming Framework For Managed Languages

James Clarkson, Christos Kotselidis

This paper describes our experiences creating Tornado: a practical and efficient heterogeneous programming framework for managed languages. The novel aspect of Tornado is that it t…

cs.DC2016

Towards co-designed optimizations in parallel frameworks: A MapReduce case study

Colin Barrett, Christos Kotselidis, Mikel Luján

The explosion of Big Data was followed by the proliferation of numerous complex parallel software stacks whose aim is to tackle the challenges of data deluge. A drawback of a such…