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Don't cry over spilled records: Memory elasticity of data-parallel applications and its application to cluster scheduling

Willy Zwaenepoel, Calin Iorgulescu, Syed Mohammad Aunn Raza, Florin Dinu, Wajih Ul Hassan

Understanding the performance of data-parallel workloads when resource-constrained has significant practical importance but unfortunately has received only limited attention. This paper identifies, quantifies and demonstrates memory elasticity, an intrinsi ...

The USENIX Association2017

Distributed Time Series Analytics

Tian Guo

In recent years time series data has become ubiquitous thanks to affordable sensors and advances in embedded technology. Large amount of time-series data are continuously produced in a wide spectrum of applications, such as sensor networks, medical monitor ...

EPFL2017

Big-Data Streaming Applications Scheduling Based on Staged Multi-armed Bandits

David Atienza Alonso, Karim Kanoun, Cem Tekin

Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to adapt at run-time the throughput and ...

Institute of Electrical and Electronics Engineers2016

Big-Data Streaming Applications Scheduling Based on Staged Multi-Armed Bandits

David Atienza Alonso, Karim Kanoun, Cem Tekin

Institute of Electrical and Electronics Engineers2016

Scalable splitting algorithms for big-data interferometric imaging in the SKA era

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

In the context of next generation radio telescopes, like the Square Kilometre Array, the efficient processing of large-scale datasets is extremely important. Convex optimisation tasks under the compressive sensing framework have recently emerged and provid ...

OUP2016

SigCO: Mining Significant Correlations via a Distributed Real-time Computation Engine

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo, Hao Zhuang

The dramatic rise of time-series data produced in a variety of contexts, such as stock markets, mobile sensing, sensor networks, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation systems (e.g., Apach ...

2015

Language Support for Distributed Functional Programming

Heather Christine Klug

Software development has taken a fundamental turn. Software today has gone from simple, closed programs running on a single machine, to massively open programs, patching together user experiences byway of responses received via hundreds of network requests ...

EPFL2015

Containers and Aggregates, Mutators and Isolates for Reactive Programming

Martin Odersky, Philipp Haller, Aleksandar Prokopec

Many programs have an inherently reactive nature imposed by the functional dependencies between their data and external events. Classically, these dependencies are dealt with using callbacks. Reactive programming with first-class reactive values is a parad ...

2014

X-Stream: Edge-centric Graph Processing using Streaming Partitions

Willy Zwaenepoel, Amitabha Roy, Ivo Mihailovic

X-Stream is a system for processing both in-memory and out-of-core graphs on a single shared-memory machine. While retaining the scatter-gather programming model with state stored in the vertices, X-Stream is novel in (i) using an edge-centric rather than ...

ACM2013

Spatiotemporal Coherence Tracking

Mohammad Alisafaee

Chip-multiprocessors require a coherence directory to track data sharing and order accesses to the shared data. Scaling coherence directories to support a large number of cores is challenging due to excessive area requirements of the directories. The state ...

2012

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