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ReCache: Reactive Caching for Fast Analytics over Heterogeneous Data

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Time- and Space-Efficient Spatial Data Analytics

Mirjana Pavlovic

Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

EPFL2019

Rock You like a Hurricane: Taming Skew in Large Scale Analytics

Willy Zwaenepoel, Nicolas Schiper, Laurent Bindschaedler, Jasmina Malicevic, Ashvin Goel

Current cluster computing frameworks suffer from load imbalance and limited parallelism due to skewed data distributions, processing times, and machine speeds. We observe that the underlying cause for these issues in current systems is that they partition ...

2018

Analysis of the vertical displacement of energy pile groups

Lyesse Laloui, Alessandro Francesco Rotta Loria

Over the last fifty years, the interaction factor method has been widely used to address the vertical displacement and the increased deformation of conventional pile groups subjected to mechanical loads when group effects and interactions occur among the p ...

2018

No data left behind: real-time insights from a complex data ecosystem

Anastasia Ailamaki, Manolis Karpathiotakis

The typical enterprise data architecture consists of several actively updated data sources (e.g., NoSQL systems, data warehouses), and a central data lake such as HDFS, in which all the data is periodically loaded through ETL processes. To simplify query p ...

2017

Just-in-time Analytics Over Heterogeneous Data and Hardware

Manolis Karpathiotakis

Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of datasets to gain insights. At the same time, data variety increases continuously across multiple axes. First, data comes in mu ...

EPFL2017

Toward timely, predictable and cost-effective data analytics

Renata Borovica-Gajic

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

EPFL2016

The Impact of Big Data and Analytics on CIO Role

Gianluigi Viscusi

The joint consideration of big data and analytics is a relatively recent development, particularly, within the domain of Management of Information Systems (MIS). In recent years there is a dramatic increment of the data produced by digital devices and syst ...

2016

Runtime Prediction for Scale-Out Data Analytics

Adrian Daniel Popescu

Many analytics applications generate mixed workloads, i.e., workloads comprised of analytical tasks with different processing characteristics including data pre-processing, SQL, and iterative machine learning algorithms. Examples of such mixed workloads ca ...

EPFL2015

How to Stop Under-Utilization and Love Multicores

Anastasia Ailamaki, Pinar Tözün, Danica Porobic, Iraklis Psaroudakis, Erietta Liarou

Hardware trends oblige software to overcome three major challenges against systems scalability: (1) taking advantage of the implicit/vertical parallelism within a core that is enabled through the aggressive micro-architectural features, (2) exploiting the ...

2015

Accelerators for Data Processing

Yusuf Onur Koçberber

The explosive growth in digital data and its growing role in real-time analytics motivate the design of high-performance database management systems (DBMSs). Meanwhile, slowdown in supply voltage scaling has stymied improvements in core performance and ush ...

EPFL2015