Publications associées à PrefEdge: SSD Prefetcher for Large-Scale Graph Traversal

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Efficient Online Processing for Advanced Analytics

Mohamed Elsayed Mohamed Ahmed El Seidy

With the advent of emerging technologies and the Internet of Things, the importance of online data analytics has become more pronounced. Businesses and companies are adopting approaches that provide responsive analytics to stay competitive in the global ma ...

EPFL2017

Diverse M-Best Solutions by Dynamic Programming

Michaël Unser, Virginie Sophie Uhlmann

Many computer vision pipelines involve dynamic programming primitives such as finding a shortest path or the minimum energy solution in a tree-shaped probabilistic graphical model. In such cases, extracting not merely the best, but the set of M-best soluti ...

Springer2017

Scaling a Reliable Distributed System

Alexandre David Olivier Maurer

We consider the problem of reliably connecting an arbitrarily large set of computers (nodes) with communication channels. Reliability means here the ability, for any two nodes, to remain connected (i.e., their ability to communicate) with probability at le ...

LPD EPFL2016

Graph-Based Representation and Coding of Multiview Images

Pascal Frossard, Bénédicte Motz

Instead of lossily coding depth images resulting in undesirable geometric distortion, graph-based representation (GBR) describes disparity information as a graph with a controllable accuracy. In this paper, we propose a more compact graphical representatio ...

Ieee2016

Chaos: Scale-out Graph Processing from Secondary Storage

Willy Zwaenepoel, Laurent Bindschaedler, Amitabha Roy, Jasmina Malicevic

Chaos scales graph processing from secondary storage to multiple machines in a cluster. Earlier systems that process graphs from secondary storage are restricted to a single ma- chine, and therefore limited by the bandwidth and capacity of the storage syst ...

2015

Moment Semantics for Reversible Rule-Based Systems

Sandro Stucki

We develop a notion of stochastic rewriting over marked graphs – i.e. directed multigraphs with degree constraints. The approach is based on double-pushout (DPO) graph rewriting. Marked graphs are expressive enough to internalize the ‘no-dangling-edge’ con ...

Springer International Publishing2015

Scale-up Graph Processing in the Cloud: Challenges and Solutions

Willy Zwaenepoel, Amitabha Roy, Jasmina Malicevic

Processing large graphs is an important part of the big-data problem. Recently a number of scale-up systems such as X-Stream, Graphchi and Turbograph have been proposed for processing large graphs using secondary storage on a single machine. The design and ...

Scale-Out NUMA

Babak Falsafi, Edouard Bugnion, Boris Robert Grot, Alexandros Daglis, Stanko Novakovic

Emerging datacenter applications operate on vast datasets that are kept in DRAM to minimize latency. The large number of servers needed to accommodate this massive memory footprint requires frequent server-to-server communication in applications such as ke ...

2014

PrefEdge: SSD Prefetcher for Large-Scale Graph Traversal

Graph Chatbot

Chattez avec Graph Search

Efficient Online Processing for Advanced Analytics

Diverse M-Best Solutions by Dynamic Programming

Scaling a Reliable Distributed System

Graph-Based Representation and Coding of Multiview Images

Chaos: Scale-out Graph Processing from Secondary Storage

Orchestration Graphs

Moment Semantics for Reversible Rule-Based Systems

Scale-up Graph Processing in the Cloud: Challenges and Solutions

Scale-Out NUMA

Graph-based representation and coding of multiview geometry

Orchestration Graphs

Graph-Based Representation and Coding of Multiview Images

Moment Semantics for Reversible Rule-Based Systems

Scale-Out NUMA

Diverse M-Best Solutions by Dynamic Programming

Efficient Online Processing for Advanced Analytics

Scaling a Reliable Distributed System

Chaos: Scale-out Graph Processing from Secondary Storage

Graph-based representation and coding of multiview geometry

Scale-up Graph Processing in the Cloud: Challenges and Solutions