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Scaling Up Concurrent Analytical Workloads on Multi-Core Servers

Publications associées (76)

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Near-Memory Address Translation

Javier Picorel Obando

Virtual memory (VM) is a crucial abstraction in modern computer systems at any scale, from handheld devices to datacenters. VM provides programmers the illusion of an always sufficiently large and linear memory, making programming easier. Although the core ...

EPFL2017

Near-Memory Address Translation

Babak Falsafi, Javier Picorel Obando

Memory and logic integration on the same chip is becoming increasingly cost effective, creating the opportunity to offload data-intensive functionality to processing units placed inside memory chips. The introduction of memory-side processing units (MPUs) ...

Ieee2017

Rack-Scale Memory Pooling for Datacenters

Stanko Novakovic

The rise of web-scale services has led to a staggering growth in user data on the Internet. To transform such a vast raw data into valuable information for the user and provide quality assurances, it is important to minimize access latency and enable in-me ...

EPFL2017

Dictionary Compression in Point Cloud Data Management

Anastasia Ailamaki, Mirjana Pavlovic

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies like dense image matching and airborne LiDAR (Light Detection and Ranging) scanning. With the increase in volume and precision ...

2017

Characterization of the Impact of Hardware Islands on OLTP

Anastasia Ailamaki, Miguel Sérgio De Oliveira Branco, Pinar Tözün, Ippokratis Pandis, Danica Porobic

Modern hardware is abundantly parallel and increasingly heterogeneous. The numerous processing cores have non-uniform access latencies to the main memory and processor caches, which causes variability in the communication costs. Unfortunately, database sys ...

Springer Verlag2016

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

Efficient Incremental Data Analysis

Milos Nikolic

Many data-intensive applications require real-time analytics over streaming data. In a growing number of domains -- sensor network monitoring, social web applications, clickstream analysis, high-frequency algorithmic trading, and fraud detections to name a ...

EPFL2016

Building Efficient Query Engines in a High-Level Language

Christoph Koch, Ioannis Klonatos, Amir Shaikhha

Abstraction without regret refers to the vision of using high-level programming languages for systems development without experiencing a negative impact on performance. A database system designed according to this vision offers both increased productivity ...

2016

Distinguishing Crowd Dynamics in Small Teams: A Crowdsourcing Exercise in Higher Education

Christopher Tucci, Gianluigi Viscusi

Folk wisdom usually takes the number of participants as an often necessary and sufficient condition for identifying a crowd. This assumption has diffused among academics interested in crowdsourcing and collective intelligence as well. Yet, consider 50 peop ...

2016

Keystroke Biometrics Ongoing Competition

Sébastien Marcel, André Anjos

This paper presents the first Keystroke Biometrics Ongoing Competition (KBOC) organized to establish a reproducible baseline in person authentication using keystroke biometrics. The competition has been developed using the BEAT platform and includes one of ...

2016