Related publications (17)

Pixels: An Efficient Column Store for Cloud Data Lakes

Anastasia Ailamaki, Haoqiong Bian

To benefit from the cloud’s higher elasticity and price-efficiency, most modern data-lake engines support S3-like cloud object storage (COS) services as their optional or preferred underlying storage. Meanwhile, the widespread column stores, such as Parque ...
IEEE2022

SPICA: Swiss portal for immune cell analysis

Nicolas Jean Philippe Guex, Christian Iseli

Single-cell transcriptomics allows the study of immune cell heterogeneity at an unprecedented level of resolution. The Swiss portal for immune cell analysis (SPICA) is a web resource dedicated to the exploration and analysis of single-cell RNA-seq data of ...
OXFORD UNIV PRESS2022

Micro-architectural Analysis of Database Workloads

Utku Sirin

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...
EPFL2021

Analysis and estimation of gripper TBM performances in highly fractured and faulted rocks

Federica Sandrone, Jian Zhao, Erika Paltrinieri

This paper focuses on performance analysis of Tunnel Boring Machine (in particular gripper TBMs) in highly jointed rock masses and fault zones. In order to investigate possible relationships between these difficult excavation conditions and TBM performance ...
Elsevier2016

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

Scaling Up Concurrent Main-Memory Column-Store Scans: Towards Adaptive NUMA-aware Data and Task Placement

Anastasia Ailamaki, Iraklis Psaroudakis

Main-memory column-stores are called to efficiently use modern non-uniform memory access (NUMA) architectures to service concurrent clients on big data. The efficient usage of NUMA architectures depends on the data placement and scheduling strategy of the ...
2015

Adaptive Query Processing on Raw Data Files

Ioannis Alagiannis

Nowadays, business and scientific applications accumulate data at an increasing pace. This growth of information has already started to outgrow the capabilities of database management systems (DBMS). In a typical DBMS usage scenario, the user should define ...
EPFL2015

Baseline System for Automatic Speech Recognition with French GlobalPhone Database

Milos Cernak, Sandrine Revaz

This report presents one month trainee work on development of French Automatic Speech Recognition ASR system using a french part of multilingual database GlobalPhone_FR. The purpose of this report is to explain and give results of the training and testing ...
Idiap2012

NoDB in Action: Adaptive Query Processing on Raw Data

Anastasia Ailamaki, Miguel Sérgio De Oliveira Branco, Ioannis Alagiannis

As data collections become larger and larger, users are faced with increasing bottlenecks in their data analysis. More data means more time to prepare the data, to load the data into the database and to execute the desired queries. Many applications alread ...
VLDB Endowment2012

Here are my Data Files. Here are my Queries. Where are my Results?

Anastasia Ailamaki, Frederick Ryan Johnson, Ioannis Alagiannis

Database management systems (DBMS) provide incredible flexibility and performance when it comes to query processing, scalability and accuracy. To fully exploit DBMS features, however, the user must define a schema, load the data, tune the system for the ex ...
2011

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.