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Publications associées (31)

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Christoph Koch, Sachin Basil John, Zhekai Jiang, Peter Lindner

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube constru ...

Association for Computing Machinery2023

An end-to-end pipeline for historical censuses processing

Lucas Arnaud André Rappo, Rémi Guillaume Petitpierre, Marion Kramer

Censuses are structured documents of great value for social and demographic history, which became widespread from the nineteenth century on. However, the plurality of formats and the natural variability of historical data make their extraction arduous and ...

2023

AiiDA-defects: an automated and fully reproducible workflow for the complete characterization of defect chemistry in functional materials

Nicola Marzari, Sokseiha Muy, Conrad Johnston

Functional materials that enable many technological applications in our everyday lives owe their unique properties to defects that are carefully engineered and incorporated into these materials during processing. However, optimizing and characterizing thes ...

IOP Publishing Ltd2023

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Anastasia Ailamaki, Viktor Sanca, Periklis Chrysogelos

Modern analytical engines rely on Approximate Query Processing (AQP) to provide faster response times than the hardware allows for exact query answering. However, existing AQP methods impose steep performance penalties as workload unpredictability increase ...

2023

Using Cloud Functions as Accelerator for Elastic Data Analytics

Anastasia Ailamaki, Haoqiong Bian, Tiannan Sha

Cloud function (CF) services, such as AWS Lambda, have been applied as the new computing infrastructure in implementing analytical query engines. For bursty and sparse workloads, CF-based query engine is more elastic than the traditional query engines runn ...

ACM2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Colin Neil Jones, Roland Schwan, Melanie Nicole Zeilinger, Xuan Truong Nghiem

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

IEEE2023

When is it safe to run a transactional workload under Read Committed?

Christoph Koch, Bas Ketsman

The popular isolation level multiversion Read Committed (RC) exchanges some of the strong guarantees of serializability for increased transaction throughput. Nevertheless, transaction workloads can sometimes be executed under RC while still guaranteeing se ...

ASSOC COMPUTING MACHINERY2023

Determining an optimum quantity of interleaved instruction streams of defined coroutines

Anastasia Ailamaki, Georgios Psaropoulos

A method for optimizing memory access for database operations is provided. The method may include performing a first database operation by at least executing a first instruction stream associated with the first database operation. The first database opera ...

2023

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Sachin Basil John

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023