Publications associées à An Economic Model for Self-tuned Cloud Caching

Publications associées (29)

Using Cloud Functions as Accelerator for Elastic Data Analytics

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

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Panagiotis Sioulas

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

EPFL2023

uKharon: A Membership Service for Microsecond Applications

Rachid Guerraoui, Javier Picorel Obando, Athanasios Xygkis, Antoine Murat

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

USENIX Association2023

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

The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry

Daniel Probst

While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the sci ...

2023

Caching and Neutrality

Aikaterini Argyraki, Pavlos Nikolopoulos, Muhammad Abdullah

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

ACM Association for Computing Machinery2023

The effects of war on Ukrainian research

Gaétan Jean A de Rassenfosse, Wolf-Hendrik Peter Uhlbach

The ongoing war in Ukraine has profoundly impacted the Ukrainian scientific community. Numerous researchers have either emigrated or transitioned to alternate professions. For those who remain in research, the destruction of civil infrastructure and psycho ...

Springernature2023

Next-generation brain observatories

Mackenzie Mathis

We propose centralized brain observatories for large-scale recordings of neural activity in mice and non-human primates coupled with cloud-based data analysis and sharing. Such observatories will advance reproducible systems neuroscience and democratize ac ...

CELL PRESS2022

Efficient GPU-accelerated Join Optimization for Complex Queries

Anastasia Ailamaki, Bikash Chandra, Srinivas Karthik Venkatesh

Analytics on modern data analytic and data warehouse systems often need to run large complex queries on increasingly complex database schemas. A lot of progress has been made on executing such complex queries using techniques like scale out query processin ...

IEEE2022

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

Graph integration of structured, semistructured and unstructured data for data journalism

Angelos Christos Anadiotis

Digital data is a gold mine for modern journalism. However, datasets which interest journalists are extremely heterogeneous, ranging from highly structured (relational databases), semi-structured (JSON, XML, HTML), graphs (e.g., RDF), and text. Journalists ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

Daniel Keller

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...

2022

HPCache: Memory-Efficient OLAP Through Proportional Caching

Anastasia Ailamaki, Hamish Mcniece Hill Nicholson, Periklis Chrysogelos

Analytical engines rely on in-memory caching to avoid disk accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- & time-based caching decisions, however, are a proxy of the expected query execution ...

ACM2022

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

Edit Based Grading of SQL Queries

Bikash Chandra

Grading student SQL queries manually is a tedious and error-prone process. Earlier work on testing correctness of student SQL queries, such as the XData system, can be used to test the correctness of a student query. However, in case a student query is fou ...

ASSOC COMPUTING MACHINERY2021

Data mining in the context of urban metabolism: A case study of Geneva and Lausanne, Switzerland

Claudia Rebeca Binder Signer, Aristide Henri Roger Athanassiadis

The highest share of the global population lives in cities. The current configuration of the latter requires considerable amounts of resource flows causing the degradation of local and global ecosystems. To face the complexity of these challenges, scientis ...

IOP PUBLISHING LTD2021

A system design for elastically scaling transaction processing engines in virtualized servers

Anastasia Ailamaki, Raja Appuswamy, Angelos Christos Anadiotis

Online Transaction Processing (OLTP) deployments are migrating from on-premise to cloud settings in order to exploit the elasticity of cloud infrastructure which allows them to adapt to workload variations. However, cloud adaptation comes at the cost of re ...

ASSOC COMPUTING MACHINERY2020

An Architecture for Load Balance in Computer Cluster Applications

Laurent Bindschaedler

Amid a data revolution that is transforming industries around the globe, computing systems have undergone a paradigm shift where many applications are scaled out to run on multiple computers in a computing cluster. As the storage and processing capabilitie ...

EPFL2020

Adaptive partitioning and indexing for in situ query processing

Anastasia Ailamaki, Ioannis Alagiannis, Manolis Karpathiotakis, Manoussos Gavriil Athanassoulis, Matthaios Alexandros Olma

The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. To alleviate the loading cost, in ...

SPRINGER2020

Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges

François Maréchal

Data are essential to urban building energy models and yet, obtaining sufficient and accurate building data at a large-scale is challenging. Previous studies have highlighted that the data impact on urban case studies has not been sufficiently discussed. T ...

2020