Publications related to An Economic Model for Self-tuned Cloud Caching

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

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, Antoine Murat, Javier Picorel Obando, Athanasios Xygkis

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

Pavlos Nikolopoulos, Muhammad Abdullah, Aikaterini Argyraki

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, Tetiana Murovana

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, Shreya Saxena

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, Riccardo Mancini, Vasileios Mageirakos

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