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Anastasia Ailamaki

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Publications associées (179)

PREDIcT: Towards Predicting the Runtime of Large Scale Iterative Analytics

Anastasia Ailamaki, Adrian Daniel Popescu

Machine learning algorithms are widely used today for analytical tasks such as data cleaning, data categorization, or data filtering. At the same time, the rise of social media motivates recent uptake in large scale graph processing. Both categories of alg ...

2013

Sharing Data and Work Across Concurrent Analytical Queries

Anastasia Ailamaki, Manoussos Gavriil Athanassoulis, Iraklis Psaroudakis

Today's data deluge enables organizations to collect massive data, and analyze it with an ever-increasing number of concurrent queries. Traditional data warehouses (DW) face a challenging problem in executing this task, due to their query-centric model: ea ...

2013

From A to E: Analyzing TPC’s OLTP Benchmarks -- The obsolete, the ubiquitous, the unexplored

Anastasia Ailamaki, Pinar Tözün, Dorde Jevdic, Ippokratis Pandis, Ilknur Cansu Kaynak

Introduced in 2007, TPC-E is the most recently standardized OLTP benchmark by TPC. Even though TPC-E has already been around for six years, it has not gained the popularity of its predecessor TPC-C: all the published results for TPC-E use a single database ...

2013

GIPSY: Joining Spatial Datasets with Contrasting Density

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Mirjana Pavlovic

Many scientific and geographical applications rely on the efficient execution of spatial joins. Past research has produced several efficient spatial join approaches and while each of them can join two datasets, the problem of efficiently joining two datase ...

2013

Enabling Scientific Discovery Via Innovative Spatial Data Management

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Mirjana Pavlovic

Researchers in several scientific disciplines are struggling to cope with the masses of data resulting from either increasingly precise instruments or from simulation runs on ever more powerful supercomputers. Efficiently managing this deluge of data has b ...

2013

Improving flash write performance by using update frequency

Anastasia Ailamaki, Radu Ioan Stoica

2013

Computational Neuroscience Breakthroughs Through Innovative Data Management

Anastasia Ailamaki, Farhan Tauheed, Sadegh Heyrani Nobari, Thomas Heinis, Laurynas Biveinis

Simulations have become key in many scientific disciplines to better understand natural phenomena. Neuroscientists, for example, build and simulate increasingly fine grained models (including subcellular details, e.g., neurotransmitter) of the neocortex to ...

2013

Task Scheduling for Highly Concurrent Analytical and Transactional Main-Memory Workloads

Anastasia Ailamaki, Iraklis Psaroudakis

Task scheduling typically employs a worker thread per hardware context to process a dynamically changing set of tasks. It is an appealing solution to exploit modern multi-core processors, as it eases parallelization and avoids unnecessary context switches ...

2013

Accelerating Spatial Range Queries

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Alexandros Stougiannis

It is increasingly common for domain scientists to use computational tools to build and simulate spatial models of the phenomena they are studying. The spatial models they build are more and more detailed as well as dense and are consequently difficult to ...

2013

Toward Scalable Transaction Processing -- Evolution of Shore-MT

Anastasia Ailamaki, Frederick Ryan Johnson, Pinar Tözün, Ippokratis Pandis

Designing scalable transaction processing systems on modern multicore hardware has been a challenge for almost a decade. The typical characteristics of transaction processing workloads lead to a high degree of unbounded communication on multicores for conv ...

VLDB Endowment2013

Clearing the Clouds: A Study of Emerging Scale-out Workloads on Modern Hardware

Mohammad Alisafaee, Anastasia Ailamaki, Babak Falsafi, Michael Ferdman, Stavros Volos, Adrian Daniel Popescu, Al Mutaz Adileh, Dorde Jevdic, Ilknur Cansu Kaynak, Yusuf Onur Koçberber

Emerging scale-out workloads require extensive amounts of computational resources. However, data centers using modern server hardware face physical constraints in space and power, limiting further expansion and calling for improvements in the computational ...

2012

SCOUT: Prefetching for Latent Structure Following Queries

Henry Markram, Felix Schürmann, Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis

Today's scientists are quickly moving from in vitro to in silico experimentation: they no longer analyze natural phenomena in a petri dish, but instead they build models and simulate them. Managing and analyzing the massive amounts of data involved in simu ...

2012

Scalability of write-ahead logging on multicore and multisocket hardware

Anastasia Ailamaki, Radu Ioan Stoica, Frederick Ryan Johnson, Manoussos Gavriil Athanassoulis, Ippokratis Pandis

The shift to multi-core and multi-socket hardware brings new challenges to database systems, as the software parallelism determines performance. Even though database systems traditionally accommodate simultaneous requests, a multitude of synchronization ba ...

2012

Accelerating Range Queries For Brain Simulations

Henry Markram, Felix Schürmann, Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Laurynas Biveinis

Neuroscientists increasingly use computational tools to build and simulate models of the brain. The amounts of data involved in these simulations are immense and the importance of their efficient management is primordial. One particular problem in analyzin ...

2012

OLTP on Hardware Islands

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

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

2012

NoDB: Efficient Query Execution on Raw Data Files

Anastasia Ailamaki, Ioannis Alagiannis, Renata Borovica-Gajic, Miguel Sérgio De Oliveira Branco

As data collections become larger and larger, data loading evolves to a major bottleneck. Many applications already avoid using database systems, e.g., scientific data analysis and social networks, due to the complexity and the increased data-to-query time ...

2012

Same Queries, Different Data: Can we Predict Query Performance?

Anastasia Ailamaki, Adrian Daniel Popescu, Miguel Sérgio De Oliveira Branco

We consider MapReduce workloads that are produced by analytics applications. In contrast to ad hoc query workloads, analytics applications are comprised of fixed data flows that are run over newly arriving data sets or on different portions of an existing ...

2012

Quantifying the Mismatch between Emerging Scale-Out Applications and Modern Processors

Mohammad Alisafaee, Anastasia Ailamaki, Babak Falsafi, Michael Ferdman, Stavros Volos, Adrian Daniel Popescu, Al Mutaz Adileh, Dorde Jevdic, Ilknur Cansu Kaynak, Yusuf Onur Koçberber

Association for Computing Machinery2012

NoDB in Action: Adaptive Query Processing on Raw Data

Anastasia Ailamaki, Ioannis Alagiannis, Renata Borovica-Gajic, Miguel Sérgio De Oliveira Branco

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

Reducing OLTP Instruction Misses With Thread Migration

Anastasia Ailamaki, Pinar Tözün

During an instruction miss a processor is unable to fetch instructions. The more frequent instruction misses are the less able a modern processor is to find useful work to do and thus performance suffers. Online transaction processing (OLTP) suffers from h ...

2012

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