Publications by Anastasia Ailamaki

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Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

As modern data pipelines continue to collect, produce, and store a variety of data formats, extracting and combining value from traditional and context-rich sources such as strings, text, video, audio, and logs becomes a manual process where such formats a ...

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

Modern big data workflows, found in e.g., machine learning use cases, often involve iterations of cycles of batch analytics and interactive analytics on temporary data. Whereas batch analytics solutions for large volumes of raw data are well established (e ...

K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...

Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. At the same time, the existing tools that att ...

Data lakes are complex ecosystems where heterogeneity prevails. Raw data of diverse formats are stored and processed, while long and expensive ETL processes are avoided. Apart from data heterogeneity, data lakes also entail hardware heterogeneity. Typical ...

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 ...

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies such as dense image matching and airborne LiDAR scanning. With the increase in volume and precision, point cloud data offers a ...

In order to improve their power efficiency and computational capacity, modern servers are adopting hardware accelerators, especially GPUs. Modern analytical DMBS engines have been highly optimized for multi-core multi-CPU query execution, but lack the nece ...

Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management nece ...

Modern big data systems process not only a huge volume of data, but also numerous concurrent queries. These queries usually span over distributed data and need to be processed within a strict deadline (e.g.: report generation, SLA, etc.). While users expec ...

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 ...

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 ...

With the deeply-ingrained notion that disks can efficiently access only one dimensional data, current approaches for mapping multidimensional data to disk blocks either allow efficient accesses in only one dimension, trading off the efficiency of accesses ...

Transactional memory is a promising way for implementing efficient synchronization mechanisms for multicore processors. Intel's introduction of hardware transactional memory (HTM) into their Haswell line of processors marks an important step toward mainstr ...

Performance-critical industrial applications, including large-scale program, network, and distributed system analyses, are increasingly reliant on recursive queries for data analysis. Yet traditional relational algebra-based query optimization techniques d ...

Increases in on-chip communication delay and the large working sets of server and scientific workloads complicate the design of the on-chip last- level cache for multicore processors. The large working sets favor a shared cache design that maximizes the ag ...

Multicore hardware demands software parallelism. Transaction processing workloads typically exhibit high concurrency, and, thus, provide ample opportunities for parallel execution. Unfortunately, because of the characteristics of the application, transacti ...

We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse ex ...

Anastasia Ailamaki

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HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics

E-Scan: Consuming Contextual Data with Model Plugins

DiNoDB: Efficient Large-Scale Raw Data Analytics

Improving K-means Clustering Using Speculation

CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning

Storage Management in Smart Data Lake

Using Cloud Functions as Accelerator for Elastic Data Analytics

Dictionary Compression in Point Cloud Data Management

Hardware-conscious Query Processing in GPU-accelerated Analytical Engines

Optimal service pricing for a cloud cache

Optimizing Goodput through Sharing for Batch Analytics with Deadlines

Enabling Scientific Discovery Via Innovative Spatial Data Management

Scalability of write-ahead logging on multicore and multisocket hardware

On Multidimensional Data and Modern Disks

Applying HTM to an OLTP System: No Free Lunch

Adaptive Recursive Query Optimization

Reactive NUCA: Near-Optimal Block Placement and Replication in Distributed Caches

Eliminating unscalable communication in transaction processing

Reconstruction and Simulation of Neocortical Microcircuitry