Taster: Self-Tuning, Elastic and Online Approximate Query Processing

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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 ...

Industry is increasingly turning to reconfigurable architectures like FPGAs and CGRAs for improved performance and energy efficiency. Unfortunately, adoption of these architectures has been limited by their programming models. HDLs lack abstractions for pr ...

The trade-offs between the use of modern high-level and low-level programming languages in constructing complex software artifacts are well known. High-level languages allow for greater programmer productivity: abstraction and genericity allow for the same ...

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies like dense image matching and airborne LiDAR (Light Detection and Ranging) scanning. With the increase in volume and precision ...

There is a trend towards increased specialization of data management software for performance reasons. The improved performance not only leads to a more efficient usage of the underlying hardware and cuts the operation costs of the system, but also is a ga ...

As data continues to be generated at exponentially growing rates in heterogeneous formats, fast analytics to extract meaningful information is becoming increasingly important. Systems widely use in-memory caching as one of their primary techniques to speed ...

Many map-reduce frameworks as well as NoSQL systems rely on collection programming as their interface of choice due to its rich semantics along with an easily parallelizable set of primitives. Unfortunately, the potential of collection programming is not ...

The integration of renewable energy technologies in the existing energy infrastructure plays a key role in improving the sustainability of cities. Due to the stochastic nature of some renewable energy sources, primarily wind and solar energy, direct integr ...

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

The goal of query optimization is to map a declarative query (describing data to generate) to a query plan (describing how to generate the data) with optimal execution cost. Query optimization is required to support declarative query interfaces. It is a co ...

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

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Dictionary Compression in Point Cloud Data Management

Spatial: A Language and Compiler for Application Accelerators

Compilation and Code Optimization for Data Analytics

Dictionary Compression in Point Cloud Data Management

Program Analysis and Compilation Techniques for Speeding up Transactional Database Workloads

ReCache: Reactive Caching for Fast Analytics over Heterogeneous Data

Compilation Techniques for Incremental Collection Processing

Extending building integrated photovoltaics (BiPV) using distributed energy hubs. A case study in Cartigny, Switzerland

Parallelizing Query Optimization on Shared-Nothing Architectures

From Massive Parallelization to Quantum Computing: Seven Novel Approaches to Query Optimization

Toward timely, predictable and cost-effective data analytics