Complex Query Operators on Modern Parallel Architectures

Identifying interesting objects from a large data collection is a fundamental problem for multi-criteria decision making applications.In Relational Database Management Systems (RDBMS), the most popular complex query operators used to solve this type of problem are the Top-K selection operator and the Skyline operator.Top-K selection is tasked with retrieving the k-highest ranking tuples from a given relation, as determined by a user-defined aggregation function.Skyline selection retrieves those tuples with attributes offering (pareto) optimal trade-offs in a given relation.Efficient Top-K query processing entails minimizing tuple evaluations by utilizing elaborate processing schemes combined with sophisticated data structures that enable early termination.Skyline query evaluation involves supporting processing strategies which are geared towards early termination and incomparable tuple pruning.The rapid increase in memory capacity and decreasing costs have been the main drivers behind the development of main-memory database systems.Although the act of migrating query processing in-memory has created many opportunities to improve the associated query latency, attaining such improvements has been very challenging due to the growing gap between processor and main memory speeds.Addressing this limitation has been made easier by the rapid proliferation of multi-core and many-core architectures.However, their utilization in real systems has been hindered by the lack of suitable parallel algorithms that focus on algorithmic efficiency.In this thesis, we study in depth the Top-K and Skyline selection operators, in the context of emerging parallel architectures.Our ultimate goal is to provide practical guidelines for developing work-efficient algorithms suitable for parallel main memory processing.We concentrate on multi-core (CPU), many-core (GPU), and processing-in-memory architectures (PIM), developing solutions optimized for high throughout and low latency.The first part of this thesis focuses on Top-K selection, presenting the specific details of early termination algorithms that we developed specifically for parallel architectures and various types of accelerators (i.e. GPU, PIM).The second part of this thesis, concentrates on Skyline selection and the development of a massively parallel load balanced algorithm for PIM architectures.Our work consolidates performance results across different parallel architectures using synthetic and real data on variable query parameters and distributions for both of the aforementioned problems.The experimental results demonstrate several orders of magnitude better throughput and query latency, thus validating the effectiveness of our proposed solutions for the Top-K and Skyline selection operators

Complex Query Operators on Modern Parallel Architectures

Identifying interesting objects from a large data collection is a fundamental problem for multi-criteria decision making applications.In Relational Database Management Systems (RDBMS), the most popular complex query operators used to solve this type of problem are the Top-K selection operator and the Skyline operator.Top-K selection is tasked with retrieving the k-highest ranking tuples from a given relation, as determined by a user-defined aggregation function.Skyline selection retrieves those tuples with attributes offering (pareto) optimal trade-offs in a given relation.Efficient Top-K query processing entails minimizing tuple evaluations by utilizing elaborate processing schemes combined with sophisticated data structures that enable early termination.Skyline query evaluation involves supporting processing strategies which are geared towards early termination and incomparable tuple pruning.The rapid increase in memory capacity and decreasing costs have been the main drivers behind the development of main-memory database systems.Although the act of migrating query processing in-memory has created many opportunities to improve the associated query latency, attaining such improvements has been very challenging due to the growing gap between processor and main memory speeds.Addressing this limitation has been made easier by the rapid proliferation of multi-core and many-core architectures.However, their utilization in real systems has been hindered by the lack of suitable parallel algorithms that focus on algorithmic efficiency.In this thesis, we study in depth the Top-K and Skyline selection operators, in the context of emerging parallel architectures.Our ultimate goal is to provide practical guidelines for developing work-efficient algorithms suitable for parallel main memory processing.We concentrate on multi-core (CPU), many-core (GPU), and processing-in-memory architectures (PIM), developing solutions optimized for high throughout and low latency.The first part of this thesis focuses on Top-K selection, presenting the specific details of early termination algorithms that we developed specifically for parallel architectures and various types of accelerators (i.e. GPU, PIM).The second part of this thesis, concentrates on Skyline selection and the development of a massively parallel load balanced algorithm for PIM architectures.Our work consolidates performance results across different parallel architectures using synthetic and real data on variable query parameters and distributions for both of the aforementioned problems.The experimental results demonstrate several orders of magnitude better throughput and query latency, thus validating the effectiveness of our proposed solutions for the Top-K and Skyline selection operators

Searching for potential marine sand resources to mitigate beach erosion in island settings

This article presents the results of a marine geophysical and sedimentological study carried out around Lesvos Island (NE Aegean) to investigate the potential of exploitable marine aggregate (MA) deposits that could be used for beach replenishment purposes. Sub-bottom profiler data showed a good prospect for potential coarse-grained deposits in two of the three surveyed areas around Lesvos. Grain size and mineralogical analysis of the surficial sediments revealed sands that could properly feed nourishment schemes for eroded beaches or artificial beach development. Observed MA volumes are considered adequate for renourishment operations, when the threat of projected sea-level rise is introduced. Environmental constraints, as well as human activities, are considered for the suggestion and prioritization of specific areas for detailed surveying before future exploitation

Combined thirty-day exposure to thioacetamide and choline-deprivation alters serum antioxidant status and crucial brain enzyme activities in adult rats

Choline (Ch) is an essential nutrient that seems to be involved in a wide variety of metabolic reactions and functions that affect the nervous system, while thioacetamide (TAA) is a well-known hepatotoxic agent. The induction of prolonged Ch-deprivation (CD) in rats receiving TAA (through the drinking water) provides an experimental model of mild progressive hepatotoxicity that could simulate commonly-presented cases in clinical practice. In this respect, the aim of this study was to investigate the effects of a 30-day dietary CD and/or TAA administration (300 mg/L of drinking water) on the serum total antioxidant status (TAS) and the activities of brain acetylcholinesterase (AChE), Na(+),K(+)-ATPase and Mg(2+)-ATPase of adult rats. Twenty male Wistar rats were divided into four groups: A (control), B (CD), C (TAA), D (CD+TAA). Dietary CD was provoked through the administration of Ch-deficient diet. Rats were sacrificed by decapitation at the end of the 30-day experimental period and whole brain enzymes were determined spectrophotometrically. Serum TAS was found significantly lowered by CD (-11% vs Control, p < 0.01) and CD+TAA administration (-19% vs Control, p < 0.001), but was not significantly altered due to TAA administration. The rat brain AChE activity was found significantly increased by TAA administration (+11% vs Control, p < 0.01), as well as by CD+TAA administration (+14% vs Control, p < 0.01). However, AChE was not found to be significantly altered by the 30-day dietary CD. On the other hand, CD caused a significant increase in brain Na(+),K(+)-ATPase activity (+16% vs Control, p < 0.05) and had no significant effect on Mg(2+)-ATPase. Exposure to TAA had no significant effect on Na(+),K(+)-ATPase, but inhibited Mg(2+)-ATPase (-20% vs Control, p < 0.05). When administered to CD rats, TAA caused a significant decrease in Na(+),K(+)-ATPase activity (-41% vs Control, p < 0.001), but Mg(2+)-ATPase activity was maintained into control levels. Our data revealed that an adult-onset 30-day dietary-induced CD had no effect on AChE activity. Treatment with TAA not only reversed the stimulatory effect of CD on adult rat brain Na(+),K(+)-ATPase, but caused a dramatic decrease in its activity (-41%). Previous studies have linked this inhibition with metabolic phenomena related to TAA-induced fulminant hepatic failure and encephalopathy. Our data suggest that CD (at least under the examined 30-day period) is an unfavorable background for the effect of TAA-induced hepatic damage on Na(+),K(+)-ATPase activity (an enzyme involved in neuronal excitability, metabolic energy production and neurotransmission)

Artificial extracellular matrix scaffolds of mobile molecules enhance maturation of human stem cell-derived neurons

Human induced pluripotent stem cell (hiPSC) technologies offer a unique resource for modeling neurological diseases. However, iPSC models are fraught with technical limitations including abnormal aggregation and inefficient maturation of differentiated neurons. These problems are in part due to the absence of synergistic cues of the native extracellular matrix (ECM). We report on the use of three artificial ECMs based on peptide amphiphile (PA) supramolecular nanofibers. All nanofibers display the laminin-derived IKVAV signal on their surface but differ in the nature of their non-bioactive domains. We find that nanofibers with greater intensity of internal supramolecular motion have enhanced bioactivity toward hiPSC-derived motor and cortical neurons. Proteomic, biochemical, and functional assays reveal that highly mobile PA scaffolds caused enhanced β1-integrin pathway activation, reduced aggregation, increased arborization, and matured electrophysiological activity of neurons. Our work highlights the importance of designing biomimetic ECMs to study the development, function, and dysfunction of human neurons