1,769 research outputs found
Graph Summarization
The continuous and rapid growth of highly interconnected datasets, which are
both voluminous and complex, calls for the development of adequate processing
and analytical techniques. One method for condensing and simplifying such
datasets is graph summarization. It denotes a series of application-specific
algorithms designed to transform graphs into more compact representations while
preserving structural patterns, query answers, or specific property
distributions. As this problem is common to several areas studying graph
topologies, different approaches, such as clustering, compression, sampling, or
influence detection, have been proposed, primarily based on statistical and
optimization methods. The focus of our chapter is to pinpoint the main graph
summarization methods, but especially to focus on the most recent approaches
and novel research trends on this topic, not yet covered by previous surveys.Comment: To appear in the Encyclopedia of Big Data Technologie
The Parallelism Motifs of Genomic Data Analysis
Genomic data sets are growing dramatically as the cost of sequencing
continues to decline and small sequencing devices become available. Enormous
community databases store and share this data with the research community, but
some of these genomic data analysis problems require large scale computational
platforms to meet both the memory and computational requirements. These
applications differ from scientific simulations that dominate the workload on
high end parallel systems today and place different requirements on programming
support, software libraries, and parallel architectural design. For example,
they involve irregular communication patterns such as asynchronous updates to
shared data structures. We consider several problems in high performance
genomics analysis, including alignment, profiling, clustering, and assembly for
both single genomes and metagenomes. We identify some of the common
computational patterns or motifs that help inform parallelization strategies
and compare our motifs to some of the established lists, arguing that at least
two key patterns, sorting and hashing, are missing
- …