Recent approaches exploiting the massively parallel architecture of graphics processors (GPUs) to accelerate database operations have achieved intriguing results. While parallel sorting received ...

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...

This report summarises the achievements of the EPSRC Parade project (GRJ/53348), which ran from June 1994 to September 1997. We have made contributions in the following three areas. Parallel Language ...

Traditionally data acquisition has been the bottleneck for large scale proteomics. This has also remained one of the limitations in leveraging mass spectrometry within the clinic. PASEF and short ...

Data parallelism is achieved in the processEmployeesAndMetricsByDepartment function, where tasks involving querying and processing employees based on their department ...

A startup named TigerGraph emerged from stealth today with a new native parallel graph database that its founder thinks can shake up the analytics market. With $31 million in venture funding and ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

With the massive growth of the internet, people can gain access to a massive amount of information. Due to this retrieving the information of interest becomes very difficult. If focused on visual ...

Running parallel database systems in an environment with heterogeneous resources has become increasingly common, due to cluster evolution and increasing interest in moving applications into public ...

Abstract: Hadoop is an efficient and simple parallel framework following the Map Reduce paradigm, and making the parallel processing recently become a hot issue in data-intensive applications. Since ...