With the emergence of data science, graph computing has become increasingly important
these days. Unfortunately, graph computing typically suffers from poor performance when …

Analytics over big graphs is becoming a first-class challenge in database research, with fast-
growing interest from both the academia and the industrial community. This problem arises …

With the emergence of data science, graph computing is becoming a crucial tool for
processing big connected data. Although efficient implementations of specific graph …

The Deep Neural Network (DNN), Recurrent Neural Network (RNN) applications, rapidly
becoming attractive to the market, process a large amount of low-locality data; thus, the …

Processing in Memory (PIM) was first proposed decades ago for reducing the overhead of
data movement between core and memory. With the advances in 3D-stacking technologies …

With the recent trend towards big data, a number of scalable data management systems:
NoSQL and NewSQL are developed to manage massive data effectively. The algorithms …

The computing domain of today's computer systems is moving very fast from arithmetic to
data processing as data volumes grow exponentially. As a result, processing-in-memory …

Processing-in-memory (PIM) has attracted attention to overcome the memory bandwidth
limitation, especially for computing memory-intensive DNN applications. Most PIM …

Big Data Streams are very popular at now, as stirred-up by a plethora of modern
applications such as sensor networks, scientific computing tools, Web intelligence, social …

Database content versioning is an established concept in modern SQL databases, which
also became part of the SQL standard in 2011. It is used in business applications to support …