Predicting personalized sequential behavior is a key task for recommender systems. In order
to predict user actions such as the next product to purchase, movie to watch, or place to visit …

Analytical databases are continuously adapting to the underlying hardware in order to
saturate all sources of parallelism. At the same time, hardware evolves in multiple directions …

This paper reports the deployment of computational storage drives in Alibaba Cloud, aiming
to enable cloud-native relational database cost-effectively support analytical workloads. With …

There has been significant amount of excitement and recent work on GPU-based database
systems. Previous work has claimed that these systems can perform orders of magnitude …

In the presence of exponential growth of the data produced every day in volume, velocity,
and variety, online analytical processing (OLAP) is becoming increasingly challenging …

There has been a growing interest in using GPU to accelerate data analytics due to its
massive parallelism and high memory bandwidth. The main constraint of using GPU for data …

Database management systems are facing growing data volumes. Previous research
suggests that GPUs are well-equipped to quickly process joins and similar stateful …

GPUs are increasingly used for high-performance and interactive data analytics workloads
due to their capability to accelerate computation using massive parallelism. A key constraint …

The emergence of novel hardware accelerators has powered the tremendous growth of
machine learning in recent years. These accelerators deliver incomparable performance …

Modern enterprise applications represent an emergent application arena that requires the
processing of queries and computations over massive amounts of data. Large-scale, multi …