With the continuous development of human-centric, resilient, and sustainable manufacturing
towards Industry 5.0, Artificial Intelligence (AI) has gradually unveiled new opportunities for …

Due to their high computational power and internal memory bandwidth, graphic processing
units (GPUs) have been extensively studied by the database systems research community …

GPUs have long been discussed as accelerators for database query processing because of
their high processing power and memory bandwidth. However, two main challenges limit the …

The huge demand for computation in artificial intelligence (AI) is driving unparalleled
investments in hardware and software systems for AI. This leads to an explosion in the …

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 …

Modern Hybrid Transactional/Analytical Processing (HTAP) systems use an integrated data
processing engine that performs analytics on fresh data, which are ingested from a …

GPUs offer massive parallelism and high-bandwidth memory access, making them an
attractive option for accelerating data analytics in database systems. However, while modern …

Data processing systems face the challenge of supporting increasingly diverse workloads
efficiently. At the same time, they are already bloated with internal complexity, and it is not …

Accelerating SQL queries on stream processing by utilizing heterogeneous coprocessors,
such as GPUs, has shown to be an effective approach. Most works show that heterogeneous …