Responding to the" datacenter tax" and" killer microseconds" problems for memory-intensive
datacenter applications, diverse solutions including Smart NIC-based ones have been …

The ability to perform machine learning (ML) tasks in a database management system
(DBMS) is a new paradigm for conventional database systems as it enables advanced data …

As databases need to strike a good balance of high performance at low costs, hardware-
accelerators like FPGAs are increasingly considered to improve core database operations …

Query processing for data analytics with machine learning scoring involves executing
heterogeneous operations in a pipelined fashion. Hardware acceleration is one approach to …

Database is an important carrier to meet information overall management. With the
continuous development of global information construction in recent years, the types and …

We study the performance, power, and thermal profiles for database workloads on hybrid P-
core and E-core CPUs. We find that E-cores run cooler than P-cores, use less power, and …

Stream processing acceleration is driven by the continuously increasing volume and velocity
of data generated on the Web and the limitations of storage, computation, and power …

Aggregation queries are a series of computationally-demanding analytics operations on
grouped and/or time series (streaming) data. They include tasks such as summation or …

The hardware of modern server is being increasingly heterogeneous as advanced
accelerators, such as FPGAs, are used together with multicore CPUs to meet the computing …

Society's reliance on computer networks has grown rapidly in recent decades, with the
number of interconnected devices projected to hit 29.3 billion in 2023 [3]. This explosion in …