Big data processing systems (eg, Hadoop, Spark, Storm) contain a vast number of
configuration parameters controlling parallelism, I/O behavior, memory settings, and …

Applying deep convolutional neural networks (NN) to video data at scale poses a substantial
systems challenge, as improving inference accuracy often requires a prohibitive cost in …

Configuration tuning is vital to optimize the performance of database management system
(DBMS). It becomes more tedious and urgent for cloud databases (CDB) due to the diverse …

The performance optimization of database systems has been widely studied for years. From
the perspective of the operation and maintenance personnel, it mainly includes three topics …

Database knob tuning is important to achieve high performance (eg, high throughput and
low latency). However, knob tuning is an NP-hard problem and existing methods have …

Although learning-based database optimization techniques have been studied from
academia in recent years, they have not been widely deployed in commercial database …

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …

Modern database management systems (DBMS) contain tens to hundreds of critical
performance tuning knobs that determine the system runtime behaviors. To reduce the total …

Finding good configurations of a software system is often challenging since the number of
configuration options can be large. Software engineers often make poor choices about …

Configuration knobs of database systems are essential to achieve high throughput and low
latency. Recently, automatic tuning systems using machine learning methods (ML) have …