Cloud deployments disaggregate storage from compute, providing more flexibility to both the
storage and compute layers. In this paper, we explore disaggregation by taking it one step …

Columnar databases rely on specialized encoding schemes to reduce storage
requirements. These encodings also enable efficient in-situ data processing. Nevertheless …

In March 2021, the US Department of Energy's Advanced Scientific Computing Research
program convened the Workshop on Reimagining Codesign. The workshop, also known as …

Hardware is evolving at a very fast pace due to diverse trends in the IT industry. In the area
of data processing, it is fair to say that software often just reacts to these changes, trying to …

Trends in hardware, the prevalence of the cloud, and the rise of highly demanding
applications have ushered an era of specialization that is quickly changing the way data is …

The growing trend towards specialization has led to a proliferation of accelerators and
alternative processing devices. When embedded in conventional computer architectures …

Many Big Data applications include the processing of data streams on semi-structured data
formats such as JSON. A disadvantage of such formats is that an application may spend a …

Getting the best performance from the ever-increasing number of hardware platforms has
been a recurring challenge for data processing systems. In recent years, the advent of data …

The enormous quantity of data produced every day together with advances in data analytics
has led to a proliferation of data management and analysis systems. Typically, these …

(57) ABSTRACT A secure machine learning system of a database system can be
implemented to use secure shared data to train a machine learning model. To manage the …