Publikation
Hardware Support for Cloud Database Systems in the Post-Moore's Law Era (Dagstuhl Seminar 24162)
David F. Bacon; Carsten Binnig; David Patterson; Margo I. Seltzer
In: Dagstuhl Reports, Vol. 14, No. 4, Pages 54-84, Dagstuhl, 2024.
Zusammenfassung
The end of scaling from Moore’s and Dennard’s laws has greatly slowed improvements in CPU
speed, RAM capacity, and disk/flash capacity. Meanwhile, cloud database systems, which are
the backbone for many large-scale services and applications in the cloud, are continuing to grow
exponentially. For example, most of Google’s products that run on the Spanner database have
more than a billion users and are continuously growing. Moreover, the growth in data also shows
no signs of slowing down, with further orders-of-magnitude increases likely, due to autonomous
vehicles, the internet-of-things, and human-driven data creation. Meanwhile, machine learning
creates an appetite for data that also needs to be preprocessed using scalable cloud database
systems. As a result, cloud database systems are facing a fundamental scalability wall on how to
further support this exponential growth given the stagnation in hardware.
While database research has a long tradition of investigating how modern hardware can
be leveraged to improve overall system performance – which is also shown by the series of
past Dagstuhl Seminars – a more holistic view is required to address the imminent exponential
scalability challenge that databases will be facing. However, applying hardware accelerators in
a database needs a careful design. In fact, so far, no commercial system has applied hardware
accelerators at scale. Unlike other hyper-scale applications such as machine learning training and
video processing where accelerators such as GPUs and TPUs circumvent this problem, workloads
in cloud database systems are typically not compute-bound and thus benefit less or not at all from
such existing accelerators. This Dagstuhl Seminar thus aimed to bring together leading researchers
and practitioners from database systems, hardware architecture, and storage systems to rethink,
from the ground up, how to co-design database systems and compute/storage hardware. By
uniting experts across these disciplines, the seminar sought to identify the architectural changes
and system designs that could enable the order-of-magnitude improvements required for the next
generation of applications.