DaMoN'21, the 17th International Workshop on Data Management on New Hardware is co-located with the ACM SIGMOD conference.

The aim of this one-day workshop is to bring together researchers who are interested in optimizing database performance on modern computing infrastructure by designing new data management techniques and tools. Please see https://sites.google.com/view/damon2021/home-damon-2021 for more info.


We invite submissions to two tracks:
1) Full papers: A full paper must be no longer than 6 pages excluding the bibliography.  There is no limit on the length of the bibliography.  Full papers describe a complete work in the area of data management for new hardware. Accepted papers will be given 10 pages (plus citations) for the camera ready version and a long presentation slot during the workshop.
2) Short Papers: Short papers must not exceed two pages excluding the bibliography. Short papers describe very early stage works or summaries of mature systems. Short papers will be included in the proceedings, and may be given a short presentation slot during the workshop.
All accepted papers (full and short) will also be presented as posters at the workshop if the virtual platform permits.


Authors are invited to submit original, unpublished research papers that are not being considered for publication in any other forum. Manuscripts should be submitted electronically as PDF files using the latest ACM paper format to the DaMoN 2021 CMT site, at https://cmt3.research.microsoft.com/DAMON2021/. Submissions will be reviewed in a single-blind manner. Submissions that are 2 pages or shorter excluding the bibliography will be reviewed as short papers. Submissions that are 6 pages or shorter excluding the bibliography will be reviewed as full papers. Submissions that are longer than 6 pages excluding the bibliography will not be accepted.
Accepted papers will be included within the informal online proceedings at the website. Additionally, all accepted papers will be published online in the ACM digital library. Therefore, the papers must include the standard ACM copyright notice on the first page.


Paper submission:  26 March 2021, 11:59pm Pacific Daylight Time

Notification of acceptance: 27 April 2021
Camera-ready copies: 24 May 2021
Workshop: 21 June 2021


The continued evolution of computing hardware and infrastructure imposes new challenges and bottlenecks to program performance. As a result, traditional database architectures that focus solely on I/O optimization increasingly fail to utilize hardware resources efficiently.  Multi-core CPUs, GPUs, FPGAs, new memory and storage technologies (such as flash and non-volatile memory), and low-power hardware imposes a great challenge to optimizing database performance. Consequently, exploiting the characteristics of modern hardware has become an important topic of database systems research.
The goal is to make database systems adapt automatically to the sophisticated hardware characteristics, thus maximizing performance transparently to applications. To achieve this goal, the data management community needs interdisciplinary collaboration with computer architecture, compiler, operating systems and storage researchers. This involves rethinking traditional data structures, query processing algorithms, and database software architectures to adapt to the advances in the underlying hardware infrastructure.
We seek submissions bridging the area of database systems to computer architecture, compilers, and operating systems. In particular, submissions covering topics from the following non-exclusive list are encouraged:

  database algorithms and data structures on modern hardware
  cost models and query optimization for novel hierarchical memory systems
  hardware systems for query processing
  data management using co-processors
  novel application of new storage technologies to data management
  query processing using computing power in storage systems
  database architectures for low-power computing and embedded devices
  database architectures on multi-threaded and chip multiprocessors
  performance analysis of database workloads on modern hardware
  compiler and operating systems advances to improve database performance
  new benchmarks for micro-architectural evaluation of database workloads
  taking advantage of modern network capabilities for data processing