@InProceedings{mayr:query,
  author = {Tobias Mayr and Philippe Bonnet and Johannes Gehrke and Praveen
  Seshadri},
  title = {Leveraging Non-Uniform Resources for Parallel Query Processing},
  booktitle = {Proceedings of the Third IEEE/ACM International Symposium on
  Cluster Computing and the Grid},
  year = {2003},
  month = {May},
  pages = {120--129},
  publisher = {IEEE Computer Society Press},
  address = {Tokyo, Japan},
  URL =
  {http://csdl.computer.org/comp/proceedings/ccgrid/2003/1919/00/19190120abs.htm},
  keywords = {parallel query processing, load balancing, parallel I/O,
  pario-bib},
  abstract = {Modular clusters are now composed of non- uniform nodes with
  different CPUs, disks or network cards so that customers can adapt the
  cluster configuration to the changing technologies and to their changing
  needs. This challenges dataflow parallelism as the primary load balancing
  technique of existing parallel database systems. We show in this paper that
  dataflow parallelism alone is ill suited for modular clusters because running
  the same operation on different subsets of the data can not fully utilize
  non-uniform hardware resources. We propose and evaluate new load balancing
  techniques that blend pipeline parallelism with data parallelism. We consider
  relational operators as pipelines of fine-grained operations that can be
  located on different cluster nodes and executed in parallel on different data
  subsets to best exploit non-uniform resources. We present an experimental
  study that confirms the feasibility and effectiveness of the new techniques
  in a parallel execution engine prototype based on the open-source DBMS
  Predator.}
}