[CGC] [Systems & Architecture]  

Data-Intensive Computing with Spatial Models

Much of the infrastructure in the Duke Computer Science Department is funded by grants from the National Science Foundation. The parallel computing research through the 1990s was funded by a 1991 Research Infrastructure (RI) award, and the Cluster Lab was established with a 1995 grant from the ARI program. Most recently, we received a 5-year Research Infrastructure award in 1999 to fund common infrastructure for projects relating to our focus on data-intensive computing with spatial models. This includes projects in scientific computing, algorithms, architecture, and systems. Much of the systems and architecture work deals basic facilities for large-scale storage, high-performance memory systems, wide-area data sharing, and pervasive computing, but we also work directly on application efforts related to the spatial theme.

Participating Groups

Center for Geometric Computing
Network Storage/Cluster Lab
Internet Systems Software Group

Projects and Related Links

Geo*: systems and algorithms for massive-data GIS
TPIE: I/O computing toolkit
Slice: scalable network storage
TUNE: memory-friendly programming
ICE: informed caching environment
Trapeze: high-speed network I/O
Bio-Geometric Modeling
PRISM: invariant subspace methods
TACT: wide-area data replication

Investigators

Pankaj Agarwal
Lars Arge
Jeff Chase
Herbert Edelsbrunner
Carla Ellis
Alvin Lebeck
Xiaobai Sun
Amin Vahdat


Funding is provided by
The National Science Foundation
under grant EIA-9972879 (RI).



Last modified: Thu May 17 08:23:15 EDT 2001