Author/Authors :
Tian، نويسنده , , Y. and Peters-Lidard، نويسنده , , C.D. and Kumar، نويسنده , , S.V. and Geiger، نويسنده , , J. and Houser، نويسنده , , P.R. and Eastman، نويسنده , , J.L. and Dirmeyer، نويسنده , , P. and Doty، نويسنده , , B. and Adams، نويسنده , , J.، نويسنده ,
Abstract :
The Land Information System (LIS) was developed at NASA to perform global land surface simulations at a resolution of 1-km or finer in real time. Such unprecedented scales and intensity pose many computational challenges. In this article, we demonstrate some of our approaches in high-performance computing with a Linux cluster to meet these challenges and reach our performance goals. These approaches include job partition and a job management system for parallel processing on the cluster, high-performance parallel input/output based on GrADS–DODS (GDS) servers, dynamic load-balancing and distributed data storage techniques, and highly scalable data replication with peer-to-peer (P2P) technology. These techniques work coherently to provide a high-performance land surface modeling system featuring fault tolerance, optimal resource utilization, and high scalability. Examples are given with LISʹs high-resolution modeling of surface runoff during 2003 to illustrate LISʹs capability to enable new scientific explorations.
Keywords :
Parallel computing , distributed computing , peer-to-peer network , Beowulf cluster , High-resolution simulation , Hydrology modeling
