Title :
A fine-grained parallel programming model for grid computing
Author :
Yang, Guangwen ; Wang, Qing ; Wu, Yongwei ; Huang, Dazheng
Author_Institution :
Tsinghua Univ., Beijing, China
Abstract :
A new fine-grained parallel programming model - Thin Kernel model is brought forth. In this model, the partitions of the parallel tasks are separated from the computational kernel of the problem. The Thin Kernel model produces parallel tasks dynamically at runtime when the tasks are being scheduled which makes the task assignment method in the Thin Kernel model real and distributed. The Thin Kernel model uses dynamic class loading and on-demand code transport. The collaboration of these technologies paves the way for large-scale parallel computing over wide-area networks.
Keywords :
grid computing; parallel programming; Thin Kernel model; dynamic class loading; fine-grained parallel programming; grid computing; on-demand code transport; parallel tasks; task assignment method; Collaboration; Concurrent computing; Dynamic scheduling; Grid computing; Kernel; Large-scale systems; Parallel processing; Parallel programming; Processor scheduling; Runtime;
Conference_Titel :
Services Computing, 2004. (SCC 2004). Proceedings. 2004 IEEE International Conference on
Print_ISBN :
0-7695-2225-4
DOI :
10.1109/SCC.2004.1358076