Name
Abstract | ||
|---|---|---|
Large parallel machines with hundreds of thousands of processors are being built. Recent studies have shown that ensuring good load balance is critical for scaling certain classes of parallel applications on even thousands of processors. Centralized load balancing algorithms suffer from scalability problems, especially on machines with relatively small amount of memory. Fully distributed load balancing algorithms, on the other hand, tend to yield poor load balance on very large machines. In this paper, we present an automatic dynamic hierarchical load balancing method that overcomes the scalability challenges of centralized schemes and poor solutions of traditional distributed schemes. This is done by creating multiple levels of aggressive load balancing domains which form a tree. This hierarchical method is demonstrated within a measurement-based load balancing framework in Charm++. We present techniques to deal with scalability challenges of load balancing at very large scale. We show performance data of the hierarchical load balancing method on up to 16,384 cores of Ranger (at TACC) for a synthetic benchmark. We also demonstrate the successful deployment of the method in a scientific application, NAMD with results on the Blue Gene/P machine at ANL. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPPW.2010.65 | ICPP Workshops |
Keywords | Field | DocType |
scalability challenge,hierarchical method,load balancing,large supercomputers,measurement-based load,centralized load,aggressive load,hierarchical load,good load balance,automatic dynamic hierarchical load,poor load balance,resource allocation,load balance,lead,scalability,memory management,databases,parallel processing | Load management,Software deployment,Network Load Balancing Services,Computer science,Load balancing (computing),Blue gene,Parallel computing,Memory management,Resource allocation,Distributed computing,Scalability | Conference |
Citations | PageRank | References |
20 | 0.92 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gengbin Zheng | 1 | 829 | 55.03 |
| Esteban Meneses | 2 | 234 | 16.82 |
| Abhinav Bhatele | 3 | 625 | 43.42 |
| Laxmikant V. Kale | 4 | 2871 | 248.18 |