Name
Abstract | ||
|---|---|---|
The mathematical frameworks of two schedulers, SCOW and UMR, are used to tune up parameters that optimize the amount of communications and parallel computations in a single-program multiple-data parallel code, under certain constraints. Comparisons are made with simulated data that is fed into the mathematical models, and with performance data taken from the scheduling of a parallel method for finding a string motif in a family of DNA sequences. The latter compares also the make-spans predicted by the underlying mathematical models with the actual results. Some considerations on the validity of the theoretical frameworks and the potential for a hybrid SCOW-UMR scheduler are presented, as well. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/HPCC.2009.96 | HPCC |
Keywords | Field | DocType |
actual result,dna sequence,underlying mathematical model,parallel method,mathematical model,performance data,simulated data,parallel computation,master-worker scheduling methods,mathematical framework,single-program multiple-data parallel code,dna sequences,high performance computing,data mining,parallel computer,computational modeling,computer networks,mathematical analysis,constraint optimization,concurrent computing,production,linear regression,dna,scheduling,cluster computing,parallel programming | Computer science,Scheduling (computing),Parallel computing,Tune-up,Mathematical model,Processor scheduling,Computer cluster,Distributed computing,Computation | Conference |
Citations | PageRank | References |
2 | 0.51 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luis de la Torre | 1 | 104 | 11.63 |
| Jaime Seguel | 2 | 39 | 10.02 |