Name
Abstract | ||
|---|---|---|
We have previously documented the on-going work in the EUFORIA project to parallelise and optimise European fusion simulation codes. This involves working with a wide range of codes to try and address any performance and scaling issues that these codes have. However, as no two simulation codes are exactly the same, it is very hard to apply exactly the same approach to optimising a disparate range of codes. Indeed, the codes investigated range in terms of performance and ability from well-optimised, highly parallelised codes, to serial or poorly performing codes. After analysing, optimising, and parallelising a range of codes it is, actually, possible to discern a number of distinct optimisation techniques or approaches/strategies that can be used to improve the performance or scaling of a parallel simulation code. This paper outlines the distinct approaches that we have identified, highlighting their benefits and drawbacks, giving an overview of the type of work that is often attempted for fusion simulation code optimisation. performing codes. After analysing, optimising, parallelising, and scaling a range of codes it is, actually, possible to discern a number of distinctoptimisation techniques or approaches/strategies that can be used to improve the performance or scaling of a parallel simulation code. This paper outlines the distinct approaches that we have identified, highlighting their benefits and drawbacks, giving an overview of the type of work that is often attempted for fusion simulation code optimisation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/PDP.2011.15 | PDP |
Keywords | Field | DocType |
parallel optimisation strategies,optimise european fusion simulation,fusion simulation code optimisation,simulation code,distinct optimisation technique,parallel simulation code,wide range,distinct approach,on-going work,parallelised code,fusion codes,disparate range,computational modeling,artificial neural network,codes,computer model,optimization,fusion,parallel processing,computer architecture,hpc,bandwidth,artificial neural networks | Parallel simulation,Computer science,Parallel computing,Parallel processing,Fusion,Bandwidth (signal processing),Artificial neural network,Scaling | Conference |
ISSN | Citations | PageRank |
1066-6192 | 0 | 0.34 |
References | Authors | |
4 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrian Jackson | 1 | 10 | 7.31 |
| Fiona Reid | 2 | 0 | 0.34 |
| Stephen Booth | 3 | 2 | 1.49 |
| Joachim Hein | 4 | 0 | 0.34 |
| Jan Westerholm | 5 | 96 | 16.56 |
| Mats Aspnas | 6 | 1 | 0.70 |
| Miquel Catala | 7 | 0 | 0.34 |
| Alejandro Soba | 8 | 5 | 4.59 |