Package: hpcwld 0.6-5
Alexander Rumyantsev
hpcwld: High Performance Cluster Models Based on Kiefer-Wolfowitz Recursion
Probabilistic models describing the behavior of workload and queue on a High Performance Cluster and computing GRID under FIFO service discipline basing on modified Kiefer-Wolfowitz recursion. Also sample data for inter-arrival times, service times, number of cores per task and waiting times of HPC of Karelian Research Centre are included, measurements took place from 06/03/2009 to 02/30/2011. Functions provided to import/export workload traces in Standard Workload Format (swf). Stability condition of the model may be verified either exactly, or approximately. Stability analysis: see Rumyantsev and Morozov (2017) <doi:10.1007/s10479-015-1917-2>, workload recursion: see Rumyantsev (2014) <doi:10.1109/PDCAT.2014.36>.
Authors:
hpcwld_0.6-5.tar.gz
hpcwld_0.6-5.tar.gz(r-4.5-noble)hpcwld_0.6-5.tar.gz(r-4.4-noble)
hpcwld_0.6-5.tgz(r-4.4-emscripten)hpcwld_0.6-5.tgz(r-4.3-emscripten)
hpcwld.pdf |hpcwld.html✨
hpcwld/json (API)
| # Install 'hpcwld' in R: |
| install.packages('hpcwld', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- HPC_KRC - Workload data for High Performance Cluster of High Performance Data Center of Karelian Research Center, Russian Academy of Sciences.
- HPC_KRC2 - Workload data for High Performance Cluster of High Performance Data Center of Karelian Research Center, Russian Academy of Sciences.
- X - Dataset with raw workload data from HPDC KRC RAS
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:71ee8c9cd4. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 01 2024 |
| R-4.5-linux | OK | Dec 01 2024 |
Exports:ApproxCDataToSWFDMCFromSWFMaxThroughput2ToSWFWld
Dependencies:
