is some dynamism in the schedule even by default. I am now
> testing a patch with these changes.
>
> Best
> Tomas
>
>
> On 02/20/2018 11:45 AM, Christian Krause wrote:
>> Dear Henrik,
>>
>> The rationale is just that it is within these extremes and t
cale factor(*) argument where default
>future.scheduling = 1 corresponds to (B) and future.scheduling = +Inf
>to (A). Using future.scheduling = 4 achieves the amount of
>load-balancing you propose in (C). (*) Different definition from the
>above 'scale'. (Disclaimer: I'm the author)
patch fully source-compatible.
Best Regards
On 02/12/2018 08:08 PM, Christian Krause wrote:
> Dear R-Devel List,
>
> **TL;DR:** The function **parLapplyLB** of the parallel package has
> [reportedly][1] (see also attached RRD output) not
> been doing its job, i.e. not actually
he number of chunks is larger than the number of workers, if
possible at all, and then load balancing
should work.
Best Regards
--
Christian Krause
Scientific Computing Administration and Support
a "parallel environment" with 2 to 20 cores #$ -pe smp
2-20 # set number of cores for the R cluster to the granted value (between 2
and 20) export MC_CORES=$NSLOTS # we want this: export MC_CLUSTER_TYPE=FORK
Rscript /path/to/script.R |
Best Regards
--
Christian Krause
Scientific
