Maybe this R-bloggers post could also help you:
https://www.google.es/amp/s/www.r-bloggers.com/implementing-parallel-processing-in-r/amp/
https://www.google.es/amp/s/www.r-bloggers.com/a-guide-to-parallelism-in-r/amp/
[[alternative HTML version deleted]]
You cannot send one task to 12 processors... the price of parallelism is that
you must break down your task into smaller tasks. Once you have number of tasks
equal to our more than the number of available cores then the higher level
functions such as parLapply or mclapply can shuffle tasks onto
Hi,
You already asked this here
(http://stackoverflow.com/questions/28357210/parallel-computing-in-r)
and got some comments.
Regards,
Pascal
On Fri, Feb 6, 2015 at 11:58 AM, Zhenchuan Wang wrote:
> I usually need to compute P-values as following:
> 1. generate one sample (usually it is a matri
I usually need to compute P-values as following:
1. generate one sample (usually it is a matrix)
2. apply several methods (I already wrote a subfunction for each method,
and they are independent) to the generated sample to get pvalues.
3. compare the pvalues.
Since each method mentioned above ta
4 matches
Mail list logo
