Kevin,
On Mar 18, 2009, at 12:08 , Kevin Hendricks wrote:
I don't think so, because IMHO it makes no sense - you're missing
the main point that R is not thread safe. There are ways to use
threads from within R very cautiously (see Luke's parallelized
vector math operations for R for exampl
> Is there any official effort underway to make R thread-safe? If so,
> are they looking for volunteers.
I'm looking forward to the answer to this question!
> Would making R fully thread-safe
> really make that much sense given you can parallelize vector/matrix
> operations now (as you noted) wh
Hi,
I don't think so, because IMHO it makes no sense - you're missing
the main point that R is not thread safe. There are ways to use
threads from within R very cautiously (see Luke's parallelized
vector math operations for R for example). There are many good
methods to use threads in
On Mar 18, 2009, at 7:11 , Ted Byers wrote:
of thing I did when writing
code to run on a supercomputer supporting vector algebra decades ago).
With ITT, if Lapack was rewritten to take advantage of it, much of
the code would look quite different from what it does today. Of
course, if you're al
On Mar 18, 2009, at 10:11 , Ted Byers wrote:
On Wed, Mar 18, 2009 at 9:28 AM, Simon Urbanek
wrote:
Things cannot happen if you don't ask ...
Cheers,
Simon
Then I have two questions.
1) What multicore package? I didn't know there was one, and would
be interested in seeing what it does.
On 18 March 2009 at 09:56, hadley wickham wrote:
| On Wed, Mar 18, 2009 at 9:11 AM, Ted Byers wrote:
| > 1) What multicore package? I didn't know there was one, and would be
| > interested in seeing what it does.
|
| http://tinyurl.com/cudqqf
|
| ;)
Readers of the CRANberries RSS feed knew ab
On Mar 18, 2009, at 9:45 , Rune Schjellerup Philosof wrote:
Simon Urbanek wrote:
On Mar 18, 2009, at 8:59 , Rune Schjellerup Philosof wrote:
A simple example of use:
data1 <- data2 <- matrix(0, r, c)
dataFiller <- function(i) {
tmp <- someCalculation(i)
data1[, i] <<- tmp$result1
data2[, i
On Wed, Mar 18, 2009 at 9:11 AM, Ted Byers wrote:
> On Wed, Mar 18, 2009 at 9:28 AM, Simon Urbanek
> wrote:
>> Things cannot happen if you don't ask ...
>>
>> Cheers,
>> Simon
>>
> Then I have two questions.
>
> 1) What multicore package? I didn't know there was one, and would be
> interested in
On Wed, Mar 18, 2009 at 9:28 AM, Simon Urbanek
wrote:
> Things cannot happen if you don't ask ...
>
> Cheers,
> Simon
>
Then I have two questions.
1) What multicore package? I didn't know there was one, and would be
interested in seeing what it does.
2) Has there been any consideration of using
Simon Urbanek wrote:
> On Mar 18, 2009, at 8:59 , Rune Schjellerup Philosof wrote:
>> A simple example of use:
>> data1 <- data2 <- matrix(0, r, c)
>> dataFiller <- function(i) {
>> tmp <- someCalculation(i)
>> data1[, i] <<- tmp$result1
>> data2[, i] <<- tmp$result2
>> }
>> runParallelIn
On Mar 18, 2009, at 8:59 , Rune Schjellerup Philosof wrote:
Duncan Temple Lang wrote (Mon Nov 7 22:35:22 CET 2005):
R is not yet thread safe.
We are working on it, and I hope to make some progress before
the end of the year. (This one even!)
D.
How is this going along?
For some things it
On Mon, Nov 07, 2005 at 07:57:28PM +0100, [EMAIL PROTECTED] wrote:
> I would like to accelerate my R computation by using parallel OpenMP
> compilers (e.g from Pathscale) on a 2-processor AMD server and I
> would like to know whether R is a tread safe library. The main
R is not thread safe, but o
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Hash: SHA1
R is not yet thread safe.
We are working on it, and I hope to make some progress before
the end of the year. (This one even!)
D.
[EMAIL PROTECTED] wrote:
> Dear R-dev,
>
> I would like to accelerate my R computation by using parallel OpenMP com
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