similar to: string substitution for argument in function

Displaying 8 results from an estimated 8 matches similar to: "string substitution for argument in function"

2018 Feb 12
2
[parallel] fixes load balancing of parLapplyLB
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 balancing the load. My colleague Dirk Sarpe and I found the cause of the problem and we also have a patch to fix it (attached). A similar fix has also been provided [here][2]. [1]:
2018 Feb 26
2
[parallel] fixes load balancing of parLapplyLB
Dear Christian and Henrik, thank you for spotting the problem and suggestions for a fix. We'll probably add a chunk.size argument to parLapplyLB and parLapply to follow OpenMP terminology, which has already been an inspiration for the present code (parLapply already implements static scheduling via internal function staticClusterApply, yet with a fixed chunk size; parLapplyLB already
2018 Feb 19
2
[parallel] fixes load balancing of parLapplyLB
Hi, I'm trying to understand the rationale for your proposed amount of splitting and more precisely why that one is THE one. If I put labels on your example numbers in one of your previous post: nbrOfElements <- 97 nbrOfWorkers <- 5 With these, there are two extremes in how you can split up the processing in chunks such that all workers are utilized: (A) Each worker, called
2018 Mar 01
0
[parallel] fixes load balancing of parLapplyLB
Dear Tomas, Thanks for your commitment to fix this issue and also to add the chunk size as an argument. If you want our input, let us know ;) Best Regards On 02/26/2018 04:01 PM, Tomas Kalibera wrote: > Dear Christian and Henrik, > > thank you for spotting the problem and suggestions for a fix. We'll probably add a chunk.size argument to parLapplyLB and parLapply to follow OpenMP
2016 Nov 24
1
[parallel-package] feature request: set default cluster type via environment variable
Dear all, I?m working as an administrator of a High-Performance Computing (HPC) Cluster which runs on Linux. A lot of people are using R on this Linux cluster and, of course, the *parallel* package to speed up their computations. It has been our collective experience, that using |makeForkCluster| yields an overall better experience /on Linux/ than the |makePSOCKcluster|, for whatever definition
2018 Feb 19
0
[parallel] fixes load balancing of parLapplyLB
Dear R-Devel List, I have installed R 3.4.3 with the patch applied on our cluster and ran a *real-world* job of one of our users to confirm that the patch works to my satisfaction. Here are the results. The original was a series of jobs, all essentially doing the same stuff using bootstrapped data, so for the original there is more data and I show the arithmetic mean with standard deviation. The
2007 Apr 28
1
freeRADIUS with winbindd, ntlm_auth on Samba 3.0.24
Hello I want to use ntlm_auth together with winbindd for RADIUS-authentication of users against the users of a Samba-server. The freeRADIUS-daemon and the Samba-, winbindd- and ntlm_auth binaries are all on the same machine. Samba works fine and the whole setup worked fine with Samba 3.0.22. Actually I have to set up this scenario on a machine with Samba 3.0.24 and it does not work at all :-(.
2018 Feb 20
0
[parallel] fixes load balancing of parLapplyLB
Dear Henrik, The rationale is just that it is within these extremes and that it is really simple to calculate, without making any assumptions and knowing that it won't be perfect. The extremes A and B you are mentioning are special cases based on assumptions. Case A is based on the assumption that the function has a long runtime or varying runtime, then you are likely to get the best load