search for: convergence

Hi Jingyue, I consider it a very important element of the design of convergent that it does not require baseline LLVM to contain a definition of uniformity, which would itself pull in a definition of SIMT/SPMD, warps, threads, etc. The intention is that it should be a conservative (but hopefully not too conservative) approximation, and that implementations of specific GPU programming models

Hi all, In light of recent discussions regarding updating passes to respect convergent semantics, and whether or not it is sufficient for barriers, I would like to propose a change in convergent semantics that should resolve a lot of the identified problems regarding loop unrolling, loop unswitching, etc. Credit to John McCall for talking this over with me and seeding the core ideas. Today,

...Folks! Just started using the gamlss package and I tried a simple code example (see below). Why the negative sigma? John > y <- rt(100, df=1)> m1<-fitDist(y, type="realline")Warning messages:1: In MLE(ll3, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma, : possible convergence problem: optim gave code=1 false convergence (8)2: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma, : possible convergence problem: optim gave code=1 false convergence (8)3: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma, : possible convergence problem: optim...

Hi, When I run the following code : Y <- c(rep(0,35),1,2,0,6,8,16,43) cst <- log(choose(42, 42:1)) beta <- 42:1 tau <- (beta^2)/2 fit <- glm(formula = Y ~ offset(cst) + beta + tau, family = poisson) fit fit$converged glm prints a warning saying that the algorithm did not converge. However, fit$converged takes the value TRUE. I don't understand why fit$converged is not

...t anl.gov> wrote: > Thanks for sending this. What do you think that we should do with the > existing convergent attribute? My preference, which is implicitly expressed in the review, is to use `convergent` both for the new and the old thing. They are implicitly distinguished via the "convergencectrl" operand bundle. The main reason for going down that route is that `convergent` is really an odd duck in that it is the only attribute in LLVM that _adds_ new constraints on program transforms. All other attributes _remove_ constraints on program transforms by expressing constraints on wh...

...nvergent operation -- is potentially far away from the paths that we're short-cutting. We want to avoid this "spooky action at a distance" because it puts an undue burden on generic code transforms. The Solution ------------ We introduce explicit annotations in the IR using "convergence tokens" that "anchor" a convergent operation with respect to some other point in control flow or with respect to the function entry. The details are in the linked Phabricator review, so I will simply illustrate here how this solves the example above. To obtain the original natur...

...ending this. What do you think that we should do with the > >> existing convergent attribute? > > My preference, which is implicitly expressed in the review, is to use > > `convergent` both for the new and the old thing. They are implicitly > > distinguished via the "convergencectrl" operand bundle. > > > > The main reason for going down that route is that `convergent` is > > really an odd duck in that it is the only attribute in LLVM that > > _adds_ new constraints on program transforms. All other attributes > > _remove_ constraints on p...

Hi Jingyue, Convergent is not intended to prevent inlining. It’s tricky to formalize this inter-procedurally, but the intended interpretation is that a convergent operation cannot be move either into or out of a conditionally executed region. Normal inlining would not violate that. I would imagine that it would make sense to use a combination of convergent and noduplicate for barrier-like

Full_Name: Bonnie Version: 1.6.1 OS: Windows Submission from: (NULL) (160.129.25.106) glm() seems to converge, even when it shouldn't. I am trying to fit a model where $converge=FALSE and I am fitting models that do not converge in SAS, but they seem to converge in R ... Thank you.

Hi Mehdi, My reading of it is that if you have a convergent instruction A, it is legal to duplicate it to instruction B if (assuming B is after A in program flow) A dominates B and B post-dominates A. James On Fri, 14 Aug 2015 at 08:32 Mehdi Amini via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On Aug 13, 2015, at 9:43 PM, Owen Anderson via llvm-dev < > llvm-dev at

...kes algorithm keeps repeating until a solution is converged?do i use a for loop? i know that we can use for loop to ask for a number of repetitions, but how to use it to ask the algorithm to keep repeating until a solution is converged? Thanks -- View this message in context: http://www.nabble.com/convergence-tf3606834.html#a10076822 Sent from the R help mailing list archive at Nabble.com.

I really want to do this: abline( a=tan(-kT*pi/180), b=kY-tan(-kT*pi/180)*kX ) where kX,kY and kT are vectors of equal length. But I can't do that with abline unless I use a loop, and I haven't figured out the least unelegant way of writing the loop yet. So is there a way to do this without a loop? Or if I am to resort to the loop, what's the best way of doing it considering that I

...king for portable use of $BLAS_LIBS ... OK * checking tests ... make[3]: Entering directory `/home/mfa/gilp/toolchain/R/src/R-rc/tests/stats.Rcheck/tests' Running 'nafns.R' Running 'nls.R' Comparing 'nls.Rout' to 'nls.Rout.save' ...134c134 < Achieved convergence tolerance: 2.75e-06 --- > Achieved convergence tolerance: 2.74e-06 145c145 < 3: 0.00060639084: 0.00517051 0.999153 --- > 3: 0.00060639084: 0.00517052 0.999153 214c214 < Achieved convergence tolerance: 1.04e-07 --- > Achieved convergence tolerance: 1.34e-07 249c249 < Achieve...

> On Sep 14, 2015, at 12:15 PM, Philip Reames <listmail at philipreames.com> wrote: > > On 09/04/2015 01:25 PM, Owen Anderson via llvm-dev wrote: >> Hi all, >> >> In light of recent discussions regarding updating passes to respect convergent semantics, and whether or not it is sufficient for barriers, I would like to propose a change in convergent semantics that

...at various time points within each grid cell. I'm trying to use a 'for' loop to try the model fit on each grid cell. In some cells lme does not converge, giving me the error: Error message: In lme.formula(logarea ~ year + summ_d, data = grid2, random = ~year + : nlminb problem, convergence error code = 1 message = iteration limit reached without convergence (9) When I get the error, the program aborts, and my loop stops. I'm not too worried about the error, as a generic mixed model structure may not be the best fit for every cell. I expect the optimization to fail in some...

Hello, I am working from a linux 64 machine on a server with R-2.12 (I can't update to 2.13). I am iterating through many linear mixed models for longitudinal data and I occasionally receive the following convergence error: > BI.lme <- lme(cd4 ~ time + genBI + genBI:time + C1 + C2 + C11 + C12, random =~ 1 + time | IID, data = d) Error in lme.formula(cd4 ~ time + genBI + genBI:time + PC1 + : nlminb problem, convergence error code = 1 message = false convergence (8) >From iteration to iteration,...

...- data.frame(x=x, y=y) model <- nls(y ~ a * (1+m*exp(-x/tau)) / (1+n*exp(-x/tau)), data=d, start=list(a=277,m=100,n=101,tau=10), algorithm='port', trace=TRUE, control=nls.control(maxiter=5000, minFactor=1/2048)) Running the above code I get the following error message: Convergence failure: function evaluation limit reached without convergence (9). To investigate this further I used nlminb() to get a set of starting parameters. Thus I did: func <- function( par ) { a = par[1] m = par[2] n = par[3] tau = par[4] a * (1+m*exp(-x/tau)) / (1+n*exp(-x/tau))...

...) including brood identity (c) as random factor. However, I get the following error message; lmer(a~b + (1|c), family=poisson, data=tab) Error in devAGQ(PQLpars, 1) : Unable to invert singular factor of downdated X'X In addition: Warning messages: 1: optim or nlminb returned message singular convergence (7) in: LMEopt(x = mer, value = cv) 2: optim or nlminb returned message singular convergence (7) in: LMEopt(x = mer, value = cv) 3: optim or nlminb returned message singular convergence (7) in: LMEopt(x = mer, value = cv) 4: optim or nlminb returned message singular convergence (7) in: L...

Hola Carlos, Gracias por la respuesta. phen_tot es un data frame visualizado como tibble, y contiene (entre otras) las columnas "convergence", "r_square" y "maxlog10mfi". Y queremos crear nuevas columnas, como "use", "convergence_cor", etc. phen_tot$convergence debería ser un factor de si el modelo converge o no (levels: 1 y 2), pero tibble lo tiene como "double". Pensamos que de a...

What are some reliable R functions that can compute the value of a convergent series? David -- David R. Bickel, PhD Associate Professor Ottawa Institute of Systems Biology Biochem., Micro. and I. Department Mathematics and Statistics Department University of Ottawa 451 Smyth Road Ottawa, Ontario K1H 8M5 http://www.statomics.com Office Tel: (613) 562-5800 ext. 8670 Office Fax: (613) 562-5185