search for: deoptimization

Dear R users, During the the running of DEoptim function which belongs to "DEoptim" package it automatically gives the output like the following: Iteration: 1 bestvalit: 181.379847 bestmemit: 0.226499 1.395852 Iteration: 2 bestvalit: 14.062649 bestmemit: 2.290357 5.597838 Iteration: 3 bestvalit: 14.062649 bestmemit: 2.290357 5.597838 Iteration: 4 bestvalit: 14.062649

Function DEoptim in package DEoptim for differential evolution defines an optional parameter fnMap: fnMap "an optional function that will be run after each population is created, but before the population is passed to the objective function. This allows the user to impose integer/cardinality constriants." Unfortunately, there is no further documentation decribing the kind of

Dear All, We are happy to announce the release of the new version of DEoptim (version 2.0-0) which is now available from CRAN. The DEoptim package [3] performs Differential Evolution (DE) minimization, a genetic algorithm-based optimization technique [2,3]. This allows robust minimization over a continuous (bounded or not) domain. The new DEoptim function calls a C implementation of the DE

Dear All, We are happy to announce the release of the new version of DEoptim (version 2.0-0) which is now available from CRAN. The DEoptim package [3] performs Differential Evolution (DE) minimization, a genetic algorithm-based optimization technique [2,3]. This allows robust minimization over a continuous (bounded or not) domain. The new DEoptim function calls a C implementation of the DE

Dear R Community, I am trying to optimize a water quality model that I am using. Based on conversations with others more familiar with what I am doing I plan to implement DEOptim to do this. The water quality model is interfaced through a GUI. I have the input file necessary to alter parameters and run the model as a text file. To do the optimization I have figured out the general procedure

On Wed, Feb 17, 2016 at 8:53 PM, Philip Reames <listmail at philipreames.com> wrote: > I think you're jumping ahead a bit here. I'm not sure the semantics are > anywhere near as weird as you're framing them to be. :) I now think this weirdness actually does not have to do anything with guard_on or bail_to_interpeter, but it has to do with deopt bundles itself. Our

I am trying to figure out how parameters are defined in a function that is used by DEOptim. That is, when I set upper and lower bounds for DEOptim how does it know which element of the function to apply those bounds to? For example, in DEOptim call below, when DEOptim goes into "optimfxn" how does it know what element of "optimfxn" to apply the upper and lower bounds to?

(the same mail was sent to the author) When I called the function DEoptim with control=list(strategy=1) or control=list(strategy=2) I got the error: Error in mui[rtd + 1, i] : incorrect number of dimensions Analysis of the source code of the DEoptim reveals the following fragment if (con$strategy > 5) st <- con$strategy - 5 ## binomial crossover else { st <-

Hi R-Core, i am using nnet and DEoptim, Xcc=matrix(rnorm(100,0.5,0.08),50,2) Ycr=matrix(rnorm(50,0.2,0.05),50,1) pred_regm1 <- function(A) { A1=A[1] A2=A[2] A3=A[3] regm1 <- nnet(Xcc,Ycr,entropy=T,size=A1,decay=A2,maxit=2000,trace=F,Hess=T,rang=A3,skip=T) dif=sum((predict(regm1,Xcc)-Ycr)^2) return(dif) } somar=DEoptim(pred_regm1,c(1,0.00001,0.01), c(25,0.999,0.95),

...nly further convinces me > that Michael's proposed intrinsics are the best way to go. I'm still not convinced, but am not going to actively oppose it either. I'm leery of designing a solution with major assumptions we don't have data to backup. I worry your assumptions about deoptimization are potentially unsound. But I don't have data to actually show this (yet). > > On April 29, 2014 at 10:09:49 AM, Philip Reames > (listmail at philipreames.com <mailto:listmail at philipreames.com>) wrote: > >> As the discussion has progressed and I've spent more...

...#39;s proposed intrinsics are the best way to go. >> I'm still not convinced, but am not going to actively oppose it >> either. I'm leery of designing a solution with major assumptions we >> don't have data to backup. >> >> I worry your assumptions about deoptimization are potentially >> unsound. But I don't have data to actually show this (yet). > > I *think* I may have been unclear about my assumptions; in particular, > my claims with respect to deoptimization are probably more subtle than > they appeared. WebKit can use LLVM and it h...

Hello Everyone, I want to raise a discussion about @llvm.experimental.guard intrinsic and reasons why we should give up using it. Here is an alternative approach to representation of guards that resolves some of fundamental flaws that the current guards have. Basically, this intrinsic was introduced to model the following situation: we want to check that some condition is true, and if it's

...ay to go. >>>> I'm still not convinced, but am not going to actively oppose it >>>> either. I'm leery of designing a solution with major assumptions >>>> we don't have data to backup. >>>> >>>> I worry your assumptions about deoptimization are potentially >>>> unsound. But I don't have data to actually show this (yet). >>> >>> I *think* I may have been unclear about my assumptions; in >>> particular, my claims with respect to deoptimization are probably >>> more subtle than they...

...gt; Michael's proposed intrinsics are the best way to go.  >  > I'm still not convinced, but am not going to actively oppose it either. I'm  > leery of designing a solution with major assumptions we don't have data to  > backup.  >  > I worry your assumptions about deoptimization are potentially unsound. But  > I don't have data to actually show this (yet).  >  > I *think* I may have been unclear about my assumptions; in particular, my  > claims with respect to deoptimization are probably more subtle than they  > appeared. WebKit can use LLVM and it has d...

...o you think it would be a good change to push upstream given we might not be able to do it in all cases (say, always fall back to rsp-based if the frame is aligned)? >>> Can I ask what you're using the deopt information for? Do you have a >>> language runtime which supports deoptimization? Or are you using it >>> for something different? If so, what? I'm curious to know how others >>> are using the infrastructure. >> >> Sure. >> I am working on LLV8, which is an attempt to use LLVM MCJIT as a >> backend >> for Google V8. So yes,...

...or other "deopt" call > site. The simple solution for this is to disallow "deopt" of readonly > calls. Assuming we're talking about the same thing, the concern was more along the lines of: you cannot do IPA on a callsite that calls something that contains a potential deoptimization point, be it either for a @guard_on call, or a "normal" deoptimization safepoint. This is because if you have: ``` void @something() void callee() { call @something() [ "deopt"(state0) ] *ptr = 100; } void caller() { call @callee() // whether this is a "deopt&quo...

...d it be hard to make the statepoint intrinsic produce frame pointer based offset (instead of sp-based) if "no-frame-pointer-elim"="true" attribute is specified? > Can I ask what you're using the deopt information for? Do you have a > language runtime which supports deoptimization? Or are you using it > for something different? If so, what? I'm curious to know how others > are using the infrastructure. Sure. I am working on LLV8, which is an attempt to use LLVM MCJIT as a backend for Google V8. So yes, we have a language runtime which supports deoptimization....

Hi Sanjoy, Thanks for feedback! As for memory effects, currently I use " inaccessiblememonly " for it. It allows to prove that it doesn't alias with any other load/store in the function, but doesn't allow CSE to eliminate it. It is not actually super-cool, because there is no way that we can safely hoist it out of loop (and sometimes we want to, for example to make unswitching).

...opose a scheme to attach "operand bundles" to call and invoke instructions. This is based on the offline discussion mentioned in http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-July/088748.html. # Motivation & Definition Our motivation behind this is to track the state required for deoptimization (described briefly later) through the LLVM pipeline as a first-class IR citizen. We want to do this is a way that is generally useful. An "operand bundle" is a set of SSA values (called "bundle operands") tagged with a string (called the "bundle tag"). One or more o...

Hi everyone, we started a new open source project Sulong: https://github.com/graalvm/sulong. Sulong is a LLVM IR interpreter with JIT compilation running on top of the JVM. By using the Truffle framework, it implements speculative optimizations such as inlining of function pointer calls through AST rewriting. One area of our research is to provide alternative ways of executing LLVM bitcode that