search for: upperbounds

I am investigating changing BoundsChecking to use address-based rather than size- & offset-based tests. To explain, here is a short code sample cribbed from one of the tests: %mem = tail call i8* @calloc(i64 1, i64 %elements) %memobj = bitcast i8* %mem to i64* %ptr = getelementptr inbounds i64* %memobj, i64 %index %4 = load i64* %ptr, align 8 Currently, the IR for bounds checking

Hi Kevin, Thanks for your interest and for your deep analysis. Unfortunately, your approach doesn't catch all bugs and is vulnerable to an attack. Consider the following case: ...................... | ----- obj --- | | end ^ ptr ^ ^ end-of-memory The scenario is as follows: - an object is allocated in the last page of the address space - obj is byte

...- as.vector(tail(head(mo,i),1)) wgt.vect <- as.vector(tail(head(moWeightsMax,i),1)) cov.mat <- cov(tail(head(morets,i+12),12)) opt.fun <- function(wgt.vect) -sum(Mo.vect %*% wgt.vect) / (t(wgt.vect) %*% (cov.mat %*% wgt.vect)) LowerBounds<-c(0.2,0.05,0.1,0,0,0) UpperBounds<-c(0.6,0.3,0.6,0.15,0.1,0.2) OptimSolution<-optim(wgt.vect, fn=opt.fun, method="L-BFGS-B",lower=LowerBounds,upper=UpperBounds) Any thoughts are appreciated! Mike Michael Ashton, CFA Managing Principal Enduring Investments LLC W: 973.457.4602 C: 551.655.8006 [[alternati...

Dear LLVM, Consider two loops with one interation - First with constant lower bound, second with usual non-constant lower bound: int main(int argc, char ** argv) { int numOfIterations= 1; int stride=1; int lowerBound = 1000; - 1st | int lowerBound = argc; - 2nd int upperBound = lowerBound + (numOfIterations - 1)*stride; int i = lowerBound;

On Mon, Feb 27, 2012 at 9:30 AM, Benjamin Kramer <benny.kra at googlemail.com> wrote: > > On 27.02.2012, at 17:13, Николай Лихогруд wrote: > >> Dear LLVM, >> >>     Consider two loops with one interation - >>     First with constant lower bound, second with usual non-constant lower bound: >> >>     int main(int argc, char ** argv) >>     {

Nuno, Inspired by this email thread, I spent a bit of time today looking through the implementation of BoundsChecking::instrument(..). Based on my reading of prior work, it should be possible to do these checks in two comparisons, or possibly even one if the right assumptions could be made. Could you provide a bit of background of the expected domains of Size and Offset? In particular,

On 27.02.2012, at 18:49, Eli Friedman wrote: > On Mon, Feb 27, 2012 at 9:30 AM, Benjamin Kramer > <benny.kra at googlemail.com> wrote: >> >> On 27.02.2012, at 17:13, Николай Лихогруд wrote: >> >>> Dear LLVM, >>> >>> Consider two loops with one interation - >>> First with constant lower bound, second with usual

On 27.02.2012, at 17:13, Николай Лихогруд wrote: > Dear LLVM, > > Consider two loops with one interation - > First with constant lower bound, second with usual non-constant lower bound: > > int main(int argc, char ** argv) > { > int numOfIterations= 1; > int stride=1; > int lowerBound = 1000; - 1st | int lowerBound =

...)) > wgt.vect <- as.vector(tail(head(moWeightsMax,i),1)) > cov.mat <- cov(tail(head(morets,i+12),12)) > opt.fun <- function(wgt.vect) -sum(Mo.vect %*% wgt.vect) / (t(wgt.vect) %*% (cov.mat %*% wgt.vect)) > > LowerBounds<-c(0.2,0.05,0.1,0,0,0) > UpperBounds<-c(0.6,0.3,0.6,0.15,0.1,0.2) > > OptimSolution<-optim(wgt.vect, fn=opt.fun, method="L-BFGS-B",lower=LowerBounds,upper=UpperBounds) > > > Any thoughts are appreciated! > > Mike > > Michael Ashton, CFA > Managing Principal > > Enduring Investme...

...vect <- as.vector(tail(head(moWeightsMax,i),1)) >> cov.mat <- cov(tail(head(morets,i+12),12)) >> opt.fun <- function(wgt.vect) -sum(Mo.vect %*% wgt.vect) / (t(wgt.vect) %*% (cov.mat %*% wgt.vect)) >> >> LowerBounds<-c(0.2,0.05,0.1,0,0,0) >> UpperBounds<-c(0.6,0.3,0.6,0.15,0.1,0.2) >> >> OptimSolution<-optim(wgt.vect, fn=opt.fun, method="L-BFGS-B",lower=LowerBounds,upper=UpperBounds) >> >> >> Any thoughts are appreciated! >> >> Mike >> >> Michael Ashton, CFA >> Ma...

Well, we are getting somewere...;) >It is probably 'greyed' out because no Windows tools use it or will add it. You will probably need to use Unix tools (ldb or ldap) to remove>them, but you can if you so wish ignore them. What you should never do is to rely on them being there, because they may or may not be there.Ok, I'll let it be there> You need to remove the gidNumber

...r(tail(head(moWeightsMax,i),1)) >>> cov.mat <- cov(tail(head(morets,i+12),12)) >>> opt.fun <- function(wgt.vect) -sum(Mo.vect %*% wgt.vect) / (t(wgt.vect) %*% (cov.mat %*% wgt.vect)) >>> >>> LowerBounds<-c(0.2,0.05,0.1,0,0,0) >>> UpperBounds<-c(0.6,0.3,0.6,0.15,0.1,0.2) >>> >>> OptimSolution<-optim(wgt.vect, fn=opt.fun, method="L-BFGS-B",lower=LowerBounds,upper=UpperBounds) >>> >>> >>> Any thoughts are appreciated! >>> >>> Mike >>> >>>...

...) > >>> cov.mat <- cov(tail(head(morets,i+12),12)) > >>> opt.fun <- function(wgt.vect) -sum(Mo.vect %*% wgt.vect) / > (t(wgt.vect) %*% (cov.mat %*% wgt.vect)) > >>> > >>> LowerBounds<-c(0.2,0.05,0.1,0,0,0) > >>> UpperBounds<-c(0.6,0.3,0.6,0.15,0.1,0.2) > >>> > >>> OptimSolution<-optim(wgt.vect, fn=opt.fun, method="L-BFGS-B",lower= > LowerBounds,upper=UpperBounds) > >>> > >>> > >>> Any thoughts are appreciated! > >>> > &gt...

*From:* flang-dev <flang-dev-bounces at lists.flang-compiler.org> *On Behalf Of *Eric Schweitz (PGI) *Sent:* Thursday, November 01, 2018 1:02 PM *To:* flang-dev at lists.flang-compiler.org *Subject:* [Flang-dev] RFC: Adding debug information to LLVM to support Fortran In order to support debugging in the Flang project, work has been done to extend LLVM debug information for the Fortran

Hi everyone, I have been using adaptIntegrate from the cubature package for a multidimensional integral that has infinite variance (and so not appropriate for Monte Carlo techniques). Most of the time it works but sometimes (though not always) when I slightly increase the accuracy I want, or increase the bounds of integration I get the following error: REAL() can only be applied to a

Hi, You can use the projectLinear argument in BB::spg to optimize with linear equality/inequality constraints. Here is how you implement the constraint that all parameters sum to 1. require(BB) spg(par=p0, fn=myFn, project="projectLinear", projectArgs=list(A=matrix(1, 1, length(p0)), b=1, meq=1)) Hope this is helpful, Ravi [[alternative HTML version deleted]]

Dear list: A datafile was sent to me that is very large (92890 x 1620) and is *very* sparse. Instead of leaving the entries with missing data blank, each cell with missing data contains a dot (.) The data are binary in almost all columns, with only a few columns containing whole numbers, which I believe requires 2 bytes for the binary and 4 for the others. So, by my calculations (assuming 4

Dear R-users I intend to create a function which calls some smaller other functions in return. Some of these smaller functions all call some functions. I do not know a good way to do this. I tried using the source() function to include the smaller functions within the main functions before they are called. This does not work, or maybe i am not doing the right thing. For example: the

>When you provision a new domain, it is set 3000000, but, seemingly, when you run the classicupgrade it gets sets to a lower number (never actually run a classicupgrade) based on what is in your old domain. > Not sure what to suggest here, do you feel up to sending me (offlist) a copy of your idmap.ldb ? > >Rowland Thank you again, Rowland, for your time. I think that different ID

Regarding flags, I was just thinking that maybe we should invent a new DISubprogramFlags type. DISubprogram already has a few bitfields for subprogram-specific things, Fortran will want 3 more, and there's no reason to fill up the generic DIFlags with more bits that are used in only one class. I agree that the array stuff needs to be designed with an eye to handling how other languages do