similar to: how to add my own passes to LTO pass

Hi. I'm trying to implement a module pass which can be dynamically loaded by `opt` (against up-to-date llvm from svn). Despite what the tutorial (http://llvm.org/docs/WritingAnLLVMPass.html) states in my module pass I cannot perform getAnalysis and fetch the function pass result. When trying to do so `opt` fails with the following mesage: [***@*** ***]$ opt -load

Dear list, I encounter an error when I try to use ddply to generate means as follows: fun3<-structure(list(sector = structure(list(gics_sector_name = c("Financials", "Financials", "Materials", "Materials")), .Names = "gics_sector_name", row.names = structure(c("UBSN VX Equity", "LLOY LN Equity", "AI FP Equity",

On 6/15/11 6:46 PM, Alexey Bakhirkin wrote: > Hi. I'm trying to implement a module pass which can be dynamically > loaded by `opt` (against up-to-date llvm from svn). > Despite what the tutorial > (http://llvm.org/docs/WritingAnLLVMPass.html) states in my module pass > I cannot perform getAnalysis and fetch the function pass result. > When trying to do so `opt` fails with the

Thanks, John. There were a couple of function declarations in the module, and 'getAnalysis' failed for those. By the way, what do you mean by "in older versions of LLVM"? I'm quite sure I was using the latest llvm trunk. 2011/6/16 John Criswell <criswell at cs.uiuc.edu>: > On 6/15/11 6:46 PM, Alexey Bakhirkin wrote: >> Hi. I'm trying to implement a module

On Jul 23, 2010, at 7:36 AM, John Criswell wrote: > 2) For prerequisite *analysis* passes (like LoopInfo), your ModulePass > can declare them as prerequisites and get access to them using the > getAnalysis<PassName>(Function *) method. Yes, I remember trying this before but was unsuccessful. I made a second attempt just now and am again running into the same issue: bool

Full_Name: Yi-Xiong Zhou Version: 1.5.1 OS: win2000pro Submission from: (NULL) (64.169.249.42) Update() can not find objects when it is used in a function, which is in turn being called by another function. Here is a R script to show the problem: ######## begin of the test script ########## fun1 <- function() { x <- matrix(rnorm(500), 20,25) y <- rnorm(20) oo <- lm(y~x)

Hello everybody, I don't understand what I'm doing wrong. But it isn't possible that each element of the if-condition is tested for each vector element? y <- c(1:20) > y [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 > if (y == c(4,5,9,11,17)) { print("yes") } else { print("no")} [1] "no" warning: In if (y == c(4, 5, 9, 11,

Trevor Harmon wrote: > On Jul 22, 2010, at 2:05 PM, John Criswell wrote: > > >> If you write your pass as a ModulePass, then you can iterate over the >> functions in any order that you want. >> > > I had considered that, but my FunctionPass depends on other passes > processing the functions first: > Two things to consider: 1) The PassManager

On Jul 22, 2010, at 2:05 PM, John Criswell wrote: > If you write your pass as a ModulePass, then you can iterate over the > functions in any order that you want. I had considered that, but my FunctionPass depends on other passes processing the functions first: void MyPass::getAnalysisUsage(AnalysisUsage &AU) const { AU.addRequired<UnifyFunctionExitNodes>();

Dear R experts Sorry for this question M1 <- 1:10 lcd1 <- c(11, 22, 33, 44, 11, 22, 33, 33, 22, 11) lcd2 <- c(22, 11, 44, 11, 33, 11, 22, 22, 11, 22) lcd3 <- c(12, 12, 34, 14, 13, 12, 23, 23, 12, 12) #generating variables through sampling pvec <- c("PR1", "PR2", "PR3", "PR4", "PR5", "PR6", "PR7",

Dear all, model.frame behaves in a way I don't expect when both its formula and subset argument are passed through a function call. This works as expected: model.frame(~wool, warpbreaks, breaks < 15) #> wool #> 14 A #> 23 A #> 29 B #> 50 B fun1 <- function(y) model.frame(~wool, warpbreaks, y) fun1(with(warpbreaks, breaks < 15)) #> wool #> 14

Hello, Rlisters I have to compute p-values that are on the tail of the distribution, P-values < 10^-20. However, my current implementations enable one to estimate P-values up to 10^-12, or so. A typical example is found below, where t is my critical value. ########### example - code adapted from Rassoc ####################### rho01 = 0.5 rho105 = 0.5 rho005 = 0.5 t = 8 z = 2

Hello, I'd appreciate it if anyone can tell me what the error message means and point out what I am doing wrong. Thank you. I am trying to use the result of the DominatorTree analysis in my ModulePass class as explained in the section "Writing an LLVM Pass". http://llvm.org/docs/WritingAnLLVMPass.html#interaction I called the method "addRequired<DominatorTree>()"

On Oct 30, 2010, at 4:38 AM, Duncan Sands wrote: >> Is there any facility in LLVM to identify recursion in a call graph? ... > use the facilities in SCCIterator.h, or declare your pass to be a > CallGraphSCCPass in which case it will work one strongly connected > component at a time. Converting my ModulePass to a CallGraphSCCPass doesn't seem feasible, so I'll use

Hi, I have two matrices, A (axd) and B (bxd). I want to get another matrix C (axb) such that, C[i,j] is the Euclidean distance between the ith row of A and jth row of B. In general, I can say that C[i,j] = some.function (A[i,], B[j,]). What is the best method for doing so? (assume a < b) I have been doing some exploration myself: Consider the following function: get.f, in which,

Dear R users, i have this problem with matrices i want to check between two matrices if they are isomorphic i will give an example for what excactly i want   1 -1  1                                 -1  1   1 -1   1  -1                                1  -1  -1   1  1   -1                                1   1  -1 this two matrices are isomorphic beacause if i change the first 2 columns the matrices

Hi, I'm trying to implement a module pass as a share object to process an entire program as a unit. The target program is built from multiple object files, hence multiple bitcode files. However, it seems that opt does not take the whole program, but just one bitcode file, "test.bc" in the example run shown below. $ opt -load mypass.dylib -mymodulepass < test.bc > /dev/null

I R-helpers #I have a data panel of thousands of firms, by year and industry and #one dummy variable that separates the firms in two categories: 1 if the firm have an auditor; 0 if not #and another variable the represents the firm dimension (total assets in thousand of euros) #I need to create two separated samples with the same number os firms where #one firm in the first have a corresponding

On Thu, Jun 4, 2015 at 3:58 PM, Duncan P. N. Exon Smith < dexonsmith at apple.com> wrote: > > > Personally, I think the right approach is to add a bool to > createGlobalDCEPass defaulting to true named something like > IsAfterInlining. In most standard pass pipelines, GlobalDCE runs after > inlining for obvious reasons, so the default makes sense. The special case > is

On Thu, Jun 4, 2015 at 5:33 PM, Reid Kleckner <rnk at google.com> wrote: > On Thu, Jun 4, 2015 at 5:17 PM, Teresa Johnson <tejohnson at google.com> wrote: >> >> Agreed. Although I assume you mean invoke the new pass under a >> ThinLTO-only option so that avail extern are not dropped in the >> compile pass before the LTO link? > > > No, this pass