similar to: [LLVMdev] Assignment of large objects, optimization?

Hi Patrik, > My fronted generates (bad) code, which I see that LLVM is unable to optimize. > For example, code similar to: > %a = type [32 x i16] > declare void @set_obj(%a*) > declare void @use_obj(%a*) > define void @foo() { > entry: > %a1 = alloca %a > %a2 = alloca %a > call void @set_obj(%a* %a2) > %a3 = load %a* %a2 > store %a %a3, %a* %a1 > call void

I used llvm-stress to find a similar problem on x86-64. See http://llvm.org/bugs/show_bug.cgi?id=12821. BTW, llvm-stress is a great tool! /Patrik Hägglund ________________________________ From: llvmdev-bounces at cs.uiuc.edu [mailto:llvmdev-bounces at cs.uiuc.edu] On Behalf Of Jakob Stoklund Olesen Sent: den 9 maj 2012 18:21 To: Jonas Paulsson Cc: llvmdev at cs.uiuc.edu Subject: Re: [LLVMdev]

Hi, I am new to llvm with a particular interested in the optimization area, specially on SLP. While working through the tutorial, I ran this example [1] with the hope to see SLP vectorization in action but for some reason, I do not see it on the LLVM assembly as seen below. Is there anything I am missing? I am using Clearlinux as build machine and this has clang version 9.0.0.

On May 9, 2012, at 6:27 AM, Jonas Paulsson <jonas.paulsson at ericsson.com> wrote: > Hi, > > Recently code using IMPLICIT_DEF and INSERT_SUBREG started to break: > > %vreg9<def> = IMPLICIT_DEF > %vreg10<def> = INSERT_SUBREG %vreg9<kill>, %vreg1<kill>, hi > %vreg12<def> = sub %vreg10<kill>,

Hi, Recently code using IMPLICIT_DEF and INSERT_SUBREG started to break: %vreg9<def> = IMPLICIT_DEF %vreg10<def> = INSERT_SUBREG %vreg9<kill>, %vreg1<kill>, hi %vreg12<def> = sub %vreg10<kill>, %vreg11<kill> => %vreg10<def> = IMPLICIT_DEF %vreg10:hi<def> = COPY %vreg1<kill>

Hello. We're having issues running Samba 2.2.8-a1, on Solaris 8 (SPARC) under Veritas VCS 3.5 clustering (HA active-passive). Every time we have a cluster failover (we're testing), we have to re-join the domain [ADS not NT] (e.g., 'smbpasswd -j XYZ -r XYZPDC -UAdminRightsUser%password'). Otherwise, we cannot connect to the shares, and 'wbinfo -t' returns 'Secret is

Dear List, I neeed a grouped list with two sort of categorical data. I have a data .frame like this. year cat. b c 1 2006 a1 125 212 2 2006 a2 256 212 3 2005 a1 14 12 4 2004 a3 565 123 5 2004 a2 156 789 6 2005 a1 1 456 7 2003 a2 786 123 8 2003 a1 421 569 9 2002 a2 425 245 I need a list with the sum of b and c for every year and every cat (a1, a2 or a3) in this year. I had used the tapply

Hi all,I know this topic has came up multiple times, but I've never fully understand the apply() function. Anyway, I'm here asking for your help again to convert this loop to apply(). I have 2 data frames with the following information: a1 is the fragment that is need to be covered, a2 is the probes that cover the specific fragment. I need to count the number of probes cover every given

Hi R users, I am trying to omit rows of data based on partial matches an example of my data (seal_dist) is below: A quick break down of my coding and why I need to answer this - I am dealing with a colony of seals where for example A1 is a female with pup and A1.1 is that female's pup, the important part of the data here is DIST which tells the distance between one seal (ID) and another

Dear R-devels, We have encountered a problem concerning a dead lock in the dependency graph: We have two packages A1 and A2 where A2 extends A1. We have one package vignette for both packages, but which should be included into package A1. So in the "suggests" field of the DESCRIPTION file of A1 we suggest A2 to be able to produce the vignette at build/install time. On the other hand

Dear list, I'm trying to add a new dim to a multidimensional array. My array looks like this a1 <- array(1:8, c(2, 2, 2)) dimnames(a1) <- list(A = c("A1", "A2"), B = c("B1", "B2"), D = c("D1", "D2")) I would like to add a new dim 'group' with the value "low".

Hello. This is a follow-up to a question I posted last week. With some previous suggestions from the R-help community, I have been able to plot survival (, hazard, and density) curves using published data for Siler hazard parameters from a number of ethnographic populations. Can the function below be modified, perhaps with a "for" statement, so that multiple curves (different line

Hi, I have a three dimensional array, e.g., my.array = array(0, dim=c(2,3,4), dimnames=list( d1=c("A1","A2"), d2=c("B1","B2","B3"), d3=c("C1","C2","C3","C4")) ) what I would like to get is then a dataframe: d1 d2 d3 value A1 B1 C1 0 A2 B1 C1 0 . . . A2 B3 C4 0 I'm sure there is one function to do

Hello fellow R users, I have an issue that has me a little confused - sorry if the subject makes little sense, I wasn't sure how to refer to this problem. I have a data set I've extracted from ArcInfo (a section is shown below). It is spatial data, showing the distance from one ID to another. I want to get the actual 'TO' ID from the data set (there is no easy way to do this in

Hi folks, Suppose I create the character vector charvec by > charvec<-c("a1.b1","a2.b2") > charvec [1] "a1.b1" "a2.b2" and then I use strsplit on charvec as follows: > splitlist<-strsplit(charvec,split=".",fixed=TRUE) > splitlist [[1]] [1] "a1" "b1" [[2]] [1] "a2" "b2" I was wondering

Dear colleges, I do not understand the following behaviour: > aa <- data.frame(a1= 1:10, a2= c(rep(NA, 5), 1:5) ) > aa a1 a2 1 1 NA 2 2 NA 3 3 NA 4 4 NA 5 5 NA 6 6 1 7 7 2 8 8 3 9 9 4 10 10 5 > aa[!aa$a2==1, ] # removing rows with a2==1 a1 a2 NA NA NA NA.1 NA NA NA.2 NA NA NA.3 NA NA NA.4 NA NA 7 7 2 8 8 3 9 9 4 10 10 5 I didn't

I want to count attributes of IDs: --8<---------------cut here---------------start------------->8--- z <- data.frame(id=c(10,20,10,30,10,20), a1=c("a","b","a","c","b","b"), a2=c("x","y","x","z","z","y"),

Dear Wiz[R]ds, I am deeply grateful for the help from Duncan Murdoch, Gray Calhoun, and others. We are almost there. For whatever reason, I can't change the symbol from a circle to a triangle in the upright posture plots. Any ideas? I have included the problem in full. # tritiated (3H)-Norepinephrine(NE) disappearance from plasma # concentrations supine and upright # supine datasu <-

Dear Wiza[R]ds, # I have the following experimentally observed data: csdata <- data.frame( time=c(0,1,3,9,20), conc=c(638.697,395.69,199.00,141.58,112.16) ) # weighting resp means response wt.MM<- function(resp, time,A1,a1,A2,a2) { pred <- A1*exp(-a1*time)+A2*exp(-a2*time) (resp - pred) / sqrt(pred) } # Fit using nls cs.wt <- nls( ~ wt.MM(conc, time,A1,a1,A2,a2),

Hi, I have a a vector and a data frame with two columns vec = c("C", "A", "B") dataDF = data.frame(A1 = c("B", "A", "C"), A2 = c(1,2,3)) I would like to sort the data frame by column A1 such that the order of elements in A1 is as the same as in vec. After the ordering, the data frame would be A1 A2 C