similar to: [LLVMdev] Question about SSA-transformation

Dear LLVM'ers, in my register allocator, sometimes I have to spill virtuals that represent the same variable before SSA conversion. I would like to assign the same stack slot to these virtuals. Is there a way to recover this information from one of LLVM data structures? In other words, is it possible to discover which virtuals represent the same variable before SSA conversion by reading

Hello, I'm new in R and I want to do one thing that is very easy in excel, however, I cant do it in R. Suppose we have the data frame: data<- data.frame(A=c("a1","a2","a3","a4","a5")) I need to obtain another column in the same data frame (lets say B=c(b1,b2,b3,b4,b5) in the following way: b1=a1/(a1+a2+a3+a4+a5)

On Mon, 15 Dec 2003, jw schultz <jw@pegasys.ws> wrote: > OK, first pass on TODO complete. .... This hardlink bug report is nearly 21 months old... So I took a look at it using 2.5.7. See below. > BUGS --------------------------------------------------------------- > > Fix hardlink reporting 2002/03/25 > (was: There seems

Dear All, Here is a hypothetical sample (sorry for the clumsy code): A1 <- matrix(1:5, nrow=5, ncol=1) A2 <- matrix(6:10, nrow=5, ncol=1) A3 <- matrix(11:15, nrow=5, ncol=1) A4 <- matrix(16:20, nrow=5, ncol=1) A5 <- matrix(21:25, nrow=5, ncol=1) A6 <- matrix(26:30, nrow=5, ncol=1) B1 <- matrix(c(A1, A2, A3), nrow=5, ncol=3) B2 <- matrix(c(A2, A3, A4), nrow=5, ncol=3) B3

Hi Florian, we though about using UIUC, like in LLVM. Do you guys know if that could be a problem, given that we are mining the functions from github? > Have you thought about integrating the benchmarks as external tests into LLVM’s test-suite? That would make it very easy to play around with. We did not think about it actually. But we would be happy to do it, if the community accepts

Dear R users, Basically, from the following arbitrary data set: a <- data.frame(id=c(c("A1","A2","A3","A4","A5"),c("A3","A2","A3","A4","A5")),loc=c("B1","B2","B3","B4","B5"),clm=c(rep(("General"),6),rep("Life",4))) > a

Dear colleagues, I'd like to reshape a datafame in a long format to a wide format, but I do not quite get what I want. Here is an example of the data I've have (dat): sp <- c("a", "a", "a", "a", "b", "b", "b", "c", "d", "d", "d", "d") tr <- c("A",

Dear friends Hope you all are fine. Suppose we have a list of arrays. a1=c(4,4,4,4,0,4,4,4,0,3,3,0,0,0,0,0); a1=array(a1,dim=c(4,4)); a2=c(4,4,4,4,0,4,4,4,0,3,3,0,0,0,0,0); a2=array(a2,dim=c(4,4)); a3=c(4,4,4,4,0,3,3,4,0,4,4,0,0,0,0,0); a3=array(a3,dim=c(4,4)); a4=c(4,4,4,4,4,0,3,3,3,3,0,4,4,4,0,0,0,0,0,0); a4=array(a4,dim=c(5,4)); a5=c(4,4,4,4,4,0,4,4,4,4,0,3,3,3,0,0,1,1,0,0);

Hello I have a data set like below: plate.id well.id Group HYB rlt1 1 P1 A1 Control SKOV3hyb 0.190 2 P1 A2 Control SKOV3hyb 0.210 3 P1 A3 Control SKOV3hyb 0.205 4 P1 A4 Control SKOV3hyb 0.206 5 P1 A5 Control SKOV3hyb 0.184 385 P1 A1 ovca SKOV3hyb 0.184 386 P1 A2 ovca SKOV3hyb 0.229 387

We have a wireless network that uses 802.1x authentication, in which domain joined computers use their machine credentials to connect. Windows machines do this automatically, and until recently Linux computers could join using wicd, wpa-supplicant, and a simple script that would retrieve the machine password with tdbdump. ( specifically tdbdump -k SECRETS/MACHINE_PASSWORD/DOMAIN

Dear R friends, I know that this topic has been mulled over before, and that there is a substantial difference between the convergence criteria for JMP and those for R. I apologize that this is somwehat raking cold coals. Summary: A model/data combination achieves convergence in JMP, and survives a reasonably rigorous examination (sensible parameter estimates, well-behaved surface,

I would like to compare two data sets saved as text files (example below) to determine if both sets are identical(or if dat2 is missing information that is included in dat1) and if they are not identical list what information is different between the two sets(ie output "a1", "a3" as the differing information). The overall purpose would be to remove "a1" and

Dear LLVM'ers, I am browsing the instruction schedulers available in llc, and there are many: -pre-RA-sched = {default, none, simple, simple-noitin, list-burr, list-tdrr, list-td} I looked into the sources in lib/CodeGen/SelectionDAG, and I could find implementation of Sethi-Ullman numbering, list scheduling, etc. Now, I wish I could find some comparison between the

Hello, all, I want to implement the register allocation algorithm described in the paper "Register Allocation via Coloring of Chordal Graphs, APLAS'05" in LLVM. This is a graph coloring algorithm that can find an optimal coloring of the interference graph in most of the cases. I've downloaded LLVM last week, and started studying the code. Basically, I have to implement: 1) A

Hi, Nicolas, I have been talking to Andre about this project. Let me add my two cents: > I don't get it. What is the cons then of a simulation? The tradeoff, IMHO, is as follows: simulation: it does not add instructions to LLVM IR. Instead, it builds an interval representation for each variable. Each interval represents a variable in SSI form, and will be associated to one or

Hi, How do I rename the column labels in the table? For Instance, if I have a table like this, and I want to have the column labels changed from "A1 A2 A3 A4 A5" to "Mike Kate Michelle Paul Young" A1 A2 A3 A4 A5 1 33 44 55 66 77 2 3 4 5 6 7 7 8 9 and my text file location is: ""/Users/MAC/Desktop/data.txt" When I type in

Hello, I am using the mda package and in particular the fda routine to classify/predict in terms of color to a set of 20 samples for which i don?t know the color. I preformed a flexible discriminant analysis (FDA) using a set of 147 samples for which i know all the information. My script and data follow in attachment. A total of 23 predictors were considered. 20 of the predictors are

Estimados usuarios de R: Tengo dos data frames, A y B, donde hay algunas variables comunes y otras distintas. En el A tengo las variables, a1, a2, a3, a4, a5. En el B tengo las variables a1, a2, a3, b1, b2, b3,b4, b5, b6, b7. Los valores llave son a1 y a2, al data frame B quiero pegarle las variables a4 y a5 y en el caso no se tenga ningun valor en la variable a3, ponerle el valor que aparece

On May 19, 2009, at 8:15 PM, Nick Lewycky wrote: > Eli Friedman wrote: >> On Tue, May 19, 2009 at 12:30 PM, Nicolas Geoffray >> <nicolas.geoffray at lip6.fr> wrote: >>>> The pi functions can be implemented with copy instructions. >>> Store instructions? >> >> I would assume something more like "select i1 true, <ty> %val, <ty>

Dear Rxperts, is there way to identify intervals from continuous data (having some kind of a pattern) and then pick the value of most frequency? a1 <- round(rnorm(50,mean=0,0.1),2) a2 <- round(rnorm(50,mean=1,0.2),1) a3 <- round(rnorm(50,mean=5,1),0) a4 <- round(rnorm(50,mean=14,4),0) a5 <- round(rnorm(50,mean=30,8),0) b1 <- rbind(a1,a2,a3,a4,a5) hist(b1,brea=100) # shows