similar to: big edge list to adjacency matrix

All, If we can speculatively execute a load instruction, why isn’t it safe to hoist it out by promoting it to a scalar in LICM pass? There is a comment in LICM pass that if a load/store is conditional then it is not safe because it would break the LLVM concurrency model (See commit 73bfa4a). It has an IR test for checking this in test/Transforms/LICM/scalar-promote-memmodel.ll However, I have

I think gcc is right. It inserted a branch for n == 0 (the cbz at the top), so that's not a problem. In all other regards, this is safe: if you examine the sequence of loads and stores, it eliminated all but the first load and all but the last store. How's that unsafe? If I had to guess, the bug here is that LLVM doesn't want to hoist the load over the condition (which it is right

Thanks for the background on the concurrent memory model. So, is it sufficient that the loop entry is guarded by condition (cbz at top) for preventing the race? The loop entry will be guarded by condition if loop has been rotated by loop rotate pass. Since LICM runs after loop rotate, we can use ScalarEvolution::isLoopEntryGuardedByCond to check if we can speculatively execute load without

I have a data frame something like: name wrist nLevel emot 1 4094 3.34 1 frustrated 2 4094 3.94 1 frustrated 3 4094 NA 1 frustrated 4 4094 3.51

Airon, I don't think you have to find an English computer 'cause the following must work in your Chinese one :-) Let me explain. First of all, change your lines to xdata <- ckhdat$Adj..Close[1:1447] #names(ckhdwt.la8) <- c("w1", "w2", "w3", "w4", "w5","w6", "v6") note the # sign, i.e., DO NOT change the names

Dear R users, I have some environmental variables and I need to find the best combination of them in order to separate two main groups (coded 1 and 2). I have performed a discriminant analysis using the stepclass function as a method for selecting the most relevant environmental variables. The problem is that this function includes a parameter (start.vars) and my results change a lot when I

Hello, I have a question about margins when plotting an unrooted tree (type="unrooted") with the 'ape' package ver. 1.7. When I plot an unrooted tree with: no.margin=TRUE it seems that the margins are still there. It appears to be only when type="unrooted". I'm plotting multiple plots using layout() and would like to be able to get rid of the margins or if

Dear all, I need to compute the ACF (autocorrel) of an AR6 process, given the values of its parameters (w1,w2,w3,w4,w5,w6). First, I notice that there is an error as soon as the sum of the wi equals 1 : "Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number = 1.00757e-18"

Dear R helpers I have following data stocks <- c("ABC", "DEF", "GHI", "JKL") prices_df <- data.frame(ABC = c(17,24,15,22,16,22,17,22,15,19),                                          DEF = c(22,28,20,20,28,26,29,18,24,21),                                           GHI = c(32,27,32,36,37,37,34,23,25,32),                                          

Dear R-helpers, I am struggling with an optimization problem at the moment and decided to write the list looking for some help. I will use a very small example to explain what I would like to. Thanks in advance for your help. We would like to distribute resources from 4 warehouses to 3 destinations. The costs associated are as follows: Destination >From 1 2 3 Total

Dear All, First of all, this is the first time for me to use R for optimization, I tried to search r-help postings & googled on weighted sum optimization, I could not find anything applicable. I would need to optimize following function in R; MAXIMIZE function = w1*R1 + w2*R2 + w3*R3 + w4*R4 Where constraints are, w1 + w2 + w3 + w4 = 1 and 0 <= w1, w2, w3, w4 <= 1 Does optim

Hi All, I've encountered an issue where tail merging MIs is causing a problem with the post-RA MI scheduler dependency analysis and I'm not sure of the best way to address the problem. In my case, the branch folding pass (lib/CodeGen/BranchFolding.cpp) is merging common code from BB#14 and BB#15 into BB#16. It's clear that there are 4 common instructions (marked with an *) in BB#14

I have a really simple question I have a data frame of 8 variables (the first column is the subjects' id): SubID G1 G2 G3 G4 W1 W2 W3 W4 1 6 5 6 2 6 2 2 4 2 6 4 7 2 6 6 2 3 3 5 5 5 5 5 5 4 5

Dear R-users, I'm running a maximization problem in which I want to impose a condition on the relationship between 2 parameters. The condition is that w[4] = (1+eps)/(2*w[1]), or equivalently w[4]*w[1] = (1+eps)/2 , where eps is some small positive constant. I've been trying to formulate a function that takes care of this, but I can't really make it work so any suggestions would be

Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N

Hi, Jiong, Thanks for the patch! It is a great start to support 32bit register in BPF. In the past, I have studied a little bit to see whether 32bit register support may reduce the number of unnecessary shifts on x86_64 and improve the performance. Looking through a few bpf programs and it looks like the opportunity is not great, but still nice to have if we have this capability. As you

Andreas, On Thu, Aug 24, 2017 at 03:37:07PM +0200, awl1 via samba wrote: > Before I follow your advice to move this whole issue/topic to the > samba-technical alias and start over there with a clean description of the > scenario and the findings, I have two simple questions: > > 1) I plan to use a new, reproducible test scenario with 2000 random small > files with a file length

I have a set of data for US t-bill returns and US stock returns frm 1980-2012. I am trying to bootstrap the data and obtain the minimum variance portfolio and repeat this portfolio 1000 times. However I am unable to get the correct code function for the minimum variance portfolio. When I tried to enter Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please help!

Airon, I used R2.4.0 on a Windows XP (SP2) (not Chinese :-)) and it still works: > data = read.csv("u:/airon.csv") > xdata = data$Adj..Close > modwt.la8 = modwt(xdata, "la8", n.level=6) > summary(modwt.la8) Length Class Mode d1 1467 -none- numeric d2 1467 -none- numeric d3 1467 -none- numeric d4 1467 -none- numeric d5 1467 -none- numeric d6 1467

Dear list, Does anyone have a suggestion (or better still) code for sampling from the uniform distribution over the convex hull of a set of points? Many thanks and best wishes, Ranjan