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Actually what I meant in my original loop, that there is a dependency between every two consecutive iterations. So, how the loop vectorizer says 'we can vectorize this loop'? for(int k=20;k<50;k++) dataY[k] = dataY[k-1]; From: Henrique Santos [mailto:henrique.nazare.santos at gmail.com] Sent: Sunday, November 03, 2013 4:28 PM To: Sara Elshobaky Cc: <llvmdev at cs.uiuc.edu> Subject: Re: [LLVMdev] loop vectorizer issue Notice that the code you provided, for globals and stack allocat...

...ot on the C code but on LLVM IR this c code was lowered to. Before the loop vectorizer runs many other optimization change the shape of this IR. You can see in the LLVM IR you referenced below, a preceding LLVM IR transformation has change your loop from: > for(int k=20;k<50;k++) > dataY[k] = dataY[k-1]; to > int a = d[19]; > for(int k = 20; k < 50; k++) > dataY[k] = a; which is allowed because they are semantically equivalent and beneficial because we safe many loads. We can vectorize the latter loop. You can see in the debug output there is no load in the...

...ion X <- matrix(c(x0,x1,x2,x3,x4),ncol=5) Y <- matrix(y,ncol=1) Design.data <- cbind(X, Y) for (j in 1:nrow(X)) { result <- vector("list", ) for( i in 1: 3100) { data <- Design.data[sample(50,50,replace=TRUE),] ##### and unique(Design.data.....) dataX <- data[,1:5] dataY <- data[,6] B.cap.simulation <- solve(crossprod(dataX)) %*% crossprod(dataX, dataY) P.simulation <- dataX %*% solve(crossprod(dataX)) %*% t(dataX) Y.cap.simulation <- P.simulation %*% dataY e.simulation <- dataY - Y.cap.simulation dX.simulation <- nrow(dataX) - ncol(dataX) var.ca...

...=50,mean=2,sd=1) x4 <- rnorm(n=50,mean=2,sd=1) y <- 1+ 2*x1+4*x2+3*x3+2*x4+e x2[1] = 10 #influential observarion y[1] = 10 #influential observarion data.x <- matrix(c(x0,x1,x2,x3,x4),ncol=5) data.y <- matrix(y,ncol=1) data.k <- cbind(data.x,data.y) dataX <- data.k[,1:5] dataY <- data.k[,6] theta <- function(data) { B.cap <- solve(crossprod(dataX)) %*% crossprod(dataX,dataY) P <- dataX %*% solve(crossprod(dataX)) %*% t(dataX) Y.cap <- P %*% dataY e <- dataY - Y.cap dX <- nrow(dataX) - ncol(dataX) var.cap <- crossprod(e) / (dX) ei <- as.vector(...

Hello, I was trying to trace the Loop vectorizer of the LLVM, I wrote a simple loop with a clear dependency. But found that the debug shows that 'we can vectorize this loop' Here you are my loop with dependency: for(int k=20;k<50;k++) dataY[k] = dataY[k-1]; And the debug prints: LV: Checking a loop in "main" LV: Found a loop: for.body4 LV: Found an induction variable. LV: Found a write-only loop! LV: We can vectorize this loop! ... LV: Vectorization is possible but not beneficial. >From the LLVM IR, it cont...

Notice that the code you provided, for globals and stack allocations, at least, is semantically equivalent to: int a = d[19]; for(int k = 20; k < 50; k++) dataY[k] = a; Like so, the load you see missing was redundant, probably hoisted by GVN/PRE and replaced with "%.pre". H. On Sun, Nov 3, 2013 at 11:26 AM, Sara Elshobaky <sara.elshobaky at gmail.com>wrote: > Hello, > > I was trying to trace the Loop vectorizer of the LLVM,...

I am a beginner in R, so please don't step on me if this is too simple. I have two data sets datax and datay for which I created a qqplot qqplot(datax,datay) but now I want a line that indicates the perfect match so that I can see how much the plot diverts from the ideal. This ideal however is not normal, so I think qqnorm and qqline cannot be applied. Perhaps you can help? Ralf

Dear all, I am trying to my dataframe for the PLS analysis using the PLS package. However I have some trouble generating the correct dataframe. The main problem is how to use one name to represent several columns in the dataframe. The example dataframe in PLS package is called "sensory". I cannot directly read the data file since it's a binary file. If I use

Hi Everyone, When I have a load of functions which have various arguments passed via the ellipsis argument it keeps on assigning them as symbol making them unusable to the function. My current work around involves using do.call but this is rather cumbersome. Does anyone know why it suddenly changes the types to symbol and if there is a way to get the actual data pointed to by the symbol? (I