similar to: [LLVMdev] clang: Manual unfolding doesn't match automatic unfolding

On Tue, Jul 26, 2011 at 11:35 AM, Taral <taralx at gmail.com> wrote: > > One piece of code I'm writing has a lot of intermediates, and I'm > trying to optimize down the number of memory accesses. Here's a > snippet from the start of the function, where I think there is some > low-hanging fruit: > > # BB#0: >        pushq   %rbp >        pushq   %r15

One piece of code I'm writing has a lot of intermediates, and I'm trying to optimize down the number of memory accesses. Here's a snippet from the start of the function, where I think there is some low-hanging fruit: # BB#0: pushq %rbp pushq %r15 pushq %r14 pushq %r13 pushq %r12 pushq %rbx movq %rdx, %rcx movq %rdi, -16(%rsp) # 8-byte Spill movq (%rsi), %rdi movq

I have the adjacency matrix of a graph. I'm trying to find all triangles (embeddings of C_3). This doesn't work: index = function(l) seq(l)[l] pairs = do.call(rbind, lapply(seq(nrow(adj)), function(x) cbind(x, index(adj[x,])))) triangles = do.call(rbind, apply(pairs, 1, function(x) cbind(x, index(adj[x[1],] & adj[x[2],])))) I'm absolutely certain I've gone down the wrong path

I'd like to convert a dist into a table/matrix/thingy of the form: A B value A C value B C value (assuming the dist was over 3 names). Is there a way to do this without using a for loop? -- Taral <taralx at gmail.com> "Please let me know if there's any further trouble I can give you." ? ? -- Unknown

Hey all, Does anyone know how we can get train set and test set for each fold of 5 fold cross validation in Caret package? Imagine if I want to do cross validation by random forest method, I do the following in Caret: set.seed(12) train_control <- trainControl(method="cv", number=5,savePredictions = TRUE) rfmodel <- train(Species~., data=iris, trControl=train_control,

Hello, I am looking for a loop unfolding procedure implemented in LLVM that helps to transform a while-loop to n-layer If-statements. The transformation should be on IR, although the example below is illustrated on the source level. original loop: * WHILE (condition) DO action ENDWHILE* Expected unfolded loop (2-layer): * IF (condition) THEN* * action* * IF

Hi, I'm using rsync for a couple of things but I am at a point where I could not find a solution for my problem. this is what I want to do: rsync only the files i_* from a directory from machine A to machine Bi and delete them from machine B if they on longer exist on machine A. so I use the command: rsync -azv --stats -e ssh --delete i_* user@host:/dir/ When using this command the files

I'm trying to put together an R routine to conduct unidimensional unfolding scaling analysis using maximum likelihood. My problem is that ML optimization will get stuck at latent scale points that are far from optimal. The point optimizes on one of the observed variables but not others and for ML to move away from this 'local optimum', it has to move in a direction in which the

Dear [R] people Could you please help with following data transformation. Any suggestions, hints, references and even guessing on performing any of the following steps are highly appreciated. Those transformations are crucial for my work. (n_, _n, j_, k_ signify numbers) SOURCE DATA: id cycle1 cycle2 cycle3 ? cycle_n 1 c c c c 1 m m m m 1 f f f f 2 m m m NA 2 f f f NA 2 c c c NA 3 a a

Alternatively, just type debug(optim) before using it, then step through it by hitting enter repeatedly... When you're done, do undebug(optim). Andy > From: Spencer Graves > > Have you looked at the code for "optim"? If you > execute "optim", it > will list the code. You can copy that into a script file and walk > through it line by line to

Hi all, I have a question regarding a transformation that is carried out in InstCombine, which has been introduced by r48715. It unfolds expressions of the form `zext(or(icmp, (icmp)))` to `or(zext(icmp), zext(icmp)))` to expose pairs of `zext(icmp)`. In a subsequent iteration these `zext(icmp)` pairs could then (possibly) be optimized by another optimization (which has already been there before

Hi Sanjay, > Am 02.08.2016 um 21:39 schrieb Sanjay Patel <spatel at rotateright.com>: > > Hi Matthias - > > Sorry for the delayed reply. I think you're on the right path with D22864. No problem, thank you for your answer! > If I'm understanding it correctly, my foo() example and zext_or_icmp_icmp() will be equivalent after your patch is added to InstCombine.

> Dave Yeo wrote: >> Yes that makes sense. Requiring a C99 compliant compiler seems quite reasonable. > Well I'm actually going to be even more reasonable than that. The only bits of C99 that flac will really require is header file > with C99 standard width integers (int8_t, uint8_t, int16_t etc). Erik I would recommend including with the distribution a file for windows

Dear R users, I have data on 4 types of interest rates. These rates evolve over time and across regions of countries . So for each type of interest rates I want to run a regression of rates on some other variables. So my regression for one type of interest rate will be I_{ij}_t= a +regressors +error term. where I_{ij}_t is the absolute difference in rates between two locations i and j at time

Hi Sanjay, thank you a lot for your answer. I understand that in your examples it is desirable that `foo` and `goo` are canonicalized to the same IR, i.e., something like `@goo`. However, I still have a few open questions, but please correct me in case I'm thinking in the wrong direction. > Am 21.07.2016 um 18:51 schrieb Sanjay Patel <spatel at rotateright.com>: > > I've

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On 09.02.2012 21:41, Ben Allison wrote: >>> Dave Yeo wrote: >>>> Yes that makes sense. Requiring a C99 compliant compiler >>>> seems quite >> reasonable. >>> Well I'm actually going to be even more reasonable than that. >>> The only >> bits of C99 that flac will really require is

Hello, I'm starting to write a C function that gets a list and a matrix from R. I'm using .Call because I've undertood that this is recommended to handle lists (am I wrong?). My problem is that I can pass the matrix as a vector, but not as a 2D array. For example, in the following simple C program: #include <R.h> #include <Rdefines.h> SEXP printListElement(SEXP list,

Hi all, I have tried a 5 fold cross validation using caret package with random forest method on iris dataset as example. Then I need ROC curve for each fold: > set.seed(1) > train_control <- trainControl(method="cv", number=5,savePredictions = TRUE,classProbs = TRUE) > output <- train(Species~., data=iris, trControl=train_control, method="rf") >

Given a field in database defined as "discount_rate numeric(3,1)" I found it not very usable for presenting it directly. For example, if there''s a value 5.00 it will render in <%= text_field ''model'', ''discount_rate %> as "0.5E1" which is not very friendly to user. All I do is that I write kind of proxy accessors (prefixing with

Hi, I would like to generate a correlation matrix with a particular structure. For example, a 3n x 3n matrix : A_(nxn) aI_(nxn) bI_(nxn) aI_(nxn) A_(nxn) cI_(nxn) aI_(nxn) cI_(nxn) A_(nxn) where - A_(nxn) is a *specified* symmetric, positive definite nxn matrix. - I_(nxn) is an identity matrix of order n - a, b, c are (any) real numbers Many attempts have been unsuccessful because a