similar to: [LLVMdev] Graph Utilities

Hi, I am trying to use the new LLVM-2.7 release in Xcode for my analysis and development. However, I do not see the top level Xcode directory as in LLVM-2.6. Can someone tell me how to develop on top of LLVM-2.7 using Xcode? Best Regards, Raj

Rajkishore Barik <rb5 at rice.edu> writes: > I am trying to use the new LLVM-2.7 release in Xcode for my analysis > and development. > However, I do not see the top level Xcode directory as in LLVM-2.6. > Can someone tell me how > to develop on top of LLVM-2.7 using Xcode? Try using cmake: http://www.llvm.org/docs/CMake.html

Hi, I found out that Auto-Vectorization was implemented as a part of GSoC 2009. Can someone point me to the code repository including any documentation available? I would also like to know if there is any progress/future plans to include this in the main trunk? Best Regards, Raj

On May 5, 2010, at 1:01 PM, Rajkishore Barik wrote: > Hi, > > I found out that Auto-Vectorization was implemented as a part of GSoC > 2009. > Can someone point me to the code repository including any > documentation available? > I would also like to know if there is any progress/future plans to > include this > in the main trunk? Unfortunately, nothing came of

On 6 May 2010 05:34, Chris Lattner <clattner at apple.com> wrote: > On May 5, 2010, at 1:01 PM, Rajkishore Barik wrote: >> I would also like to know if there is any progress/future plans to >> include this >> in the main trunk? > > Unfortunately, nothing came of this project AFAIK, maybe Devang knows more. I looked for it and couldn't find any, too. I found

I am going to re-ask a question that has been asked a few times in the past. What is the best way to represent an undirected self-referential many to many relationship. Trivial examples of this include an edge in an undirected graph, or a mutual friendship. Alice is a person Bob is a person Alice and Bob are friends of each other We have a whole bunch of extra information about their friendship

In trying to set up a LLVM development environment, CMake seemed "too easy" - cmake <srctree>. No configuration options necessary whatsoever. But it worked, at least for Xcode on MacOS and for Visual Studio on Windows. Builds were successful. I have not tried running any of the output yet, though, since I don't yet have a front-end set up. Yet in discussion here, a lot of

Hello R experts, I went through R mailing,Nabble R.I could not find solution.Can someone help me. I have undirected Graph. Here is an example of spreadsheet I have( Unique 3559 Nodes) snippet of 4 rows. Node1 Node2 Weights 1 2 5 2 3 30 2 4 30 1 4 5 3 4 30 1 3 2 I created a program reading the csv and created a Adjacency matrix.From the adjacency matrix I created graph.I am not sure the

Estimados, estoy ?jugando? con unos datos clínicos donde realizo un análisis de redes, utilicé igraph como nerwork, pero finalmente uso igraph (creo que tiene más opciónes). Son algo de 200 nodos y algo más de 2000 relaciones. Puedo graficarlos. Los datos están de la siguiente forma, por ejemplo, individuo, patología, (las dos primeras columnas son la relación), luego un fármaco, el grupo

Excerpts from Waiman Long's message of July 8, 2020 1:33 pm: > On 7/7/20 1:57 AM, Nicholas Piggin wrote: >> Yes, powerpc could certainly get more performance out of the slow >> paths, and then there are a few parameters to tune. >> >> We don't have a good alternate patching for function calls yet, but >> that would be something to do for native vs pv.

Excerpts from Waiman Long's message of July 8, 2020 1:33 pm: > On 7/7/20 1:57 AM, Nicholas Piggin wrote: >> Yes, powerpc could certainly get more performance out of the slow >> paths, and then there are a few parameters to tune. >> >> We don't have a good alternate patching for function calls yet, but >> that would be something to do for native vs pv.

Hello, I am working with graph and adjacency matrix, the package 'graph' seems to be appropriate for this. An example in the package > mat <- rbind(c(0, 0, 1, 1), + c(0, 0, 1, 1), + c(1, 1, 0, 1), + c(1, 1, 1, 0)) > rownames(mat) <- colnames(mat) <- letters[1:4] > graph1 <- new("graphAM", adjMat=mat) > graph1 A

Hi all, A while ago there was a discussion on changing the current "set of trees" representation of TBAA metadata to be more expressive, prompted by the need to support C structs. Dan Gohman also talked about the issue here: http://llvm.org/devmtg/2012-11/Gohman-AliasAnalysis.pdf. It was suggested that the trees be replaced by a type DAG then. While working on this compiler

Hello all, I'm having a spot of trouble. I have made a very nice distance matrix from some comparison calculations. However, the matrix is 3096 x 3096, so it's relatively large. Currently I'm using the svn package as it seems to work for my data. The graph package errors and says the "adjacency matrix must be symmetric for undirected graphs". I though 3096 x 3096 was

On Mon, Jun 12, 2017 at 11:24 PM, Tobias Grosser via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Hi Jakub, > > thanks for the update. I was already eagerly waiting to hear what your > internship on dominance brings. I think the numbers are already very > encouraging and I believe moving incrementally over to the new algorithm > is exactly the right approach. > >

Hi all, I'm unable to compile R under an HPC system (which like many HPC systems doesn't always have the latest and greatest software). The version of GCC is 4.1.2 under CentOS 5.7. Running ./configure gives the following output: R is now configured for x86_64-unknown-linux-gnu Source directory: . Installation directory: /home/tbarik C compiler: gcc

Estimados Copio un mensaje de error que da igraph, es más fácil verlo que explicarlo. > fastgreedy.community(udatos) Error in .Call("R_igraph_community_fastgreedy", graph, as.logical(merges), : At fast_community.c:553 : fast-greedy community finding works only on graphs without multiple edges, Invalid value > cluster_louvain(udatos) IGRAPH clustering multi level, groups: 7,

I create an undirected graph with Rgraphviz (see code below). I would like to make the edges thicker. Can anyone help on this?? Regards S?ren V <- c("A","B","C","D") E <- list(c("A","B"),c("B","C"),c("C","D"),c("D","A"),c("A","C")) Eidx

Hi all, I'm having issues coding a random walk on a fully connected, undirected graph G with probability transition matrix P = (p_ij). Here is what I have so far ... for(i in 1:n){ for(m in 1:M){ x <- as.vector(matrix(rep(0,N+1),nc=N+1)) x[1] <- i for(k in 2:N+1){ y <- as.vector(matrix(rep(0,n),nc=n)) r <- runif(1) c <- c(0,cumsum(P[x[k-1],])) for(j in

Hi friends, Is there anyone who happened to import data set in the "DL" format into R for further analysis? In the package of "network", there's only a method named "read.paj()". So now, I have to get the dl file from the original data set, and use UCINET to convert it to .net file. It's too complicated. :( In the package of "igraph", edgelist is