similar to: [LLVMdev] Unrolling power sum calculations into constant time expressions

Hello, I've come across another example: I'm compiling with clang -S -emit-llvm -std=gnu99 -O3 clang version 2.9 (trunk 118238) Target: x86_64-unknown-linux-gnu Thread model: posix I take the code: int loops(int x) { int ret = 0; for(int i = 0; i < x; i++) { for(int j = 0; j < x; j++) { ret += 1; } } return ret; } and the

Hello, I've been redirected from cfe-dev, as code optimizations in clang are done in llvm layer. I'm investigating how optimized code clang generates, and have come across such an example: I have two procedures: void exec0(const int *X, const int *Y, int *res, const int N) { int t1[N],t2[N],t3[N],t4[N],t5[N],t6[N]; for(int i = 0; i < N; i++) { t1[i] = X[i]+Y[i];

The following series adds initial vector support for PowerPC64. On POWER9, flac --best is about 3.3x faster. Amitay Isaacs (2): Add m4 macro to check for C __attribute__ features Check if compiler supports target attribute on ppc64 Anton Blanchard (5): configure.ac: Remove SPE detection code configure.ac: Add VSX enable/disable configure.ac: Fix FLAC__CPU_PPC on little endian, and add

----- Original Message ----- > From: "Dibyendu Das" <Dibyendu.Das at amd.com> > To: "Hal Finkel" <hfinkel at anl.gov>, "Renato Golin" <renato.golin at linaro.org> > Cc: llvmdev at cs.uiuc.edu > Sent: Tuesday, November 4, 2014 12:15:12 PM > Subject: RE: [LLVMdev] supporting SAD in loop vectorizer > > Here's the simple SAD

----- Original Message ----- > From: "James Molloy" <james at jamesmolloy.co.uk> > To: "Hal Finkel" <hfinkel at anl.gov> > Cc: "Dibyendu Das" <Dibyendu.Das at amd.com>, llvmdev at cs.uiuc.edu > Sent: Tuesday, November 11, 2014 8:21:37 AM > Subject: Re: [LLVMdev] supporting SAD in loop vectorizer > > > If you'd like to

Hi! When I'm trying to run wine (I've tried many compilations), I got something like that: wineserver: /root/.wine/config is not a valid registry file Why I'm not using /etc/wine.conf, /usr/etc/wine.conf or /usr/local/etc/wine.conf? Because wineserver wants only $HOME/.wine/config... When I delete this file wineserver 'says' that I don't have configuration file (even

----- Original Message ----- > From: "Renato Golin" <renato.golin at linaro.org> > To: "Dibyendu Das" <Dibyendu.Das at amd.com> > Cc: llvmdev at cs.uiuc.edu > Sent: Tuesday, November 4, 2014 5:23:30 AM > Subject: Re: [LLVMdev] supporting SAD in loop vectorizer > > On 4 November 2014 11:06, Das, Dibyendu <Dibyendu.Das at amd.com> wrote:

Dear List: I am working to understand some differences between the results of the svymean() function in the survey package and from code I have written myself. The results from svymean() also agree with results I get from SAS proc surveymeans, so, this suggests I am misunderstanding something. I am never comfortable with "I did what the software" does mentality, so I am working to

I would like to code the following in R: a1(b1+b2+b3) + a2(b1+b3+b4) + a3(b1+b2+b4) + a4(b1+b2+b3) or in summation notation: sum_{i=1, j\neq i}^{4} a_i * b_i I realise this is the same as: sum_{i=1, j=1}^{4} a_i * b_i - sum_{i=j} a_i * b_i would appreciate some help. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/summation-coding-tp4646678.html Sent from the R

Hi Everybody I want to print a latex table containing math characters in the column heading These are the formulae I want to use as column headings. It prints OK from TeX $\sum_{i}\sum_{j}C_{P,i,j,y}\times\mathit{FC}_{i}$, $XU_{alt,y}$, $n$, $\bar{C}_{P,y}$ My plan was to create a character vector with these and later rbind the values to them. When I create the vector like:

Dear R Users, I have 12 data frames, each of 12 rows and 2 columns. e.g. FeketeJAN MEAN SUM_ AMAZON 144.4997874 68348.4 NILE 5.4701955 1394.9 CONGO 71.3670036 21196.0 MISSISSIPPI 18.9273250 6511.0 AMUR 1.8426874 466.2 PARANA 58.3835497 13486.6 YENISEI 1.4668313 592.6 OB 1.4239179 559.6 LENA 0.9342164

Dear R experts I need to write a function that incorporates double summation, the problem being that the upper limit of the second summation is the index of the first summation, i.e: sum_{j=0}^{x} sum_{i=0}^{j} choose(i+j, i) where x variable or constant, doesn't matter. The following code obviously doesn't work: f=function(x) {j=0:x; i=0:j; sum( choose(i+j,i) ) } Can you help? Thanks

I need to refresh my memory on Probability Theory, especially on conditional probability. In particular, I want to solve the following two problems. Can somebody point me some good books on Probability Theory? Thank you! 1. Z=X+Y, where X and Y are independent random variables and their distributions are known. Now, I want to compute E(X | Z = z). 2.Suppose that I have $I \times J$ random number

Hi all, I have a problem using rdirichlet{gtools}. For Dir( a1, a2, ..., a_n), its mode can be found at $( a_i -1)/ ( \sum_{i}a_i - n)$; The means are $a_i / (\sum_{i} a_i ) $; I tried to study the above properties using rdirichlet from gtools. The code are: ############## library(gtools) alpha = c(1,3,9) #totoal=13 mean.expect = c(1/13, 3/13, 9/13) mode.expect = c(0, 2/10, 8/10) #

Hello, I am looking into description of surf.ls(spatial) and see under value $beta - the coefficients. When I use polynomial of degree 2 to fit surface I expect to get 4 coefficients: z = a_1 x^2 + a_2 xy + a_3 y^2 + a_4 What do beta really stand for and why do I get $beta vector of length 6? Thakns, Mark

Hi, If I do a standard svm regression with e1071 x <- seq(0.1, 5, by = 0.05) y <- log(x) + rnorm(x, sd = 0.2) m <- svm(x, y) we can do predict(m,x) to get the fitted values. But what if I wan tho get them by hand? Seem to me like it should be w = t(m$coefs)%*%m$SV x.scaled = scale(x, m$x.scale[[1]], m$x.scale[[2]]) t(w %*% t(as.matrix(x.scaled))) - m$rho but this is wrong If i

Dear helpers in this forum, This is a clarified version of my previous questions in this forum. I really need your generous help on this issue. > Suppose I have the following data set: > > id x y > 023 1 2 > 023 2 5 > 023 4 6 > 023 5 7 > 412 2 5 > 412 3 4 > 412 4 6 > 412 7 9 > 220 5 7 > 220 4 8 > 220 9 8 > ...... > Now I want to compute the

Dear helpers in this forum, I have the following question: Suppose I have the following data set: id x y 023 1 2 023 2 5 023 4 6 023 5 7 412 2 5 412 3 4 412 4 6 412 7 9 220 5 7 220 4 8 220 9 8 ...... and i want to calculate sum_{i=1}^k sum_{j=1}^{n_i}x_{ij}*y_{ij} is there a simple way to do this within and between subject summation in R?

Hi, I'm bit confused about ecdf (read the help files but still not sure about this). I have an analytical expression for the pdf, but want to get the empirical cdf. How do I use this analytical expression with ecdf? If this helps make it concrete, the pdf is: f(u) = \sum_{t = 1}^T 1/n_t \sum_{i = 1}^{n_t} 1/w K((u - u_{it})/w) where K = kernel density estimator, w = weights, and u_{it} =

I wrote some functions for multiway CANDECOMP, i.e. for least squares fitting of a_{i_1\cdots i_m}\approx\sum_{s=1}^p x^1_{i_1s}x^1_{i_1s}\cdots x^m_{i_ms} with arrays of arbitrary dimension. Reminded me of the good old APL days. I could not find this in the archives, but if it's already there, I would appreciate if someone let me know.