similar to: sum(..., na.rm=FALSE): Summing over NA_real_ values much more expensive than non-NAs for na.rm=FALSE? Hmm...

This is a great example how you cannot figure it out after spending two hours troubleshooting, but a few minutes after you post to R-devel, it's just jumps to you (is there a word for this other than "impatient"?); Let me answer my own question. The discrepancy between my sum2() code and the internal code for base::sum() is that the latter uses LDOUBLE = long double (on some system

Looking for more ways to speed up R, I've found that large improvements are possible in the speed of "sum" and "prod" for long real vectors. Here is a little test with R version 2.11.1 on an Intel Linux system > a <- seq(0,1,length=1000) > system.time({for (i in 1:1000000) b <- sum(a)}) user system elapsed 4.800 0.010 4.817 > system.time({for (i

Greetings. For R gurus this may be a no brainer, but I could not find pointers to efficient computation of this beast in past help files. Background - I wish to implement a Cramer-von Mises type test statistic which involves double sums of max(X_i,Y_j) where X and Y are vectors of differing length. I am currently using ifelse pointwise in a vector, but have a nagging suspicion that there is a

The attached patch eliminates some warnings while compiling for ARM4 targets. It also simplifies the asm constraints a bit. Now we can use the ARM4 optimisations when compiling for PortalPlayer targets in Rockbox. Cheers, Dan -------------- next part -------------- A non-text attachment was scrubbed... Name: speex_arm4.patch Type: text/x-diff Size: 1550 bytes Desc: not available Url :

Hello! # I have 3 vectors of values: values1<-rnorm(10) values2<-rnorm(10) values3<-rnorm(10) # In real life, all 3 vectors have a length of 25 # I create all possible combinations of 4 based on 10 elements: mycombos<-expand.grid(1:10,1:10,1:10,1:10) dim(mycombos) # Removing rows that contain pairs of identical values in any 2 of these columns: mycombos<-mycombos[!(mycombos$Var1

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

The attached patch cleans up Opus's x86 intrinsics configury. It: * Makes ?enable-intrinsics work with clang and other non-GCC compilers * Enables RTCD for the floating-point-mode SSE code in Celt. * Disables use of RTCD in cases where the compiler targets an instruction set by default. * Enables the SSE4.1 Silk optimizations that apply to the common parts of Silk when Opus is built in

Hi, I run this code to get the power of the test for modified bartlett's test..but I'm not really sure that my coding is right.. #normal distribution unequal variance asim<-5000 pv<-rep(NA,asim) for(i in 1:asim) {print(i) set.seed(i) n1<-20 n2<-20 n3<-20 mu<-0 sd1<-sqrt(25) sd2<-sqrt(50) sd3<-sqrt(100) g1<-rnorm(n1,mu,sd1) g2<-rnorm(n2,mu,sd2)

From: Jonathan Lennox <jonathan at vidyo.com> * Makes ?enable-intrinsics work with clang and other non-GCC compilers * Enables RTCD for the floating-point-mode SSE code in Celt. * Disables use of RTCD in cases where the compiler targets an instruction set by default. * Enables the SSE4.1 Silk optimizations that apply to the common parts of Silk when Opus is built in floating-point mode, not

From: Jonathan Lennox <jonathan at vidyo.com> * Makes ?enable-intrinsics work with clang and other non-GCC compilers * Enables RTCD for the floating-point-mode SSE code in Celt. * Disables use of RTCD in cases where the compiler targets an instruction set by default. * Enables the SSE4.1 Silk optimizations that apply to the common parts of Silk when Opus is built in floating-point mode, not

I've continued to work on speeding up R, and now have a collection of fourteen patches, some of which speed up particular functions, and some of which reduce general interpretive overhead. The total speed improvement from these patches is substantial. It varies a lot from one R program to the next, of course, and probably from one machine to the next, but speedups of 25% can be expected in

On 01/08/14 19:37, Reid Kleckner wrote: > What happens if you drop appending linkage? I think it will just work, > since you are already using a custom section, which will ensure that all > the data appears contiguously in memory. Thanks for the suggestion, but it still puts everything in a single .section statement. > Although, I do worry about what LLVM's alias analysis will

Hi All, Since I continue to base my work on top of Jonathan's patch, and my previous Ne10 fft/ifft/mdct_forward/backward patches, I thought it would be better to just post all new patches as a patch series. Please let me know if anyone disagrees with this approach. You can see wip branch of all latest patches at https://git.linaro.org/people/viswanath.puttagunta/opus.git Branch:

Hi Timothy, As I mentioned earlier [1], I now fixed compile issues with fixed point and resubmitting the patch. I also have new patch that does intrinsics optimizations for celt_pitch_xcorr targetting aarch64. You can find my latest work-in-progress branch at [2] For reference, you can use the Ne10 pre-built libraries at [3] Note that I am working with Phil at ARM to get my patch at [4]

Hi, The function cummax() seems to have a bug. > x <- c(NA, 0) > storage.mode(x) <- "integer" > cummax(x) [1] NA 0 The correct result of this case should be NA NA. The mistake in [ https://github.com/wch/r-source/blob/trunk/src/main/cum.c#L130-L136] may be the reason. Best Regards, Dongcan -- Dongcan Jiang Team of Search Engine & Web Mining School of Electronic

Hi All, As per Timothy's suggestion, disabling mdct_forward for fixed point. Only effects armv7,armv8: Extend fixed fft NE10 optimizations to mdct Rest of patches are same as in [1] For reference, latest wip code for opus is at [2] Still working with NE10 team at ARM to get corner cases of mdct_forward. Will update with another patch when issue in NE10 gets fixed. Regards, Vish [1]:

Hi All, Changes from RFC v2 [1] armv7,armv8: Extend fixed fft NE10 optimizations to mdct - Overflow issue fixed by Phil at ARM. Ne10 wip at [2]. Should be upstream soon. - So, re-enabled using fixed fft for mdct_forward which was disabled in RFCv2 armv7,armv8: Optimize fixed point fft using NE10 library - Thanks to Jonathan Lennox, fixed some build fixes on iOS and some copy-paste errors Rest

Hello Timothy / Jean-Marc / opus-dev, This patch series is follow up on work I posted on [1]. In addition to what was posted on [1], this patch series mainly integrates Fixed point FFT implementations in NE10 library into opus. You can view my opus wip code at [2]. Note that while I found some issues both with the NE10 library(fixed fft) and with Linaro toolchain (armv8 intrinsics), the work

Full_Name: Nick Efthymiou Version: R1.5.0 and above OS: Red Hat Linux Submission from: (NULL) (162.93.14.73) With the introduction of the functions rowSums(), colSums(), rowMeans() and colMeans() in R1.5.0, function "SEXP do_colsum(SEXP call, SEXP op, SEXP args, SEXP rho)" was added to perform the fast summations. We have an excellent opportunity to improve the accuracy by

Dear R-Developers, I think I found two bugs in max.col(). Ties between zeros are not broken, which might affect simulations. -Inf and Zero can be treated the same, which can give completely wrong results, e.g. when the second max is sought by replacing all maxs by -Inf. To fix max.col I do offer the C-code behind my function rowMax(), which also handles NAs and seems to be faster. However,