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Hello all! I'm working on a library with bignum support, and I wanted to try LLVM as an apparently simpler and more portable system to my current design (a Haskell script which spits out mixed C and assembly). Porting the script to use the LLVM bindings instead of the current hack was pretty easy. But I have a few remaining questions: (1) Are bignums exposed to any higher-level

...t fails at this statement ### lines(doR, col="blue") lines(doN, col="red") points(xx[i.out], rep(.01,10)) The following statement in density() was not getting the right output: y <- .C("massdist", x = as.double(x), nx = N, xlo = as.double(lo), xhi = as.double(up), y = double(2 * n), ny = as.integer(n), NAOK = has.na, PACKAGE = "base")$y y[1] and y[2] should be 0 and 0 but both of them became NaN after this statement. So I looked at src/appl/masdist.c with a debugger. The bug is caused by floor(). On Alpha/Linux, floot(...

If anyone has a very fast vectorized method for doing the following I would appreciate some help. I want to avoid outer() to limit memory problems for very large n. Let x = real vector of length n y = real vector of length n w = real vector of length m, m typically less than n/2 but can be > n z = real vector of length m For w[i], i=1,,,m, find the value of x that is closest to w[i]. In

Dear All, The institute I work for is organizing an internal workshop for High Performance Computing (HPC). I am planning to attend it and talk a bit about fluid dynamics, but there is also quite a lot of interest devoted to data post-processing and management of huge data sets. A lot of people are interested in image processing/pattern recognition and statistic applied to geography/ecology, but I

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