similar to: [LLVMdev] LLVM Execution engine: Native call vs LLVM IR function call

Hi Óscar, Thank you for your response. I did not explicitly optimize the IR. I compile and run the two versions with ... GenericValue gv = EE->runFunction(bsqr, args); ... GenericValue gv2 = EE->runFunction(cppnat, args); I am calling method runFunction of ExecutionEngine. I am using the default code gen optimization level. Best regards, Nurudeen. On Thu, March 28, 2013 7:05 am, Óscar

nlamee at cs.mcgill.ca writes: > I would like to understand why calling a native function from a function > in LLVM IR can be much faster than calling an equivalent function in LLVM > IR. Do you optimize the LLVM IR? The IR version can inline the call and just that would make it faster than the "native" version. Please describe how do you compile your LLVM IR. Once knowing

Hi, How can I dynamically change the code generation optimization level (e.g., None) of a JIT in other to recompile a function with a new optimization level (e.g., Default)? Thank you. Best regards, Nurudeen.

I would like to replace a few varaibles within a data frame. For example, in the dataframe below (contrived) I would like to replace the current housesize value only if the Location is HSV. However, I would like to leave the other values intact. I tried "ifelse", but I don't really need the else condition. test_data2_df<-data.frame(Variables=c("SQR

Hello list, I just started R today and tried something quite simple. I wanted to create a colored plot and eventually after hours of fiddling around got it working. However, my solution seems very suboptimal and I'd really appreciate your hints on how to improve. I believe that R already offers many functions I coded (e.g. distance between two vectors, vector length, vector normalization and

Dear R developers! Considering I got no response or comments in the general r-help forum so far, perhaps my question is actually better suited for this list? I have added some more hopefully relevant technical details to my original post (edited below). Any comments gratefully received! Best regards, David Kreil. ---------- Dear R experts, I have a problem that is a related to the question

Hi Larry, Thanks so much! This seems to do the trick. I would have spun my wheels for > a long time before discovering all of this, wow. No worries. :) I'll try to keep this in mind and make sure I address it in future Kaleidoscope tutorial chapters - these issues tripped me up the first time I encountered them too. Do I even want to know what additional chickens need to be sacrificed

Good morning, I am investigating dll import in R under Windows XP. Using examples I found on the internet, I started with a very simple dll, e.g. including only the basic function: void { *x2 = x*x; }sqr(doublex, double*x2) I compiled it as a dll with Eclipse and Cygwin's gcc. It works when I call it with another simple .exe C program, compile with Eclipse and gcc as well. I can do what I

>> llvm::sys::DynamicLibrary::LoadLibraryPermanently(nullptr) This is one is a bit tricky and hard to find. I spent quiet some time digging into MC and ORC JIT execution engines trying to find what makes them work. The problem is that this trick (LoadLibraryPermanently) happens inside of EngineBuilder, despite that the functionality belongs to a JIT engine itself, not to the builder. I

Following a discussion about numerical performance on comp.lang.functional recently I just tried running a simple C mandelbrot benchmark that uses C99's complex arithmetic using gcc and llvm-gcc on a 2.1GHz Opteron 2352 running Debian: gcc: 5.727s llvm-gcc: 1.393s There is still 20% room for improvement but LLVM is >4x faster than gcc here. Sweet. Here's the code: #include

Thanks so much! This seems to do the trick. I would have spun my wheels for a long time before discovering all of this, wow. Do I even want to know what additional chickens need to be sacrificed to get this to work on Windows? -- lg > On May 18, 2016, at 1:52 PM, Lang Hames <lhames at gmail.com> wrote: > > Hi Larry, > > You're basically there, but you're hitting

I was having some problems persuading optim() to give me the answers I wanted, & simplified down to: sqr<-function(x){(x+1)^2} optim(1,sqr) I accept this is a hammer to crack a nut, but was still expecting the answer -1. I got: $par [1] -0.8 $value [1] 0.04 $counts function gradient 12 NA $convergence [1] 0 $message NULL so I've

On gcc's side, this is a simple missed opt on the part of builtin lowering. As a result, the gcc code ends up with a call to muldc3 (complex = 2x2 multiply double) and the llvm code doesn't. GCC should be fixed in a second, and with that, there is no appreciable performance difference between the two. On Thu, Feb 26, 2009 at 4:07 PM, Jon Harrop <jon at ffconsultancy.com> wrote: >

When using ORC JIT, I'm having trouble with external function resolution (that is, of a function defined in the app, with C linkage). I add a declaration for the function to my IR, and when I use MCJIT, it finds it and all is well, But when I use ORC JIT (I *think* correctly, at least it closely matches what I see in the tutorial), I get an LLVM error, "Program used external function

I noticed a problem using R 2.7.1 on Windows XP SP2 with the precompiled Atlas Rblas.dll. Running the code below causes R to crash. I started R using Rgui --vanilla and am using the precompiled Atlas Rblas.dll from cran.fhcrc.org dated 17-Jul-2007 05:04 for Core2 Duo. The code that causes the crash: x <- rnorm(100) y <- rnorm(100) z <- rnorm(100) loess(z ~ x * y) loess(z ~ x) does

Dear R experts, I really have difficulty when I try to deal with this question. suppose X is a square symmetric matrix. The exponent of X is defined by the matrix limit as following: exp(X) = lim (I + X/n)^n, note: the limit is from n to infinite. How can I write R function for the above? Thank you very much -- View this message in context:

Sirs, I have recently been interested in your Maxstat. I have computed with my own programme the ranks (by using the Kaplan-Meier method and the log-rank test) with the formula (Observed-Expected)/(SQR Var). The results are similar but not exact to the M value obtained with the Maxstat. I would like to know whether you are using some correction or adjustment in computing the different ranks. Thank

Hi list, I am just wondering if anyone knows a way to stream with automated crossfading under Linux. I know that you can stream to icecast from windows using something like otsjuke, or WinAmp with the SQR crossfading plugin, but am not aware of anything for Linux that will allow me to stream with gapless output. Any suggestions greatly appreciated as always.

While I don't know anything about Box's M test, I googled around and found a Matlab M-file that computes it. Below is my straight-forward translation of the code, without knowing Matlab or the formula (and done in a few minutes). I hope this demonstrates one of Prof. Ripley's point: If you really want to shoot yourself in the foot, you can probably program R to do that for you. [BTW:

Dear all I am a bit new to R so please keep your swords sheathed! I would simply like to bootstrap a covariance matrix from a multivariate gaussian density. At face value that seemed like a very straightforward problem to solve but I somehow could not get the boot package to work and did not really understand the documentation so I tried to do the bootstrap manually. Hence: x<-rmvnorm(n = 5,