search for: straightfoward

Hello! I am trying to write a function with vector and data.frame parameters that uses the sum() function and values from the rows of the data.frame. I need to pass this function as a parameter to optim(). My starting point is: observs <- data.frame(y, x1, x2, x3) Fn <- function(par, observs) { sum( (y - (par[1] * (x1 + 1) * x2^(-par[2]) * x3^par[3])^2 ) }

...atures around. > > > > > > > > > > I have already done that in last Nov. I made a very rough (yet hacky) > > > version (only with Tx path) in one day while companying my wife in > > > hospital. > > > > Any performance data? > > A straightfoward implementation only brings 10% performance boost in a > txonly micro benchmarking. But I'm sure there are still plenty of room > for improvement. > > > > If someone are interested in, I could share the code soon. I could > > > even cleanup the code a bit if necessary...

...atures around. > > > > > > > > > > I have already done that in last Nov. I made a very rough (yet hacky) > > > version (only with Tx path) in one day while companying my wife in > > > hospital. > > > > Any performance data? > > A straightfoward implementation only brings 10% performance boost in a > txonly micro benchmarking. But I'm sure there are still plenty of room > for improvement. > > > > If someone are interested in, I could share the code soon. I could > > > even cleanup the code a bit if necessary...

Hopefully this is straightfoward. I have an matrix which is mostly zeroes. I want to assign it some non-zero elements whose rows, columns, and values I know. As a simple example, say I create a 3x2 matrix of zeros: > m <- matrix(rep(0,6),nrow=3) Now say I want to make the [1,1] and [3,2] elements of this matrix be non-ze...

...he usual case, the JITEmitter calls into JIT and updates its own data structures, so that case works fine. I think adding a smarter allocateSpace to JITEmitter is the right general idea, and your patch looks OK. I'd like to get another pair of eyes on it though, as I find this area not straightfoward:) Please run the testsuite before committing. Thanks for analyzing this and the test case. > The problem only happens when calling > ExecutionEngine::getPointerToGlobal(someGV) from some non-llvm > program. If > the function is called when JITing a function, it works, since it...

Hello, this set of patches adds SystemZ support to base LLVM. This is split up into three patches just to simplify review; they should be committed as a single change if approved. The first patch adds SystemZ support to the configure logic and support for the systemz Triple. This ought to be straightfoward. The second patch adds changes to LLVM common code required to support the SystemZ ELF object format, including relocation types and processing and the runtime loader. There is one change to common code that it not solely SystemZ related: the patch adds a new routine "getStubAlignment",...

...s fine. exactly! :) Thank you for summarizing. I hope others can now follow this description. > I think adding a smarter allocateSpace to JITEmitter is the right > general idea, and your patch looks OK. I'd like to get another pair > of eyes on it though, as I find this area not straightfoward:) Please > run the testsuite before committing. Yes, I would also appreciate more reviewers. The JIT's code is particularly complex and I'm also quite new to the LLVM code.. Thanks, Nuno

Dear R-Help, My problem/bug came to light,when fitting a linear model using stepwise selection. I'd started with the straightfoward command step(lm(y~., dataset)) This worked fine, but because this starts with all the possible explanatory variables, it results in a model with too many explanatory variables. Hence I wanted to start with just a constant and do forward selection, to get a new starting model for full stepwise se...

...y. This will require an initial pass to be performed (called IRFinalize?), and equality of Type objects by pointer comparison will not be valid until after this pass is complete. The Module is already the unit of compilation once LLVM IR has been initially emitted for most cases, and it should be straightfoward to structure the pass such that it can work on single functions if the user is compiling at that level. The IRFinalize pass can allocate the bookkeeping storage for identifying duplicate Constants and Types and then release it so long as none of the optimization and analysis passes 1) Emit new Typ...

...o this 'undle-gcc-4.02' problem? By the way, the package contains one C source file only but the installation seems quite complicated. I understand it uses 'standard' procedures--- configure, etc.---but wouldn't a simple Makefile be much easier to cope with? I would be pretty straightfoward what variables and paths to change, etc. By the way again, any comments on ncdf vs RNetCDF? I just couldn't like the inconsistent naming in ncdf (put.var.ncdf, att.put.ncdf, dim.get.ncdf, get.var.ncdf, ...), otherwise its very recent update would have attracted me to it. Anyway these are no...

On Tue, Feb 28, 2017 at 12:29:43PM +0800, Yuanhan Liu wrote: > Hi Michael, > > Again, as usual, sorry for being late :/ > > On Wed, Feb 22, 2017 at 06:27:11AM +0200, Michael S. Tsirkin wrote: > > Stage 2: prototype guest/host drivers > > > > At this stage we need real guest and host drivers > > to be able to test real life performance. > > I suggest

On Tue, Feb 28, 2017 at 12:29:43PM +0800, Yuanhan Liu wrote: > Hi Michael, > > Again, as usual, sorry for being late :/ > > On Wed, Feb 22, 2017 at 06:27:11AM +0200, Michael S. Tsirkin wrote: > > Stage 2: prototype guest/host drivers > > > > At this stage we need real guest and host drivers > > to be able to test real life performance. > > I suggest

>> Today I found a nice bug in the JIT global variable emitter. >> The problem may lead to an assert() failure when doing the following: >> 1) compile some function >> 2) emit a global variable >> 3) compile another function. an assert() may trigger in the JIT memory >> manager >> >> This happens because the JIT global variable emitter is using the

Dear All, I am trying to generate some Pareto random variates using the inverse method. This is really straightfoward and my R function looks as below : pareto <- function(c, a, cnt=1000) { u <- runif(cnt) x <- (c / ((u ^ (1 / a)))) mean.theo <- ((c * a) / (a - 1)) mean.gen <- mean(x) cat('Pareto mean : theoritical', mean.theo, 'generated', mean.gen, '\n') retur...

...tied to the TableGen instruction descriptions. The new model lets you define the structure of the subtarget scheduling description, so it can be self-documenting. The new model lets you use a plethora of tablegen tricks to handle all the variations on vector operations. I believe it's much more straightfoward to specify special constraints, like bypassing. It's fairly easy to extend certain opcodes with predicates (callbacks) that depend on immediate values or any other arbtrary info. See Javed and Florian's tutorial on the "new" machine model: https://www.youtube.com/watch?v=brpomKUy...

...u tried it, did it not work? If it didn't work, what error did you get? > i have another question, i want know how can estimate execution time > for each operand such as mul ,add, ... ? I don't know of an analysis that does this within LLVM. I would think that this is less-than-straightfoward due to instruction folding (e.g., merging a GEP and a load into a single x86 indexed mov instruction) and other machine-code specific optimizations. That said, if you just need to have relative differences in execution, you could probably write a very simple analysis that generates a rough est...

...unimal hack in qemu to > > > pass features around. > > > > > > > I have already done that in last Nov. I made a very rough (yet hacky) > > version (only with Tx path) in one day while companying my wife in > > hospital. > > Any performance data? A straightfoward implementation only brings 10% performance boost in a txonly micro benchmarking. But I'm sure there are still plenty of room for improvement. > > If someone are interested in, I could share the code soon. I could > > even cleanup the code a bit if necessary. > > Especially i...

...> > > > > > > I have already done that in last Nov. I made a very rough (yet hacky) > > > > version (only with Tx path) in one day while companying my wife in > > > > hospital. > > > > > > Any performance data? > > > > A straightfoward implementation only brings 10% performance boost in a > > txonly micro benchmarking. But I'm sure there are still plenty of room > > for improvement. > > > > > > If someone are interested in, I could share the code soon. I could > > > > even cleanup th...

Given f, a pdf over a finite interval, is there any existing R function that can efficiently tabulate the cumulative distribution function for f, or produce all N+1 quantiles of the form i/N? "Efficiently" here means better than doing repeated integrations for each point.

Hi, I am using the reldist package and having problems determining the p-value for the entropy value from the reldist function. I am able to properly determine the entropy value, but cannot figure out what function to use to find the p-value. I have tried using rpy, rpluy (which provides p-values for the polarization values) and investing the results from reldist(). Thus, far I cannot find the