similar to: [LLVMdev] [llvm] r190717 - Adds support for Atom Silvermont (SLM) - -march=slm

Hi, I am trying out the SparseM package and had the a question. The following piece of code works fine: ... fit = slm(model, data = trainData, weights = weight) ... But how do I use the fit object to predict the values on say a reserved testDataSet? In the regular lm function I would do something like this: predict.lm(fit,testDataSet) Thanks -Bala

iterations <- 100 nvars <- 4 combined <- rbind(scaleMiceTrain, scaleMiceTest) reducedSample <- combined reducedSample <- subset(reducedSample, select = -pID50) reducedSample <- subset(reducedSample, select = -id) for (i in 1:iterations) { miceSample <- sample(combined[,-c(1,2)],nvars, replace=FALSE) miceSample$pID50 <- combined$pID50 miceTestSample <-

Could someone advise me about how to react to the message: * checking R code for possible problems ... NOTE slm: no visible binding for global variable 'response' from R CMD check SparseM with * using R version 2.6.0 Under development (unstable) (2007-09-03 r42749) The offending code looks like this: "slm" <- function (formula, data, weights, na.action, method =

I'm trying to use stepAIC on sparse matrices, and I need some help. The documentation for slm.fit suggests: slm.fit and slm.wfit call slm.fit.csr to do Cholesky decomposition and then backsolve to obtain the least squares estimated coefficients. These functions can be called directly if the user is willing to specify the design matrix in matrix.csr form. This is often advantageous in large

Johannes, I tried the last one and it gave me this: error: unknown target CPU 'XYZ' note: valid target CPU values are: nocona, core2, penryn, bonnell, atom, silvermont, slm, goldmont, goldmont-plus, tremont, nehalem, corei7, westmere, sandybridge, corei7-avx, ivybridge, core-avx-i, haswell, core-avx2, broadwell, skylake, skylake-avx512, skx, cascadelake,

Hi All, I created a two variable lm() model slm<-lm(y[1:3000,8]~y[1:3000,12]+y[1:3000,15]) I made two predictions predict(slm,newdata=y[201:3200,]) predict(slm,newdata=y[601:3600,]) there is no error message for either of these. the results are identical, and identical to slm$fitted as well. if this is not the right way to apply the model coefficients to a new set of inputs, what is

Dear R list, members of my course have encountered the following error message: > slm <- lm(price ~ engsize, autoframe) Error in get(x, envir, mode, inherits) : variable "FUN" was not found [more context is given in the fuller listing below]. Once the error is encountered it seems to persist; for example early in one session: > summary(blin.fit) Call: lm(formula = Response

It is my actual target architecture ________________________________ From: Doerfert, Johannes <jdoerfert at anl.gov> Sent: Saturday, March 23, 2019 1:30 PM To: J S Cc: via llvm-dev Subject: Re: [llvm-dev] Generating object files more efficiently I copied "-march=XYZ" from your original email, you have to replace it with your actual target architecture or simply drop it.

-march for clang and -march for llc do different things unfortunately. -march for clang at least on x86 is the same as -mcpu in llc. Which is an artifact of gcc compatibility. ~Craig On Sat, Mar 23, 2019 at 1:40 PM Doerfert, Johannes via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Oh, my bad. > > > Idk why llc seems to know that architecture but clang does not. > >

Hi all, Thanks for your feed-backs :-) @Andrew: In fact, I've reused most of the postRA list scheduler code and the resource priority queue. Every time it needs to move forward, either because of a res hazard (HazardRec) or an invalid combination of instructions in the current packet (DFA), it closes the current bundle and advances to the next cycle. The non-interlocked nature of our

Hi, >From what I can understand from analyzing several *.td files, there are two ways of specifying scheduling information for a specific target, either using SchedWriteRes and InstrItinClass/Data. Specifically looking at ARMScheduleA9.td, I can find both representations and a comment (in the beggining of the file): // This section contains legacy support for itineraries. This is // required

> On Mar 26, 2018, at 5:18 AM, Pedro Lopes via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > Hi, > > From what I can understand from analyzing several *.td files, there are two ways of specifying scheduling information for a specific target, either using SchedWriteRes and InstrItinClass/Data. > > Specifically looking at ARMScheduleA9.td, I can find both

Dear R gurus, I am looking for a way to fit a predictive model for a contingency table which has counts. I found that glm( family=poisson) is very good for figuring out which of several alternative models I should select. But once I select a model it is hard to present and interpret it, especially when it has interactions, because everything is done "relative to reference cell". This

Hello Andy, I want to use the existing scheduling models to estimate performance on a subtarget. For that, I am looking at the new llvm-mca tool where they only use SchedReadWrite and state that not supporting Instruction Itineraries is a limitation. I have also read that the Instruction Itineraries allow to model certain things which cannot be represented in the SchedReadWrite however, I am

On Mar 29, 2012, at 1:18 PM, Tom Stellard <thomas.stellard at amd.com> wrote: > On Thu, Mar 29, 2012 at 02:57:27PM -0500, Sergei Larin wrote: >> Tom, >> >> I do not have your call stack, but packetizer calls >> ScheduleDAGInstrs::buildSchedGraph to create dependency model. If this is >> the first time you use the new MI sched infrastructure (like your

On Thu, Mar 29, 2012 at 03:51:10PM -0700, Andrew Trick wrote: > > On Mar 29, 2012, at 1:18 PM, Tom Stellard <thomas.stellard at amd.com> wrote: > > > On Thu, Mar 29, 2012 at 02:57:27PM -0500, Sergei Larin wrote: > >> Tom, > >> > >> I do not have your call stack, but packetizer calls > >> ScheduleDAGInstrs::buildSchedGraph to create

On Jul 31, 2012, at 8:37 AM, Ivan Llopard <ivanllopard at gmail.com> wrote: > Hi, > > I'm working on a custom top-down post RA scheduler which builds bundles > at the same time for our VLIW processor. I've borrowed most of the > implementation from the resource priority queue implemented for the > existent VLIW scheduler but applied to the context of MI

Using the following example program #include <math.h> double f(double d){ return sqrt(d); } and compiling it with "clang -O3 ...", I was trying to determine what it would take to get the X86 code generator to replace the call to sqrt with a sqrtsd instruction inline. It turns out that it could do exactly that, were it not for the fact that in the function

Guys, Just to clarify that with the current fix in SLM there is no need to wait for other issues to be fixed (minor issue). So you can move on with your patch. From: Agabaria, Mohammed Sent: Wednesday, June 07, 2017 15:24 To: Zaks, Ayal <ayal.zaks at intel.com>; Chandler Carruth <chandlerc at gmail.com>; Flamedoge <code.kchoi at gmail.com>; Dehao Chen <dehao at google.com>

On Mar 4, 2014, at 10:05 AM, Pete Cooper <peter_cooper at apple.com> wrote: > > On Mar 3, 2014, at 2:21 PM, Andrew Trick <atrick at apple.com> wrote: > >> >> On Mar 3, 2014, at 8:53 AM, Pierre-Andre Saulais <pierre-andre at codeplay.com> wrote: >> >>> Hi Andrew, >>> >>> We are currently using a custom model where