similar to: lattice dotplot with missing levels in factor variable

Hi, How does the requirement that phi instructions have one value per predecessor basic block interact with indirectbr instructions? For instance, take the following code: L1: br i1 %somevalue, label %L2, label %L3 L2: %ret1 = i8* blockaddress(@myfunction, %L5) br label %L4 L3: %ret2 = i8* blockaddress(@myfunction, %L6) br label %L4 L4: %ret = phi i8* [%ret1, L2], [%ret2, L3]

The following IR implements the following nested loop: for (int i = start ; i < end ; ++i ) for (int p = 0 ; p < 4 ; ++p ) a[i*4+p] = b[i*4+p] + c[i*4+p]; define void @main(i64 %arg0, i64 %arg1, i1 %arg2, i64 %arg3, float* noalias %arg4, float* noalias %arg5, float* noalias %arg6) { entrypoint: br i1 %arg2, label %L0, label %L1 L0:

The loop vectorizer relies on cleanup passes to be run after it: from Transforms/IPO/PassManagerBuilder.cpp: // Add the various vectorization passes and relevant cleanup passes for // them since we are no longer in the middle of the main scalar pipeline. MPM.add(createLoopVectorizePass(DisableUnrollLoops)); MPM.add(createInstructionCombiningPass());

After a crash, in my zpool tree, some dataset report this we i do a ls -la: brwxrwxrwx 2 777 root 0, 0 Oct 18 2009 mail-cts also if i set zfs set mountpoint=legacy dataset and then i mount the dataset to other location before the directory tree was only : dataset - vdisk.raw The file was a backing device of a Xen VM, but i cannot access the directory structure of this dataset. However i

The instcombine pass cleans up a lot. Any idea why there are still shufflevector, insertelement, *and* bitcast (!!) etc. instructions left? The original loop is so clean, a textbook example I'd say. There is no need to shuffle anything.At least I don't see it. Frank vector.ph: ; preds = %L5 %broadcast.splatinsert1 = insertelement <4 x

I am trying a setup where the one loop is rewritten as two loops. This avoids the 'rem' and 'div' instructions in the index calculation (which give the loop vectorizer a hard time). However, with this setup the loop vectorizer complains about a too small loop. LV: Checking a loop in "main" LV: Found a loop: L3 LV: Found a loop with a very small trip count. This loop

Hello, #I have two matrices, eg.: y <- matrix( c(20, NA, NA, 45, 50, 19, 32, 101, 10, 22, NA, NA, 80, 49, 61, 190), ncol=4 ) x <- matrix( c(20, NA, NA, NA, 50, 19, 32, 101, 10, 22, NA, NA, 80, 49, 61, 190), ncol=4 ) #Whereas x contains all NA?s from y plus some additional NA?s. #I want to find the index of these additional NA?s. I think, there must be a very

In dotplot, what's the best way to suppress the unused levels of 'y' on a per-panel basis? This is useful for the case that 'y' is a factor taking perhaps thousands of levels, but for a given panel, only a handfull of these levels ever present. Thanks, Ben

In the case when coming from C it was probably the loop unroller and SLP vectorizer which vectorized the code. Potentially I could do the same in the IR. However, the loop body that is generated in the IR can get very large. Thus, the loop unroller will refuse to unroll the loop in a large number of (important) cases. Isn't there a way to convince the loop vectorizer that it should

Hello all, I don't understand a strange behavior in data frame manipulation. data_frame1 = data.frame(Site = c("S1", "S2", "S3", "S4", "L1", "L2", "L3", "L4"), Number = c(1, 3, 5, 2, 1, 1, 2, 1)) data_frame2 = data_frame1 [data_frame1$Site != "S1", ] dput (data_frame2) structure(list(Site =

Hi list, I have a data set - something like this dfr <- data.frame(A=factor(letters[1:25]),B=runif(25), C=sample(LETTERS[1:4],25,replace=TRUE)) and I want to create a dotplot: library(lattice)dotplot(A ~ B | C, data=dfr, scales=list(y=list(relation="free"))) but this puts uneven spaces along the y-axis in each panel. drop.unused.levels=TRUE will drop conditioning

I'm fitting a GLMM to some questionnaire data. The structure is J individuals, nested within I areas, all of whom answer the same K (ordinal) questions. The model I'm using is based on so-called continuation ratios, so that it can be fitted using the lme4 package. The lmer function fits the model just fine, but using mcmcsamp to judge the variability of the parameter estimates produces

Hi to all, I am trying to run breakpoints() on a fairly large sample (>10.000 observations). The process is very slow, any idea on how to speed this up? I have tried the hpc="foreach" parameter, but this didn't work at all when I tried to run it on a smaller sample. breakpoints(x ~ x.l1 + x.l2 + X.l3 + x.l4 + x.l5 + x.l6 + x.l7 + x.l8 + y.l1 + y.l2 + y.l3 + y.l4 + y.l5 + y.l6

On 10/12/2016 3:15 PM, Alex Bradley wrote: > > Yes the result goes into memory. But the *address* of that destination > memory location also needs to be loaded first into a register. > Your architecture has a single instruction for the following operation? define void @foo(i32 **%a, i32**%b) { entry: %l1 = load i32*, i32** %a, align 4 %l2 = load i32, i32* %l1, align 4 %l3 =

Hello All, I have a discontinuous dataset and I used spplot to plot the points. I was wondering whether it is possible to show the legend of the plot as color ramp. I saw that on continuous data. If anyone could tell me that would be great. Another thing I would like to know is how can we create the horizontal legend. By default, the legend is vertical. I was able to shift the legend inside

On 11/12/2009, at 10:43 AM, Anton Korobeynikov wrote: > Hi, Chris > >> That is target independent code, so you should not put sparc specific changes there. It sounds like one of the sparc-specific target hooks is wrong. > Since sparc does not provide any hooks for operation of branches (e.g. > AnalyzeBranch and friends) it might be possible that generic codegen > code is

I am using the dotplot function from the lattice package to display a quantitative variable versus two factors, say 'a' and 'b'. The levels of 'a' are nested within levels of 'b'. The issue is that dotplot includes all the levels of 'a' in each panel (conditioning on 'b'), even though many are empty in any given panel. A toy example is dat

Good afternoon, I would like to ask for help in controlling y-axis limits and labels in lattice doplots. Unfortunately, the problem is somewhat convoluted, please bear with the long explanation. I would like to create a 3x3 lattice of dotplots, say subject ~ count. The plot is conditioned on variables treatment and risk: subject ~ count | treatment + risk. In the experiment, not all subjects

On Feb 8, 2010, at 12:37 AM, Nathan Keynes wrote: > Firstly, the BNE/BA pair should be reduced to a BE (I assume this is > the responsibility of AnalyzeBranch and friends that you mention). Right. Implementing AnalyzeBranch will allow a bunch of block layout and branch optimizations to happen. > However I still wouldn't have expected that to result in the label > being

Hi all, Recently, I read codes about the shadow page table. I''m wondering whether the kernel has provided the function to revoke write access of all the shadows of one domain. If you know one with this function, please tell me about it. Thanks. BTW, I have my own idea to implement this. My idea is as follows: void sh_revoke_write_access_all(struct domain *d) {