similar to: What does .[foo] really mean?

Stamp softlockup thread earlier before do_timer, because the latter is the one to actually trigger lock warning for long-time offline. Or else, I obserevd softlockup warning easily at manual vcpu hot-remove/plug, or when suspend cancel into old context. One point here is to cover both stolen and blocked time to compare with offline threshold. vcpu hotplug falls into ''stolen''

> On Jun 24, 2019, at 10:53 AM, Tian, Xinmin <xinmin.tian at intel.com> wrote: > > To me, it is also an issue related to SIMD signature matching when the vectorizer kicks in. Losing info from FE to BE is not good in general. > Yes, we cannot loose such information. In particular, the three examples I reported are all generating i64 in the scalar function signature: // Type 1

For example, Type 2 case, scalar-foo used call by value while vector-foo used call by ref. The question Johannes is asking is whether we can decipher that after the fact, only by looking at the two function signatures, or need some more info (what kind, what's minimal)? I think we need to list up cases of interest, and for each vector ABI of interest, we need to work on the requirements and

@Xinmin, Saito: If Clang/the frontend generates the version there is no problem, or is there? The frontend knows about the original source type and it's ABI specific lowering already. @Francesco, we should even consider putting the generating capabilities outside of the OpenMP code generation (in the future). That could allow easier reuse by other frontends. Get Outlook for

>In all cases, the IR type of the parameters in `foo` is i64, therefore is not possible to distinguish what C type generated the signature of `foo`. Ouch. >I don’t know if this is going to be a problem for other architectures I haven't checked what IA-32/Intel64 should do for type 2, but I fully agree that this needs to be done properly according to the ABI. >Therefore, I would

>Thank you everybody for their input, and for your patience. This is proving harder than expected! :) Thank you for doing the hard part of the work. Hideki -----Original Message----- From: Francesco Petrogalli [mailto:Francesco.Petrogalli at arm.com] Sent: Monday, June 24, 2019 11:26 AM To: Saito, Hideki <hideki.saito at intel.com> Cc: Doerfert, Johannes <jdoerfert at anl.gov>;

Amara, >I support this direction Thanks for the support. >but are there actually any real world workloads where gather/scatter scalarisation would be worth it, on any micro-architecture? If we don’t have examples and the compile time cost is non-negligible then I think we’d still like to keep the early >bailouts in some form.’ It's not like I have specific application code in

I assume the referring case is something like below, right? #pragma omp parallel num_threads(n) { #pragma omp critical { x = x + 1; } } If that is the case, the programmer is already writing the code that is not "serial equivalent". Our representation for parallelizer is %t = @llvm.region.entry()["omp.parallel"(),

On 01/05/2018 06:28 PM, Saito, Hideki wrote: > Amara, > >> I support this direction > Thanks for the support. > >> but are there actually any real world workloads where gather/scatter scalarisation would be worth it, on any micro-architecture? If we don’t have examples and the compile time cost is non-negligible then I think we’d still like to keep the early >bailouts in

Thanks, Hal. I plan to post a patch w/o HW Legality early bailout first. That should enable further discussion on where the initial very high cost for "illegal masked load/store/gather/scatter" should be coming from --- like should LoopVectorize provide it? Or should it be provided by TTI? I prefer the latter (TTI) but the first revision of the patch will intentionally do the former

The IR-region annotation we proposed is as below, there is no @llvm.parallel.for.iterator()..... There is no change to loop CFG. alloc A[100]; %t = call token @llvm.region.entry()["parallel.for"()] for(i = 0; i < 100; i++) { a[i] = f(i); } @llvm.region.exit(%t)() ["end.parallel.for"()] Xinmin -----Original Message----- From: Johannes Doerfert

> On Mar 8, 2017, at 11:50 AM, Hal Finkel <hfinkel at anl.gov> wrote: > > > On 03/08/2017 01:24 PM, Tian, Xinmin wrote: >> I assume the referring case is something like below, right? >> >> #pragma omp parallel num_threads(n) >> { >> #pragma omp critical >> { >> x = x + 1; >> } >> }

".... the problem Mehdi pointed out regarding the missed initializations of array elements, did you comment on that one yet?" What is the initializations of array elements question? I don't remember this question. Please refresh my memory. Thanks. I thought Mehdi's question is more about what are attributes needed for these IR-annotation for other LLVM pass to understand and

Hi R-users, I am using arima to fit a time series. Now I would like to include an intervention component "It (0 before intervention, 1 after)" using different types of impacts, that is, not only trying the simple abrupt permanent impact (yt = w It ) with the xreg option but also trying with a gradual permanent impact (yt= d * yt-1 + w * It ), following the filosophy of Box and Tiao

I wrote the Rcpp library and the RcppTemplate package to make it easier for developers to contribute packages to the R community. In addition to providing detailed documentation on package creation it provides a clean object mapping between R anc C++ that helps developers to implement packages that benefit from the performance of C++ and the flexibility of R. The package named 'Rcpp' was

Here are another three problems with logarithmic scales: 1) segments() does not work with logarithmic scales. I suggest to change lines 962-973 in "plot.c": for (i = 0; i < n; i++) { if (FINITE(xt(x0[i%nx0])) && FINITE(yt(y0[i%ny0])) && FINITE(xt(x1[i%nx1])) && FINITE(yt(y1[i%ny1]))) { GP->col = INTEGER(col)[i % ncol];

I'm having trouble creating a looping variable and i can't see wher ethe problem arises from any hep gratfully appreciated First create a table x<-table(SURVEY$n_0,exposed) > x exposed False True Under 16 24 1 16-19 68 9 20-24 190 37 25-34 555 204 35-44 330 87 45-54 198 65 55-64 67 35 65+

Dear R users, I read your methods of extracting the variance explained by each predictor in different places. My question is: using the method you suggested, the sum of the deviance explained by all terms is not equal to the deviance explained by the full model. Could you tell me what caused such problem? > set.seed(0) > n<-400 > x1 <- runif(n, 0, 1) > ## to see problem

Dear R users, I still feel new to R so please apologize if I am doing something stupid here. My use of the polygon() function produces a result that I cannot comprehend: In a plot, I would like to shade the area below a normal distribution. However, I do not want the entire area to be shaded, but just the area on the right side of a vertical line that I draw through the distribution (in

On 03/08/2017 12:44 PM, Johannes Doerfert wrote: > I don't know who pointed it out first but Mehdi made me aware of it at > CGO. I try to explain it shortly. > > Given the following situation (in pseudo code): > > alloc A[100]; > parallel_for(i = 0; i < 100; i++) > A[i] = f(i); > > acc = 1; > for(i = 0; i < 100; i++) > acc = acc *