similar to: [LLVMdev] NVPTX CUDA_ERROR_NO_BINARY_FOR_GPU

Timothy, Those calls to compute grid intrinsics are definitely wrong. In ptx code they should end up into reading special registers, rather than function calls. Try to take some working example and figure out the LLVM IR differences between it and the result of your compiler. - D. ----- Original message ----- > I've written a compiler that outputs PTX code, the result seems fairly >

I'm building this with llvm-c, and accessing these intrinsics via calling the intrinsic as if it were a function. class F_SREG<string OpStr, NVPTXRegClass regclassOut, Intrinsic IntOp> : NVPTXInst<(outs regclassOut:$dst), (ins), OpStr, [(set regclassOut:$dst, (IntOp))]>; def INT_PTX_SREG_TID_X : F_SREG<"mov.u32 \t$dst, %tid.x;",

Ok, as I said, the most precise way to figure out what's wrong is to emit LLVM IR first (use clang -emit-llvm ...) and check out how it differs from working examples, for instance, nvptx regression tests. ----- Original message ----- > I'm building this with llvm-c, and accessing these intrinsics via calling > the intrinsic as if it were a function. > > class F_SREG<string

Hi Timothy, I'm not sure what you mean by this working for other intrinsics, but in this case, I think you want the intrinsic name llvm.nvvm.read.ptx.sreg.tid.x. For me, this looks like: %x = call i32 @llvm.nvvm.read.ptx.sreg.tid.x() Pete On Fri, Mar 1, 2013 at 11:51 AM, Timothy Baldridge <tbaldridge at gmail.com> wrote: > I'm building this with llvm-c, and accessing these

The identifier INT_PTX_SREG_TID_X is the name of an instruction as the back-end sees it, and has very little to do with the name you should use in your IR. Your best bet is to look at the include/llvm/IR/IntrinsicsNVVM.td file and see the definitions for each intrinsic. Then, the name mapping is just: int_foo_bar -> llvm.foo.bar() int_ prefix becomes llvm., and all underscores turn into

Hello, following functions doesnt work correct with my data: median(), geo.mean(). My datafiles contain more than 10.000 lines and six columns from a flow-cytometer-measurment. I need the arithmetic and geometric mean and median. For the calculation of the geometric mean i wrote following function: fix(geo.mean) function(x) { n<-length(x)

Dear all I was thinking about efficient reading data into R and tried several ways to test if load(file.Rdata) or readRDS(file.rds) is faster. The files file.Rdata and file.rds contain the same data, the first created with save(d, ' file.Rdata', compress=F) and the second with saveRDS(d, ' file.rds', compress=F). First I used the function microbenchmark() and was a astonished

Hi R-help, I am working with US COOP network station data and the files are concatenated in single rows for all years, but I need to pull these apart into rows for each day. To do this, I need to extract part of each row such as station id, year, mo, and repeat this against other variables in the row (days). My problem is that there are repeated values for each day, and the files are fixed width

The large value for maximum time may be due to garbage collection, which happens periodically. E.g., try the following, where the unlist(as.list()) creates a lot of garbage. I get a very large time every 102 or 51 iterations and a moderately large time more often mb <- microbenchmark::microbenchmark({ x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000)

This is my first post requesting help to this mailing list. I am new to R. My apologies for any breach in posting etiquette. I am new to this language and just learning my way around. I am attempting to run some sample code and and am confused by the error message: Loading required package: rrcov Error in fitNorm2(fdat[, "FSC-H"], fdat[, "SSC-H"], scalefac = ScaleFactor) :

Note that if you force a garbage collection each iteration the times are more stable. However, on the average it is faster to let the garbage collector decide when to leap into action. mb_gc <- microbenchmark::microbenchmark(gc(), { x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000, control=list(order="inorder")) with(mb_gc,

I've landed the patch in r324449. Before we merge this into two different Clang release branches and almost immediately release one of them, I would really like someone to confirm that this patch works well with the Linux kernel. David, if you're up for that, it would be great. Alternatively, Guenter or someone else here can help. On Tue, Feb 6, 2018 at 5:59 PM Chandler Carruth

Hi, My goal is to use Clang/LLVM/libclc to compile an OpenCL kernel and eventually generate a PTX code. I already did this but I am not sure if the PTX code I am generating is correct (is the one that is supposed to be generated). For example, currently, In OpenCL : get_global_id(0) translates to In LLVM : %call = tail call i32 @get_global_id(i32 0) which translates to In PTX:

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Daniel Dunbar wrote: > Thanks, applied as r78247. Next? :) Oh my, first he is lagging and now it's all a hurry :-) Okay, here comes the next one. I'm taking a short vacation next week so I will try to prepare 1 or 2 of the next patches so that you can work on them as you have time. Greetings, Andi - --

After your pointers I was able to get a little further on with my problem. I installed the software on a Win95 machine to get the DLL's that I needed and the original error message has gone. I can start the program, look at preferences but when I try to connect to another machine there appears to be a problem opening the prxgpxv.vxd file and the connection fails to open..

You need to study how reading files works in your operating system. This question is not about R. -- Sent from my phone. Please excuse my brevity. On August 22, 2017 5:53:09 AM PDT, raphael.felber at agroscope.admin.ch wrote: >Dear all > >I was thinking about efficient reading data into R and tried several >ways to test if load(file.Rdata) or readRDS(file.rds) is faster. The

Thank you all for your help about the encoding of my yahoo.gr. I am sending you now the original data. Hope tha you can read them. I am trying to create a clustered barplot for the following 2 variables: > h$rocbiopsy1 聽 [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 聽[38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 聽[75] 0 0 0 0 0

Hai Elias, 聽 Sorry for the late reply. I do preffer the list, and i understand why you mailt my directly, but best is to keep this on the list. The more eye that see this, the more chance you have on a reply. I must say, i personaly dont use any trust relations ships. that was long ago when i used that, so im bit rusty here. 聽 Now, i see you are using my 4.8.2 packages. so you on debian. *( or

On Wed, 2018-02-07 at 06:20 +0000, Chandler Carruth wrote: > I've landed the patch in r324449. > > Before we merge this into two different Clang release branches and > almost immediately release one of them, I would really like someone > to confirm that this patch works well with the Linux kernel. David, > if you're up for that, it would be great. Alternatively, Guenter

Applied as r78477. I do have a few comments on the patch, below, but I'll wait to see where things are going before acting on them. :) -- > Index: include/llvm/Analysis/ProfileInfo.h > =================================================================== > + // MissingValue - The value that is returned for execution counts in case > + // no value is available. > +