similar to: PTX generation from CUDA file for compute capability 1.0 (sm_10)

Hello Bergström/Eric, Thanks for the reply. The G80(sm_10) architecture was ported on FPGA by a group of researchers (http://www.ecs.umass.edu/ece/tessier/andryc-fpt13.pdf). Our group have some further research interest on this work. I was working on modifying the Clang-LLVM for a couple of months and achieved the required changes. But Clang-LLVM is only allowing me to generate PTX for sm_20,

I was wondering if anyone has encountered this issue when cross compiling cuda on Nvidia TX2 running android. The error is In file included from <built-in>:1: In file included from prebuilts/clang/host/linux-x86/clang-4667116/lib64/clang/7.0.1/include/__clang_cuda_runtime_wrapper.h:219: ../cuda/targets/aarch64-linux-androideabi/include/math_functions.hpp:3477:19: error: no matching function

+Artem Belevich <tra at google.com> On Fri, Mar 23, 2018 at 7:53 PM Bharath Bhoopalam via llvm-dev < llvm-dev at lists.llvm.org> wrote: > I was wondering if anyone has encountered this issue when cross compiling > cuda on Nvidia TX2 running android. > > The error is > In file included from <built-in>:1: > In file included from >

Thanks a lot Justin, I will remove the toolkit header. Just one last question..(maybe ;) ) If I do away with toolkit headers it says unknown type name '__device__'. Does this function qualifier have an alternative ? or I can just do away with ? -- View this message in context: http://llvm.1065342.n5.nabble.com/UNREACHABLE-executed-error-while-trying-to-generate-PTX-tp56026p56093.html

David's change makes nvvm_reflect_anchor unnecessary. The issue with dots in names generated by llvm still needs to be fixed. On Apr 9, 2016 8:32 AM, "Jingyue Wu" <jingyue at google.com> wrote: > Artem, > > With David's http://reviews.llvm.org/rL265060, do you think > __nvvm_reflect_anchor is still necessary? > > On Fri, Apr 8, 2016 at 9:37 AM, Yuanfeng

Hi, I'm trying to install a module - gputools - and keep getting compile time errors about missing R.h Does anyone know where this file can be found? Thanks!

Hi, Looks like "{" and "}" are lost when trying to use the combination of Clang and NVPTX, which may result into clash of definitions of the function-scope and asm-scope. Here is an example: > cat test.cu __attribute__((device)) __attribute__((nv_linkonce_odr)) __inline__ int __any(int a) { int result; asm __volatile__ ("{ \n\t" ".reg .pred

Dmitry, You might be better served by filing this as a bug (http://llvm.org/bugs/). Please include a test case and the steps to reproduce (i.e., what you've provided below). Chad On Jul 10, 2012, at 3:15 PM, Dmitry N. Mikushin wrote: > Hi, > > Looks like "{" and "}" are lost when trying to use the combination of Clang and NVPTX, which may result into clash of

Hi, I work in a large CUDA codebase and use Clang to build some of our CUDA code to improve compilation speed. We're planning to upgrade to CUDA 11 soon, and it appears that CUDA 11 is not yet supported in LLVM. >From the LLVM commits history, I can see that work on CUDA 11 has started. Is this currently being worked on? What is the remaining work left? And is any help needed to finish

Yes, sure, good idea, because might be also Clang-related. http://llvm.org/bugs/show_bug.cgi?id=13322 2012/7/11 Chad Rosier <mcrosier at apple.com> > Dmitry, > You might be better served by filing this as a bug (http://llvm.org/bugs/). > Please include a test case and the steps to reproduce (i.e., what you've > provided below). > > Chad > > On Jul 10, 2012,

Not really. Clang does not have a way to annotate device vs. kernel functions in C/C++ mode. You're probably better off trying to use OpenCL or CUDA mode in clang. In the clang unit tests, there is a cuda.h header that provides very basic support for these keywords: tests/SemaCUDA/cuda.h If you compile as CUDA (use .cu extension, or "-x cuda") and use this header, you will have

Clang currently doesn't support CUDA separate compilation and thus extern __device__ functions and variables cannot be used. Could someone give me any pointers where to look or what has to be done to support this? If at all possible, I'd like to see what's missing and possibly try to tackle it. -------------- next part -------------- An HTML attachment was scrubbed... URL:

Dear LLVM NVPTX maintainers, Just to have the issue recorded, I don't know how important it is: clang generates linkonce_odr out of __inline__, and NVPTX generates .weak out of linkonce_odr (how it happens - a big question, btw, because I can't find anything related in NVPTX asm printer - does it chain to some other printer?), and finally ptxas (both 4.2 and 5) fails to compile it to

Hello, FYI, this is a bug http://llvm.org/bugs/show_bug.cgi?id=13324 When compiling the following code for sm_20, func params are by some reason given with .align 0, which is invalid. Problem does not occur if compiled for sm_10. > cat test.ll ; ModuleID = '__kernelgen_main_module' target datalayout = "e-p:64:64-i64:64:64-f64:64:64-n1:8:16:32:64" target triple =

On Tue, Jun 12, 2012 at 6:11 PM, Dmitry N. Mikushin <maemarcus at gmail.com>wrote: > Dear LLVM NVPTX maintainers, > > Just to have the issue recorded, I don't know how important it is: > > clang generates linkonce_odr out of __inline__, and NVPTX generates .weak > out of linkonce_odr (how it happens - a big question, btw, because I can't > find anything related

On Fri, Mar 4, 2016 at 5:50 PM, Yuanfeng Peng <yuanfeng.jack.peng at gmail.com> wrote: > Hi Jingyue, > > My name is Yuanfeng Peng, I'm a PhD student at UPenn. I'm sorry to bother > you, but I'm having trouble with gpucc in my project, and I would be really > grateful for your help! > > Currently we're trying to instrument CUDA code using LLVM 3.9, and

Well, I tried the command line given by you and I get the following error clang++ nbody.kernel.cu -Xclang -fcuda-is-device -I/home/upitamba/llvm-3.2.src/tools/clang/test/SemaCUDA/ -Xclang -triple -Xclang nvptx64 -Xclang -target-cpu -Xclang sm_10 -S fatal error: error in backend: Cannot select: 0x334a870: v4f32 = NVPTXISD::MoveParam 0x334a770 [ORD=1] [ID=22] 0x334a770: v4f32 =

Dear Yuan, Sorry for delay with reply, Answers on your questions could be different, depending on the math library placement in the code generation pipeline. At KernelGen, we currently have a user-level CUDA math module, adopted from cicc internals [1]. It is intended to be linked with the user LLVM IR module, right before proceeding with the final optimization and backend. Last few months we

Hi Justin, I don't understand, why, for instance, X86 backend handles pow automatically, and NVPTX should be a PITA requiring user to bring his own pow implementation. Even at a very general level, this limits the interest of users to LLVM NVPTX backend. Could you please elaborate on the rationale behind your point? Why the accuracy modes I suggested are not sufficient, in your opinion? - D.

> The issue is really that there is no standard math library for PTX. Well, formally, that could very well be true. Moreover, in some parts CPU math standard is impossible to accomplish on parallel architectures, consider, for example errno behavior. But here we are speaking more about practical side. And the practical side is: past 5 years CUDA claims to accelerate compute applications, and