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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

It's hard to tell what is wrong without a concrete example. E.g., what is the program you are instrumenting? What is the definition of the hook function? How did you link that definition with the binary? One thing suspicious to me is that you may have linked the definition of _Cool_MemRead_Hook as a host function instead of a device function. AFAIK, PTX assembly cannot be linked. So, if you

Hey Jingyue, Thanks for being so responsive! I finally figured out a way to resolve the issue: all I have to do is to use `-only-needed` when merging the device bitcodes with llvm-link. However, since we actually need to instrument the host code as well, I encountered another issue when I tried to glue the instrumented host code and fatbin together. When I only instrumented the device code, I

Hi Jingyue, Sorry to ask again, but how exactly could I glue the fatbin with the instrumented host code? Or does it mean we actually cannot instrument both the host & device code at the same time? Thanks! yuanfeng On Tue, Mar 15, 2016 at 10:09 AM, Jingyue Wu <jingyue at google.com> wrote: > Including fatbin into host code should be done in frontend. > > On Mon, Mar 14, 2016

Hey Jingyue, Though I tried `opt -nvvm-reflect` on both bc files, the nvvm reflect anchor didn't go away; ptxas is still complaining about the duplicate definition of of function '_ZL21__nvvm_reflect_anchorv' . Did I misused the nvvm-reflect pass? Thanks! yuanfeng On Fri, Mar 11, 2016 at 10:10 AM, Jingyue Wu <jingyue at google.com> wrote: > According to the examples you

Hi all, I compiled the *llvm3.9* source code on the *Nvidia TX1* board. And now I am following the document in the docs/CompileCudaWithLLVM.rst to compile cuda program with clang++. However, when I compile `axpy.cu` using `nvcc`, *nvcc* can generate the correct the binary; while compiling `axpy.cu` using clang++, the detailed command is `clang++ axpy.cu -o axpy --cuda-gpu-arch=sm_53

Yes, I followed the guide. The same error showed up: >clang++ axpy.cu -o axpy --cuda-gpu-arch=sm_35 -L/usr/local/cuda/lib64 -I/usr/local/cuda/include -lcudart_static -ldl -lrt -pthread error: unable to create target: 'No available targets are compatible with this triple.' ________________________________ From: Kevin Choi <code.kchoi at gmail.com> Sent: Wednesday, August 2,

Hi, I have trouble compiling CUDA code with Clang. The following is a command I tried: > clang++ axpy.cu -o axpy --cuda-gpu-arch=sm_35 --cuda-path=/usr/local/cuda The error message is error: unable to create target: 'No available targets are compatible with this triple.' The info of the LLVM I'm using is as follows: > lang++ --version clang version 6.0.0

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

Hi Char, I found the problem, for some reason the last patch was applied correctly. Just committed the fixed version. Tried to compile axpy.cu, everything works. ------------- Best regards, Alexey Bataev 23.01.2019 13:37, treinz пишет: > Hi Alexey, > > I tried the b7195a6 from the llvm github mirror, which does include > your commit D46189 <https://reviews.llvm.org/D46189> (see

Dear all, In the official document <https://llvm.org/docs/CompileCudaWithLLVM.html>, it is mentioned that CUDA compilation is supported on Windows as of 2017-01-05. I used msys2 to install clang 5.0.1. Then I installed cuda 8.0. However, I basically could not compile any code of cuda by the prescribed setting. I wounder if anyone can successfully compile cuda code by the clang on Windows.

+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 >

Hi Alexey, Thanks for the great work! The version I checked out works most of the time. But I do encounter crashes sometimes. I can't file a bug report on https://bugs.llvm.org/ because I don't have an account. I sent an email to bugs-admin at lists.llvm.org for an account already but I haven't heard back. Meanwhile, can you take a look at the issue? I'm attaching the bug report

Hi, it looks like you're compiling CUDA for an ARM host? This is not a configuration we have tested, nor is it something we have the capability of testing at the moment. You may be able to make it work by providing the appropriate -isystem flags to clang so that it can find your headers, but who knows, it may be more complicated than that. Regards, -Justin On Wed, Oct 26, 2016 at 9:59 PM,

Hi Alexey, Is there any option for clang to turn on debug for the host code only but not the device code? I've been using something like -ggdb3 -O0 but this generate debug info for both host and device. I'm trying to work around the aforementioned ptxas bug. Thanks, Char At 2019-02-28 02:09:54, "Alexey Bataev" <a.bataev at outlook.com> wrote: Hi Char, it looks like

Are you planning to release this as soon as it's ready or you want to make it into a major release? Is it possible to let me know (maybe by replying to this thread) once the code is ready? I know sometimes it takes a while to get things in the major release. I greatly appreciate your work on this! Thanks, Char 在 2018-12-15 05:19:50，"Alexey Bataev" <a.bataev at outlook.com>

(+llvm-dev) My question was whether your host machine, the one which is running the compiler, is ARM (as opposed to x86 or POWER). The header you pointed to was in "aarch64-linux-gnu", which made me think you might be on an ARM system. If you are not running linux x86, it is not likely to work. If you are running linux x86, we will need much more details about your system in order to

Hi Alexey, Just want to make sure I understand what you said because I'm not familiar with the llvm pipeline, it's this line: /net/gs/vol3/software/modules-sw/cuda/10.0/Linux/RHEL6/x86_64/bin/ptxas" -m64 -g --dont-merge-basicblocks --return-at-end -v --gpu-name sm_75 --output-file /tmp/60663577.1.login.q/testparticles-4fd988.o /tmp/60663577.1.login.q/testparticles-1d20c4.s that

Hi Alexey, I submitted the bug report to nvidia. While they are working on it, can you share some insight in what could potentially cause this? I just want to get a sense if such a bug require significant amount of work to fix, which can help me make some decision moving forward with my project. Thanks, Char At 2019-02-27 03:19:02, "Alexey Bataev" <a.bataev at outlook.com>

Hi Alexey, Almost a year has passed and Nvidia finally fixes the ptxas issue in CUDA 10.2 according to: https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#cuda-compiler-resolved-issues However, I can not yet use it with llvm 9.0.0 release because CUDA 10.2 is not supported yet. Is there other branches of the llvm repo that supports CUDA 10.2 now? Or do I need to wait for llvm 10