similar to: Debug info for CUDA code

Adding Alexey here who has been driving this effort in llvm. There are about 5 patches waiting on my review: -: https://reviews.llvm.org/D54320 -: https://reviews.llvm.org/D46189 -: https://reviews.llvm.org/D51554 -: https://reviews.llvm.org/D46061 -: https://reviews.llvm.org/D45784 After which I think we're good. -eric On Mon, Dec 3, 2018 at 6:29 PM Valentin Churavy via

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>

Hi Alex, Eric and Valentin, Thanks for the information. I don't mean to push this but I'm in desperate need of debugging some cuda code. I'm not familiar with the llvm internal but it sounds like there's at least line info now, right? If so, can you point me to a branch of llvm that can help tracing the bug down to certain line of code. I believe my bug is simply a write/read

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

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, 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, 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 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

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

I'm building a simple R extension around a CUDA-enabled dynamic library, and I want to run the whole package with cuda-memcheck for debugging purposes. I can run it just fine with Valgrind: $ R --no-save -d valgrind < test.R However, if I try the same thing with cuda-memcheck, $ R --no-save -d cuda-memcheck < test.R I get: *** Further command line arguments ('--no-save ')

On Wed, Apr 8, 2015 at 10:12 AM, Dmitry Mikushin <dmitry at kernelgen.org> wrote: > A tool of this kind here: https://github.com/apc-llc/nvcc-llvm-ir > > 2015-04-08 19:01 GMT+02:00 Ahmed ElTantawy <ahmede at ece.ubc.ca>: > >> Hi, >> >> I wanted to ask whether there is ongoing effort (or an already >> established tool) that enables to convert CUDA

Hi, I wanted to ask whether there is ongoing effort (or an already established tool) that enables to convert CUDA kernels (that uses CUDA specific intrinsics, e.g., threadId.x, __syncthreads(), ...) to LLVM IR. I am aware that I can do this for OpenCL with the help of libclc but I can not find something similar for CUDA. Thanks -------------- next part -------------- An HTML attachment was

Hi, I am trying to convert a simple CUDA program to LLVM IR using clang 3.0. The program is as follows, #include<stdio.h> #nclude<clang/test/SemaCUDA/cuda.h> __global__ void kernfunc(int *a) { *a=threadIdx.x+blockIdx.x*blockDim.x; } int main() { int *h_a,*d_a,n; n=sizeof(int); h_a=(int*)malloc(n); *h_a=5; cudaMalloc((void*)&d_a,n); cudaMemcpy(d_a,h_a,n,cudaMemcpyHostToDevice);

Hi, I received an email from Nvidia, saying that llvm now supports ptx code generation. I am confused how to use llvm as my backend, as it seems clang's support for cuda is not complete yet. My question is: given a cuda program, how can I use llvm to generate ptx code? Thanks, Bo -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi: Does Clang support CUDA? I am looking for a front end for my compiler that can take CUDA programming framework. Thanks, -- *Abid ****************************************************** "I have learned silence from the talkative, toleration from the intolerant, and kindness from the unkind"---Gibran "Success is not for the chosen few, but for the few who choose" --- John

Nvidia previously announced open source LLVM CUDA compiler but now I couldn't find it anywhere. Can anyone help me to point out where I can download source code for playing with? Best Regards, Dan -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20120920/45d097d5/attachment.html>

Hi, I wonder whether the current version of LLVM supports separate compilation and linking of device code, i.e., is there a flag analogous to nvcc's --relocatable-device-code flag? If not, is there any plan to support this? Thanks! Yuanfeng Peng -------------- next part -------------- An HTML attachment was scrubbed... URL:

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, I am trying to write a CUDA memory instrumentation code. So far I have made little progress, please see attached file. In lines 82 and 88 I get error as: ‘LoadOperand’ is not captured and ‘StoreOperand’ is not captured Unfortunately, I am not able to tell if the error is generic C++ or LLVM related. Earlier I had verified the "syntax" of such code in a dummy C++ implementation,

Hi, I am trying to instrument CUDA kernel functions only (llvm-3.9.0). Is there a way to identify cuda kernel functions? I see that in llvm IR for CUDA has nvvm annotations section, where kernel functions are identified for NVPTX usage. I can parse the whole IR for this kernel metadata and then proceed, but this is very clumsy. Other way is to work with cuda-device-only IR. But then I am not