Failed to load CUDA kernel from filter_compute_75.ptx #92900

Closed
opened 2021-11-07 11:56:53 +01:00 by Piotr · 12 comments

System Information
Operating system: Ubuntu 20.04.2 LTS
Graphics card: Nvidia A100-SXM4-40GB
Driver version: 450.119.04
CUDA Version: 11.0

Blender Version
Blender 2.93.5 (hash a791bdabd0 built 2021-10-06 06:26:10)
(unable to generate from Help > Report a Bug, because I am using gui-less mode on server)

Short description of error
When I run python script with .blend file in Blender's background mode, I get following error when it comes to rendering:

Fra:44 Mem:51.55M (Peak 63.32M) | Time:00:00.90 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchroni
zing object | Desk
Fra:44 Mem:51.55M (Peak 63.32M) | Time:00:00.95 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchroni
zing object | Plane
Fra:44 Mem:53.07M (Peak 63.32M) | Time:00:00.96 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Initializ
ing
Fra:44 Mem:51.07M (Peak 63.32M) | Time:00:00.96 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Waiting f
or render to start
Fra:44 Mem:51.08M (Peak 63.32M) | Time:00:00.97 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Loading r
ender kernels (may take a few minutes the first time)
Failed to load CUDA kernel from '/bin/2.93/scripts/addons/cycles/lib/kernel_compute_75.ptx' (Unknown CU
DA error value)

Refer to the Cycles GPU rendering documentation for possible solutions:
https://docs.blender.org/manual/en/latest/render/cycles/gpu_rendering.html

Failed to load CUDA kernel from '/bin/2.93/scripts/addons/cycles/lib/filter_compute_75.ptx' (Unknown CU
DA error value)
Invalid handle in cuModuleGetFunction( &functions.adaptive_stopping, cuModule, "kernel_cuda_adaptive_st
opping") (device_cuda_impl.cpp:601)
Invalid handle in cuModuleGetFunction( &functions.adaptive_filter_x, cuModule, "kernel_cuda_adaptive_fi
lter_x") (device_cuda_impl.cpp:603)
Invalid handle in cuModuleGetFunction( &functions.adaptive_filter_y, cuModule, "kernel_cuda_adaptive_fi
lter_y") (device_cuda_impl.cpp:605)
Invalid handle in cuModuleGetFunction( &functions.adaptive_scale_samples, cuModule, "kernel_cuda_adapti
ve_scale_samples") (device_cuda_impl.cpp:607)
Invalid handle in cuFuncSetCacheConfig(functions.adaptive_stopping, CU_FUNC_CACHE_PREFER_L1) (device_cu
da_impl.cpp:610)
Invalid handle in cuFuncSetCacheConfig(functions.adaptive_filter_x, CU_FUNC_CACHE_PREFER_L1) (device_cu
da_impl.cpp:611)
Invalid handle in cuFuncSetCacheConfig(functions.adaptive_filter_y, CU_FUNC_CACHE_PREFER_L1) (device_cu
da_impl.cpp:612)
Invalid handle in cuFuncSetCacheConfig(functions.adaptive_scale_samples, CU_FUNC_CACHE_PREFER_L1) (devi
ce_cuda_impl.cpp:613)

What's interesting, if I run same command on my local desktop, where I have:
Operating system: Ubuntu 18.04.5 LTS
Graphics card: Nvidia GeForce GT 1030
Driver version: 450.102.04
CUDA Version: 11.0,
everything works as expected.

Exact steps for others to reproduce the error

  1. Prepare following script:
import os

import bmesh  # noqa
import bpy  # noqa
import bpy_extras  # noqa
from bpy import context  # noqa
from mathutils import Vector, geometry  # noqa


def enable_gpus(device_type, use_cpus=False):
    """
    Attribution: https://blender.stackexchange.com/a/156680
    """

    preferences = bpy.context.preferences
    cycles_preferences = preferences.addons["cycles"].preferences
    cuda_devices, opencl_devices = cycles_preferences.get_devices()

    if device_type == "CUDA":
        devices = cuda_devices
    elif device_type == "OPENCL":
        devices = opencl_devices
    else:
        raise RuntimeError("Unsupported device type")

    activated_gpus = []

    for device in devices:
        if device.type == "CPU":
            device.use = use_cpus
        else:
            device.use = True
            activated_gpus.append(device.name)

    cycles_preferences.compute_device_type = device_type
    bpy.context.scene.cycles.device = "GPU"

    return activated_gpus


def render():
    scene = bpy.context.scene
    scene.render.engine = 'CYCLES'
    render_filepath = os.path.join('/tmp/file.jpg')
    scene.render.filepath = render_filepath
    bpy.ops.render.render(write_still=True, use_viewport=True)


def main():
    - Use 'CUDA' or 'OPENCL' for your preferred method of rendering
    - nvidia-docker requires 'CUDA' for GPU rendering.
    enable_gpus("CUDA")
    render()


if __name__ == '__main__':
    main()
  1. Run it in console:
blender --background --python /opt/input/script_mwe.py
  1. Error will abort execution of rendering.

blender.crash.txt

# Blender 2.93.5, Commit date: 2021-10-05 12:04, Hash a791bdabd0b2

# backtrace
blender(BLI_system_backtrace+0x20) [0xa594750]
blender() [0xf6024d]
/lib/x86_64-linux-gnu/libc.so.6(+0x3f040) [0x7f3e911af040]
/usr/lib/x86_64-linux-gnu/libcuda.so(+0x1ff7f1) [0x7f3e47c607f1]
/usr/lib/x86_64-linux-gnu/libcuda.so(+0x113b6c) [0x7f3e47b74b6c]
/usr/lib/x86_64-linux-gnu/libcuda.so(cuFuncSetCacheConfig+0x5e) [0x7f3e47d35d5e]
blender(_ZN3ccl10CUDADevice14load_functionsEv+0xcc) [0x26b76bc]
blender(_ZN3ccl10CUDADevice12load_kernelsERKNS_23DeviceRequestedFeaturesE+0x2cd) [0x26c052d]
blender(_ZN3ccl11MultiDevice12load_kernelsERKNS_23DeviceRequestedFeaturesE+0x45) [0x2697265]
blender(_ZN3ccl5Scene12load_kernelsERNS_8ProgressEb+0x3b5) [0x30cb915]
blender(_ZN3ccl5Scene6updateERNS_8ProgressERb+0x70) [0x30cbfe0]
blender(_ZN3ccl7Session12update_sceneEv+0xe7) [0x30d5767]
blender(_ZN3ccl7Session7run_cpuEv+0x370) [0x30d6790]
blender(_ZN3ccl7Session3runEv+0x42d) [0x30d77dd]
blender(_ZN3ccl6thread3runEPv+0x1e) [0x77be40e]
blender() [0xa7b4160]
/lib/x86_64-linux-gnu/libpthread.so.0(+0x76db) [0x7f3e928f46db]
/lib/x86_64-linux-gnu/libc.so.6(clone+0x3f) [0x7f3e9129171f]

# Python backtrace
**System Information** Operating system: Ubuntu 20.04.2 LTS Graphics card: Nvidia A100-SXM4-40GB Driver version: 450.119.04 CUDA Version: 11.0 **Blender Version** Blender 2.93.5 (hash a791bdabd0b2 built 2021-10-06 06:26:10) (unable to generate from Help > Report a Bug, because I am using gui-less mode on server) **Short description of error** When I run python script with .blend file in Blender's background mode, I get following error when it comes to rendering: ``` Fra:44 Mem:51.55M (Peak 63.32M) | Time:00:00.90 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchroni zing object | Desk Fra:44 Mem:51.55M (Peak 63.32M) | Time:00:00.95 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchroni zing object | Plane Fra:44 Mem:53.07M (Peak 63.32M) | Time:00:00.96 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Initializ ing Fra:44 Mem:51.07M (Peak 63.32M) | Time:00:00.96 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Waiting f or render to start Fra:44 Mem:51.08M (Peak 63.32M) | Time:00:00.97 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Loading r ender kernels (may take a few minutes the first time) Failed to load CUDA kernel from '/bin/2.93/scripts/addons/cycles/lib/kernel_compute_75.ptx' (Unknown CU DA error value) Refer to the Cycles GPU rendering documentation for possible solutions: https://docs.blender.org/manual/en/latest/render/cycles/gpu_rendering.html Failed to load CUDA kernel from '/bin/2.93/scripts/addons/cycles/lib/filter_compute_75.ptx' (Unknown CU DA error value) Invalid handle in cuModuleGetFunction( &functions.adaptive_stopping, cuModule, "kernel_cuda_adaptive_st opping") (device_cuda_impl.cpp:601) Invalid handle in cuModuleGetFunction( &functions.adaptive_filter_x, cuModule, "kernel_cuda_adaptive_fi lter_x") (device_cuda_impl.cpp:603) Invalid handle in cuModuleGetFunction( &functions.adaptive_filter_y, cuModule, "kernel_cuda_adaptive_fi lter_y") (device_cuda_impl.cpp:605) Invalid handle in cuModuleGetFunction( &functions.adaptive_scale_samples, cuModule, "kernel_cuda_adapti ve_scale_samples") (device_cuda_impl.cpp:607) Invalid handle in cuFuncSetCacheConfig(functions.adaptive_stopping, CU_FUNC_CACHE_PREFER_L1) (device_cu da_impl.cpp:610) Invalid handle in cuFuncSetCacheConfig(functions.adaptive_filter_x, CU_FUNC_CACHE_PREFER_L1) (device_cu da_impl.cpp:611) Invalid handle in cuFuncSetCacheConfig(functions.adaptive_filter_y, CU_FUNC_CACHE_PREFER_L1) (device_cu da_impl.cpp:612) Invalid handle in cuFuncSetCacheConfig(functions.adaptive_scale_samples, CU_FUNC_CACHE_PREFER_L1) (devi ce_cuda_impl.cpp:613) ``` What's interesting, if I run same command on my local desktop, where I have: Operating system: Ubuntu 18.04.5 LTS Graphics card: Nvidia GeForce GT 1030 Driver version: 450.102.04 CUDA Version: 11.0, everything works as expected. **Exact steps for others to reproduce the error** 1. Prepare following script: ``` import os import bmesh # noqa import bpy # noqa import bpy_extras # noqa from bpy import context # noqa from mathutils import Vector, geometry # noqa def enable_gpus(device_type, use_cpus=False): """ Attribution: https://blender.stackexchange.com/a/156680 """ preferences = bpy.context.preferences cycles_preferences = preferences.addons["cycles"].preferences cuda_devices, opencl_devices = cycles_preferences.get_devices() if device_type == "CUDA": devices = cuda_devices elif device_type == "OPENCL": devices = opencl_devices else: raise RuntimeError("Unsupported device type") activated_gpus = [] for device in devices: if device.type == "CPU": device.use = use_cpus else: device.use = True activated_gpus.append(device.name) cycles_preferences.compute_device_type = device_type bpy.context.scene.cycles.device = "GPU" return activated_gpus def render(): scene = bpy.context.scene scene.render.engine = 'CYCLES' render_filepath = os.path.join('/tmp/file.jpg') scene.render.filepath = render_filepath bpy.ops.render.render(write_still=True, use_viewport=True) def main(): - Use 'CUDA' or 'OPENCL' for your preferred method of rendering - nvidia-docker requires 'CUDA' for GPU rendering. enable_gpus("CUDA") render() if __name__ == '__main__': main() ``` 2. Run it in console: ``` blender --background --python /opt/input/script_mwe.py ``` 3. Error will abort execution of rendering. **blender.crash.txt** ``` # Blender 2.93.5, Commit date: 2021-10-05 12:04, Hash a791bdabd0b2 # backtrace blender(BLI_system_backtrace+0x20) [0xa594750] blender() [0xf6024d] /lib/x86_64-linux-gnu/libc.so.6(+0x3f040) [0x7f3e911af040] /usr/lib/x86_64-linux-gnu/libcuda.so(+0x1ff7f1) [0x7f3e47c607f1] /usr/lib/x86_64-linux-gnu/libcuda.so(+0x113b6c) [0x7f3e47b74b6c] /usr/lib/x86_64-linux-gnu/libcuda.so(cuFuncSetCacheConfig+0x5e) [0x7f3e47d35d5e] blender(_ZN3ccl10CUDADevice14load_functionsEv+0xcc) [0x26b76bc] blender(_ZN3ccl10CUDADevice12load_kernelsERKNS_23DeviceRequestedFeaturesE+0x2cd) [0x26c052d] blender(_ZN3ccl11MultiDevice12load_kernelsERKNS_23DeviceRequestedFeaturesE+0x45) [0x2697265] blender(_ZN3ccl5Scene12load_kernelsERNS_8ProgressEb+0x3b5) [0x30cb915] blender(_ZN3ccl5Scene6updateERNS_8ProgressERb+0x70) [0x30cbfe0] blender(_ZN3ccl7Session12update_sceneEv+0xe7) [0x30d5767] blender(_ZN3ccl7Session7run_cpuEv+0x370) [0x30d6790] blender(_ZN3ccl7Session3runEv+0x42d) [0x30d77dd] blender(_ZN3ccl6thread3runEPv+0x1e) [0x77be40e] blender() [0xa7b4160] /lib/x86_64-linux-gnu/libpthread.so.0(+0x76db) [0x7f3e928f46db] /lib/x86_64-linux-gnu/libc.so.6(clone+0x3f) [0x7f3e9129171f] # Python backtrace ```
Author

Added subscriber: @VictorAtPL

Added subscriber: @VictorAtPL
Member

Added subscriber: @Alaska

Added subscriber: @Alaska
Member

Changed status from 'Needs Triage' to: 'Needs User Info'

Changed status from 'Needs Triage' to: 'Needs User Info'
Member

This report is very similar to #91879

An important aspect is that you need to be using Nvidia driver version 470 or higher. You're using 450.119.04 which could be causing this issue.

This report is very similar to #91879 An important aspect is that you need to be using Nvidia driver version 470 or higher. You're using 450.119.04 which could be causing this issue.
Author

Added subscribers: @Raimund58, @pmoursnv

Added subscribers: @Raimund58, @pmoursnv
Author

Weird, I was Googling quite a lot to find similar bug, but couldn't find anything worth.

That's right, I am using r450 and I am not able to upgrade the nvidia driver, because I am not the sudoer of the server.

However,

In #91879#1231094, @pmoursnv wrote:
@Raimund58 You could build Blender yourself with CUDA toolkit 11.2, that should give you PTX files that are compatible. Or build a Cubin for sm_80 directly (via CYCLES_CUDA_BINARIES_ARCH CMake variable), then the CUDA toolkit version should not matter.
Blender doesn't ship with a Cubin for sm_80 by default since there are no consumer GPUs using that architecture.

Does it mean that if I build Blender locally (with r450 and Cuda 11.0) with enabled Cubin for sm_80 then it might work? Or this is a vain hope?

Weird, I was Googling quite a lot to find similar bug, but couldn't find anything worth. That's right, I am using r450 and I am not able to upgrade the nvidia driver, because I am not the sudoer of the server. However, > In #91879#1231094, @pmoursnv wrote: > @Raimund58 You could build Blender yourself with CUDA toolkit 11.2, that should give you PTX files that are compatible. Or build a Cubin for sm_80 directly (via `CYCLES_CUDA_BINARIES_ARCH` CMake variable), then the CUDA toolkit version should not matter. > Blender doesn't ship with a Cubin for sm_80 by default since there are no consumer GPUs using that architecture. Does it mean that if I build Blender locally (with r450 and Cuda 11.0) with enabled Cubin for sm_80 then it might work? Or this is a vain hope?
Member

In #92900#1250009, @VictorAtPL wrote:
Does it mean that if I build Blender locally (with r450 and Cuda 11.0) with enabled Cubin for sm_80 then it might work? Or this is a vain hope?

You can give it a try. I'm not sure if it will work but since Patrick Mours works at Nvidia I'm inclined to believe him.

To build Blender you can follow these steps: https://wiki.blender.org/wiki/Building_Blender
If you wish to use Blender 2.93 rather than 3.1 (which can have major bugs as it's early in development), then you should follow the guide described until you get to the step Update and Build. Rather than running the commands:

cd ~/blender-git/blender
make update
make

I would recommend (I'm not sure if the second make update is necessary, but it's worth doing just in case):

cd ~/blender-git/blender
make update
git checkout blender-v2.93-release
make update
make


For help with CUDA and OptiX there is a little bit of information here that might be useful: https://wiki.blender.org/wiki/Building_Blender/CUDA
For configuring the build of the sm_80 kernels make sure you checkout the section on that page that says:

If you will be using the build only on your own computer, you can compile just the kernel needed for your graphics card, to speed up building. For that you need to edit CYCLES_CUDA_BINARIES_ARCH in the CMake configuration, and leave only the architecture needed for your GPU.

However instead of leaving just the architecture you need, you're adding an architecture, sm_80

Note about this section with CUDA: You want to edit the file CMakeCache.txt in ~/blender-git/build_linux/ then run make again in the source directory (~/blender-git/blender/)

> In #92900#1250009, @VictorAtPL wrote: > Does it mean that if I build Blender locally (with r450 and Cuda 11.0) with enabled Cubin for sm_80 then it might work? Or this is a vain hope? You can give it a try. I'm not sure if it will work but since Patrick Mours works at Nvidia I'm inclined to believe him. To build Blender you can follow these steps: https://wiki.blender.org/wiki/Building_Blender If you wish to use Blender 2.93 rather than 3.1 (which can have major bugs as it's early in development), then you should follow the guide described until you get to the step `Update and Build`. Rather than running the commands: > cd ~/blender-git/blender > make update > make I would recommend (I'm not sure if the second make update is necessary, but it's worth doing just in case): > cd ~/blender-git/blender > make update > git checkout blender-v2.93-release > make update > make --- For help with CUDA and OptiX there is a little bit of information here that might be useful: https://wiki.blender.org/wiki/Building_Blender/CUDA For configuring the build of the `sm_80` kernels make sure you checkout the section on that page that says: > If you will be using the build only on your own computer, you can compile just the kernel needed for your graphics card, to speed up building. For that you need to edit CYCLES_CUDA_BINARIES_ARCH in the CMake configuration, and leave only the architecture needed for your GPU. However instead of leaving just the architecture you need, you're adding an architecture, `sm_80` Note about this section with CUDA: You want to edit the file `CMakeCache.txt` in `~/blender-git/build_linux/` then run `make` again in the source directory (`~/blender-git/blender/`)
Author

So I tried to built Blender by myself with sm_80 and compute_80, but it fails.

Please see attached files for Dockerfile (commands I used to compile Blender) and log.
compile.log

Dockerfile

e.g.:

Killed
make[2]: *** [intern/cycles/kernel/CMakeFiles/cycles_kernel_cuda.dir/build.make:990: intern/cycles/kernel/kernel_sm_70.cubin] Error 137
make[2]: *** Waiting for unfinished jobs....

Edit:

Error 137 means I am running out of memory. I do have only 16GB of ram. I'll let you know if I succeed to compile it on larger node.

So I tried to built Blender by myself with `sm_80` and `compute_80`, but it fails. Please see attached files for Dockerfile (commands I used to compile Blender) and log. [compile.log](https://archive.blender.org/developer/F11761484/compile.log) [Dockerfile](https://archive.blender.org/developer/F11761483/Dockerfile) e.g.: ``` Killed make[2]: *** [intern/cycles/kernel/CMakeFiles/cycles_kernel_cuda.dir/build.make:990: intern/cycles/kernel/kernel_sm_70.cubin] Error 137 make[2]: *** Waiting for unfinished jobs.... ``` Edit: Error 137 means I am running out of memory. I do have only 16GB of ram. I'll let you know if I succeed to compile it on larger node.
Member

In #92900#1250099, @VictorAtPL wrote:
Error 137 means I am running out of memory. I do have only 16GB of ram. I'll let you know if I succeed to compile it on larger node.

By default all listed GPU architectures files are compiled at once and that can take up a lot of RAM. You can enable the option WITH_CYCLE_CUDA_BUILD_SERIAL and it should compile each file separately. The compile time will be longer but RAM usage will be much lower.

> In #92900#1250099, @VictorAtPL wrote: > Error 137 means I am running out of memory. I do have only 16GB of ram. I'll let you know if I succeed to compile it on larger node. By default all listed GPU architectures files are compiled at once and that can take up a lot of RAM. You can enable the option `WITH_CYCLE_CUDA_BUILD_SERIAL` and it should compile each file separately. The compile time will be longer but RAM usage will be much lower.
Author

Thank you, @Alaska - I successfully compiled Blender.

However if I use compiled version locally (with Minimal Working Example I pasted on top of this discussion), I get CUDA cuInit: Unknown CUDA error value.
console.log

I'd like firstly to make Blender work locally with GT 1030 before I start it with A100.

I suppose it's more like a CUDA error right now rather than Blender. Do you know any way of how to enable more extensive debug logs of CUDA?

Thank you, @Alaska - I successfully compiled Blender. However if I use compiled version locally (with Minimal Working Example I pasted on top of this discussion), I get `CUDA cuInit: Unknown CUDA error value`. [console.log](https://archive.blender.org/developer/F11766188/console.log) I'd like firstly to make Blender work locally with GT 1030 before I start it with A100. I suppose it's more like a CUDA error right now rather than Blender. Do you know any way of how to enable more extensive debug logs of CUDA?
Member

Changed status from 'Needs User Info' to: 'Archived'

Changed status from 'Needs User Info' to: 'Archived'
Member

In #92900#1250223, @VictorAtPL wrote:
I suppose it's more like a CUDA error right now rather than Blender. Do you know any way of how to enable more extensive debug logs of CUDA?

I'm not sure. I believe your best approach is to continue this discussion on https:*devtalk.blender.org/ or https:*blender.chat/channel/blender-builds where you will likely get help from people more experienced than myself. Also, this site is aimed at bug reports and bug tracking, not for help with compiling Blender (one of the other reasons I'm suggesting those other sites).

Remember to explain your issue and the limitations you're facing (You don't have access to sudo on the A100 system and as such you can't update the GPU drivers to a supported version to use the pre-compiled version of Blender)

> In #92900#1250223, @VictorAtPL wrote: > I suppose it's more like a CUDA error right now rather than Blender. Do you know any way of how to enable more extensive debug logs of CUDA? I'm not sure. I believe your best approach is to continue this discussion on https:*devtalk.blender.org/ or https:*blender.chat/channel/blender-builds where you will likely get help from people more experienced than myself. Also, this site is aimed at bug reports and bug tracking, not for help with compiling Blender (one of the other reasons I'm suggesting those other sites). Remember to explain your issue and the limitations you're facing (You don't have access to `sudo` on the A100 system and as such you can't update the GPU drivers to a supported version to use the pre-compiled version of Blender)
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