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Segmentation fault when running Sibernetic built on WSL2 #170

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clausagerskov opened this issue Sep 27, 2020 · 11 comments
Open

Segmentation fault when running Sibernetic built on WSL2 #170

clausagerskov opened this issue Sep 27, 2020 · 11 comments

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@clausagerskov
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clausagerskov commented Sep 27, 2020

Tried building Sibernetic on Windows Subsystem for Linux 2 (Ubuntu 20.04).
The build succeeds but then when I try to run sibernetic using the usual ./Release/Sibernetic -f worm (or any other configuration file), I get a segmentation fault

@clausagerskov clausagerskov changed the title Segmentation fault when running Sibernetic built using CUDA Segmentation fault when running Sibernetic built using CUDA on WSL2 Sep 27, 2020
@clausagerskov clausagerskov reopened this Mar 13, 2022
@clausagerskov clausagerskov changed the title Segmentation fault when running Sibernetic built using CUDA on WSL2 Segmentation fault when running Sibernetic built on WSL2 Mar 13, 2022
@clausagerskov
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impossible to debug sibernetic so just reporting that this is an issue

@mwatts15
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@clausagerskov how is it impossible to debug?

@clausagerskov
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i mean i dont know much about debugging segmentation faults in c++, so i should have said i dont know how to do it rather than its impossible

@clausagerskov
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clausagerskov commented Mar 15, 2022

i cant replicate this in 18.04 though on a different machine, might be an opencl issue since i was testing CUDA support in WSL2

@clausagerskov
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Apparently OpenCL on NVIDIA GPUs is not supported on WSL so this is not expected to work

@clausagerskov
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would be cool if someone with an intel gpu could check if they can run sibernetic on it in WSL2 since it should be supported

@clausagerskov clausagerskov reopened this Mar 15, 2022
@clausagerskov
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this is strange, it happens on my nvidia gpu machine whether or not cuda is installed, even with just intel opencl

@clausagerskov
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commented out the try catch that was obscuring the actual cause of the error. turns out its "No OpenCL devices were found"

@clausagerskov
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this also happens when running in a WSL2 backed docker container.
seems to be a problem when sibernetic selects from opencl platforms and somehow doesnt pick a valid one on systems with nvidia gpus

@clausagerskov
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also happens with hyper-v backed docker containers

@clausagerskov
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clinfo output from docker container:
Number of platforms 1
Platform Name Intel(R) OpenCL
Platform Vendor Intel(R) Corporation
Platform Version OpenCL 1.2
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_icd cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64
Platform Extensions function suffix INTEL

Platform Name Intel(R) OpenCL
Number of devices 1
Device Name 11th Gen Intel(R) Core(TM) i7-11700K @ 3.60GHz
Device Vendor Intel(R) Corporation
Device Vendor ID 0x8086
Device Version OpenCL 1.2 (Build 475)
Driver Version 1.2.0.475
Device OpenCL C Version OpenCL C 1.2
Device Type CPU
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 8
Max clock frequency 3600MHz
Device Partition (core)
Max number of sub-devices 8
Supported partition types by counts, equally, by names (Intel)
Max work item dimensions 3
Max work item sizes 8192x8192x8192
Max work group size 8192
Preferred work group size multiple <getWGsizes:671: create context : error -2>
Preferred / native vector sizes
char 1 / 32
short 1 / 16
int 1 / 8
long 1 / 4
half 0 / 0 (n/a)
float 1 / 8
double 1 / 4 (cl_khr_fp64)
Half-precision Floating-point support (n/a)
Single-precision Floating-point support (core)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero No
Round to infinity No
IEEE754-2008 fused multiply-add No
Support is emulated in software No
Correctly-rounded divide and sqrt operations No
Double-precision Floating-point support (cl_khr_fp64)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Address bits 64, Little-Endian
Global memory size 16788430848 (15.64GiB)
Error Correction support No
Max memory allocation 4197107712 (3.909GiB)
Unified memory for Host and Device Yes
Minimum alignment for any data type 128 bytes
Alignment of base address 1024 bits (128 bytes)
Global Memory cache type Read/Write
Global Memory cache size 262144 (256KiB)
Global Memory cache line size 64 bytes
Image support Yes
Max number of samplers per kernel 480
Max size for 1D images from buffer 262319232 pixels
Max 1D or 2D image array size 2048 images
Max 2D image size 16384x16384 pixels
Max 3D image size 2048x2048x2048 pixels
Max number of read image args 480
Max number of write image args 480
Local memory type Global
Local memory size 32768 (32KiB)
Max number of constant args 480
Max constant buffer size 131072 (128KiB)
Max size of kernel argument 3840 (3.75KiB)
Queue properties
Out-of-order execution Yes
Profiling Yes
Local thread execution (Intel) Yes
Prefer user sync for interop No
Profiling timer resolution 1ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels Yes
SPIR versions 1.2
printf() buffer size 1048576 (1024KiB)
Built-in kernels
Device Extensions cl_khr_icd cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64

NULL platform behavior
clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...) No platform
clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...) No platform
clCreateContext(NULL, ...) [default] No platform
clCreateContext(NULL, ...) [other] <checkNullCtx:2694: create context with device from non-default platform : error -2>
clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) No platform

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