FFT RuntimeError: FFT_INVALID_DESCRIPTOR
jedcheng opened this issue · 6 comments
jedcheng commented
Describe the bug
Hi all
I am working on a scientific solver based on pytorch. The software worked perfectly on Nvidia GPUs and Arm/x86 CPUs.
However, there was an error related to the FFT function when I ran it on an Intel GPU.
The error is down to the inverse real FFT call:
x = torch.rand(1000,1000,1,3).to(torch.device("xpu"))
torch.fft.irfftn(x)
which returns the error:
RuntimeError: FFT_INVALID_DESCRIPTOR
Versions
Collecting environment information...
PyTorch version: N/A
PyTorch CXX11 ABI: N/A
IPEX version: N/A
IPEX commit: N/A
Build type: N/A
OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: N/A
IGC version: 2023.2.0 (2023.2.0.20230721)
CMake version: version 3.22.1
Libc version: glibc-2.35
Python version: 3.9.16 (main, Jun 15 2023, 02:33:25) [GCC 13.1.0] (64-bit runtime)
Python platform: Linux-5.15.0-91-generic-x86_64-with-glibc2.35
Is XPU available: N/A
DPCPP runtime version: 2023.2.1
MKL version: 2023.2.0
GPU models and configuration:
N/A
Intel OpenCL ICD version: 23.22.26516.32-682~22.04
Level Zero version: 1.3.26516.32-682~22.04
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 52 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 224
On-line CPU(s) list: 0-223
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Platinum 8480+
CPU family: 6
Model: 143
Thread(s) per core: 2
Core(s) per socket: 56
Socket(s): 2
Stepping: 8
CPU max MHz: 3800.0000
CPU min MHz: 800.0000
BogoMIPS: 4000.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 5.3 MiB (112 instances)
L1i cache: 3.5 MiB (112 instances)
L2 cache: 224 MiB (112 instances)
L3 cache: 210 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-55,112-167
NUMA node1 CPU(s): 56-111,168-223
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==1.24.3
[pip3] torchdiffeq==0.2.4
[pip3] xitorch==0.6.0.dev20230224192755
[conda] blas 1.0 mkl anaconda
[conda] mkl 2023.2.0 intel_49495 file:///opt/intel/oneapi/conda_channel
[conda] mkl-dpcpp 2023.2.0 intel_49495 file:///opt/intel/oneapi/conda_channel
[conda] mkl-service 2.4.0 py39hae59892_35 file:///opt/intel/oneapi/conda_channel
[conda] mkl_fft 1.3.6 py39h173b8ae_56 file:///opt/intel/oneapi/conda_channel
[conda] mkl_random 1.2.2 py39h1595b48_76 file:///opt/intel/oneapi/conda_channel
[conda] mkl_umath 0.1.1 py39hd987cd3_86 file:///opt/intel/oneapi/conda_channel
[conda] numpy 1.24.3 py39hed7eef7_0 file:///opt/intel/oneapi/conda_channel
[conda] numpy-base 1.24.3 py39he88ecf9_0 file:///opt/intel/oneapi/conda_channel
jingxu10 commented
Could you run the env info collection script again in the conda env that you ran into this failure?
We want to know which GPU device was used and which version of software were used.
jedcheng commented
This is a mistake on my side. I was using the dev cloud jupyter notebooks and simply used ! to execute the commands. Thus the GPU didn't show up.
But here is it:
Collecting environment information...
PyTorch version: 2.0.1a0+cxx11.abi
PyTorch CXX11 ABI: Yes
IPEX version: 2.0.110+xpu
IPEX commit: ba7f6c127
Build type: Release
OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: N/A
IGC version: 2023.2.0 (2023.2.0.20230721)
CMake version: version 3.22.1
Libc version: glibc-2.35
Python version: 3.9.16 (main, Jun 15 2023, 02:33:25) [GCC 13.1.0] (64-bit runtime)
Python platform: Linux-5.15.0-91-generic-x86_64-with-glibc2.35
Is XPU available: True
DPCPP runtime version: 2023.2.1
MKL version: 2023.2.0
GPU models and configuration:
[0] _DeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) Level-Zero', dev_type='gpu, support_fp64=1, total_memory=49152MB, max_compute_units=448, gpu_eu_count=448)
Intel OpenCL ICD version: 23.22.26516.32-682~22.04
Level Zero version: 1.3.26516.32-682~22.04
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 52 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 224
On-line CPU(s) list: 0-223
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Platinum 8480+
CPU family: 6
Model: 143
Thread(s) per core: 2
Core(s) per socket: 56
Socket(s): 2
Stepping: 8
CPU max MHz: 3800.0000
CPU min MHz: 800.0000
BogoMIPS: 4000.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 5.3 MiB (112 instances)
L1i cache: 3.5 MiB (112 instances)
L2 cache: 224 MiB (112 instances)
L3 cache: 210 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-55,112-167
NUMA node1 CPU(s): 56-111,168-223
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] intel-extension-for-pytorch==2.0.110+xpu
[pip3] numpy==1.24.3
[pip3] torch==2.0.1a0+cxx11.abi
[pip3] torchdiffeq==0.2.4
[pip3] torchvision==0.15.2a0+cxx11.abi
[pip3] xitorch==0.6.0.dev20230224192755
[conda] intel-extension-for-pytorch 2.0.110 py39_xpu_0 file:///opt/intel/oneapi/conda_channel
[conda] mkl 2023.2.0 intel_49495 file:///opt/intel/oneapi/conda_channel
[conda] mkl-dpcpp 2023.2.0 intel_49495 file:///opt/intel/oneapi/conda_channel
[conda] mkl-service 2.4.0 py39hae59892_35 file:///opt/intel/oneapi/conda_channel
[conda] mkl_fft 1.3.6 py39h173b8ae_56 file:///opt/intel/oneapi/conda_channel
[conda] mkl_random 1.2.2 py39h1595b48_76 file:///opt/intel/oneapi/conda_channel
[conda] mkl_umath 0.1.1 py39hd987cd3_86 file:///opt/intel/oneapi/conda_channel
[conda] numpy 1.24.3 py39hed7eef7_0 file:///opt/intel/oneapi/conda_channel
[conda] numpy-base 1.24.3 py39he88ecf9_0 file:///opt/intel/oneapi/conda_channel
[conda] pytorch 2.0.1 py39_xpu_0 file:///opt/intel/oneapi/conda_channel
[conda] torchvision 0.15.2 py39_0 file:///opt/intel/oneapi/conda_channel
alexsin368 commented
Hi @jedcheng, I see you are using a Max Series 1100 GPU. Right now, our servers are undergoing maintenance until 12/20. I will try reproducing your issue then. Thank you for understanding.
alexsin368 commented
Issue reproduced. Diving deeper to identify the root cause.
alexsin368 commented
@jedcheng this issue is not reproducible on IPEX version 2.1. Please retry and let me know if the issue persists.
jedcheng commented
@jedcheng this issue is not reproducible on IPEX version 2.1. Please retry and let me know if the issue persists.
Thank you for the response and fixing the problem, but I am not able to login to the dev cloud due to a 500 internal server error.
I will test it out once the error is gone. If there are other problems related to Pytorch on Intel GPU when running the solver, I will open another issue.