Hello,
I have a weird error in my application on Windows 10-based Azure VM with Tesla T4 GPU. I’m getting cudaErrorNotSupported (801) returned by any cudaMallocAsync() method. Code builds without any problems on this VM, GPU device identified correctly, but I’m always getting this cudaErrorNotSupported error.
The same code without any changes works on all physical Windows 10 machines in my team, on Ubuntu 22.04 Azure VM with the same Tesla T4 GPU, inside WSL2 and Docker containers.
What is interesting, is that all samples from the CUDA samples repository work correctly.
But the only differences I was able to identify between my code and the CUDA samples, are:
- CUDA samples use min Compute Capability of 5.2, but my app uses 7.5 (tried to change it in my app - didn’t help).
- CUDA samples use C++11, my code C++20.
Results of Device query from this Azure VM:
CUDA Device Query (Driver API) statically linked version
Detected 1 CUDA Capable device(s)
Device 0: "Tesla T4"
CUDA Driver Version: 12.1
CUDA Capability Major/Minor version number: 7.5
Total amount of global memory: 16218 MBytes (17005740032 bytes)
(40) Multiprocessors, ( 64) CUDA Cores/MP: 2560 CUDA Cores
GPU Max Clock rate: 1590 MHz (1.59 GHz)
Memory Clock rate: 5001 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 4194304 bytes
Max Texture Dimension Sizes 1D=(131072) 2D=(131072, 65536) 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 1024
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Texture alignment: 512 bytes
Maximum memory pitch: 2147483647 bytes
Concurrent copy and kernel execution: Yes with 3 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Concurrent kernel execution: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
CUDA Device Driver Mode (TCC or WDDM): TCC (Tesla Compute Cluster Driver)
Device supports Unified Addressing (UVA): Yes
Device supports Managed Memory: Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 1 / 0 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Result = PASS
I also found that on local machines “CUDA Device Driver Mode” is WWDM, but on the Azure VM - TCC. Not sure if it has any impact.
I completely do not understand what causes this issue. Would be grateful for any advice.