Memory checker bug?

Hello guys,

I’m encountering weird results from CUDA memory checker. It gives me misaligned access to shared memory errors while address it reports is clearly not misaligned. Also,it always happens in random lines and iterations of the code,while all inputs are the same. Also,moving that array out of the shared memory doesn’t trigger any erros in CUDA memory checker anymore.
The code is too big to show it there and I don’t really think the error is related to the code itself, but basically it something like that:
[i]
shared uint32_t test[256];
for(uint32_t i=0; i<256; i++) test[i] = someDataFromConstantMemory;
uint32_t aVal = test[aPseudoRandomVal & 0xFF];// here the error happens

and if we move it out of shared memory,it doesn’t trigger any errors reports from CUDA memory checker:
[i]
uint32_t test[256]; //not in shared memory,no errors anymore
for(uint32_t i=0; i<256; i++) test[i] = someDataFromConstantMemory;
uint32_t aVal = test[aPseudoRandomVal & 0xFF];// everything works fine

And the error is:
[i]
GPU State:
Address Size Type Mem Block Thread blockIdx threadIdx PC Source

000001bc 4 mis ld s 0 0 {0,0,0} {0,0,0} _Z14TestPj+0076f0 f:\kernel.cu:136
000001e8 4 mis ld s 0 1 {0,0,0} {1,0,0} _Z14TestPj+0076f0 f:\kernel.cu:136

Summary of access violations:
f:\kernel.cu(136): error MemoryChecker: #misaligned=2 #invalidAddress=0

Memory Checker detected 2 access violations.
error = misaligned load (shared memory)
gridid = 1
blockIdx = {0,0,0}
threadIdx = {0,0,0}
address = 0x000001bc
accessSize = 4[/i]
So, address = 0x000001bc and accessSize = 4, seems legit, doesn’t it?

Does anyone have any idea of what may cause that problem?
Windows 10 x64, CUDA 8, GTX1070.
Thanks.

yes, it seems legit

it might be a bug in the memory checker. I don’t see how anyone could confirm that, or do anything about it, if you’re unable/unwilling to give a complete code that reproduces the issue.

If your claim that the code doesn’t matter is true, then you should be able to easily provide a simple code that demonstrates the issue.

Anyway if you’re interested in reporting a bug, the best suggestion is to do so at developer.nvidia.com

(Hint: One of the first things they will ask you for is a complete set of steps to reproduce the issue, including the code.)