"__eh_curr_region" error? No idea how to fix this error

Does anyone know what might cause the following error:

error: identifier “__eh_curr_region” is undefined

I know this sounds very general, but I have a lot of code and up until now it was compiling fine. But now I get this error everytime I run the makefile.
Any suggestions are appreciated

I recently got the same error. Mine was caused by trying to define an array in shared memory whose length was set by another variable.

I narrowed it down and mine is caused by the exact same thing:

shared int arr;

I think this is happening because SIZE is either (a) defined in another file and kernel can’t “see it” or (b) the variable is not declared as constant. Anymore ideas?

Have you tried allocating the shared memory when you call the kernel?

kernel<<<grid, thread, shared_mem_size>>>parameters

global_ kernel (parameters){

extern shared int arr;


This should allow you to dynamically allocate your shared memory

The error occurs at compile time, not runtime so I don’t think it will matter whether or not the shared memory is properly allocated. The problem is with the declaration of the array. I see you’re suggesting declaring the array as extern, could you explain why? And another thing i think i should mention (since i don’t know if it matters or not) my kernel is a device function.

I figured out what causes the error. When declaring an array in shared memory, the size must be specified by a constant variable or an integer:

__constant__ int SIZE = 16;

__global__ void func( ... )


  Â __shared__ float arrayOfFloats;

  Â //or like this:

 Â __shared__ float anotherArrayOfFloats[8];


The solution to this problem is discussed in Section of the CUDA Programming Guide. It describes a method of dynamic allocating shared memory to an array (which is what johsimr was alluding to):

Lastly, don’t forget to specify the appropriate number of bytes dedicated to shared memory in your execution configuration of this kernel (as described in Section 4.2.3).

Hope my explanation helps to anyone with this problem



Thanks to johsimr who mentioned this earlier.

Thanks, ur explanation was really good.

I also defined size of shared memory as constant like below and it worked:

const int SIZE=255;

shared float s_dataX;

So, is there no way to dynamically specify the memory to be allocated? I’m not sure (until runtime) how much shared memory I will be requiring. Should I just assume the worst case and allocate that much memory? Is such an allocation an expensive operation?

look up in the programming guide, that’s how you do runtime shmem allocations

Is there a way to use a variable BLOCK_SIZE? I want to read one from a file in my host code and pass it to the kernel call. The compiler gives me the __eh_curr_region error when I try to do this, even if it is passed as a const int. The allocation of shared variables depends on this BLOCK_SIZE.

Hi, I don’t know how much shared memory i will need in compile time so i need to allocate the shared memory dinamically too. My questions are:

  1. Is there a limit or a maximum for the shared memory you can allocate?
  2. Is this limit different for each device?
  3. How can i know the limit for my device?
    Thanks in advance for any answer. Anyway, i’ll read the section to see if it’s explained there.

There is a limit, currently there is 16kb of shared memory per multiprocessor on all graphics card.

This might chance… who knows.

It is shown in the deviceQuery SDK exemple… you can adapt from there:

Thank you, that is useful for me because now i know how shared memory limits the block_size. Is there a maximum number of blocks you can use when you call your kernel? I assume that if there aren’t enought free multiprocessors they will run a block after another. But maybe i’m not right.

If i’m wrong, please let me know.

The extern keyword allows you to declare your array without a size. If you do not use extern, you must specify a size, and that size has to be constant to avoid the __eh_curr_region error.

The reason you want to not specify a size in the kernel is that you want the allocation to be dynamic. The size of the dynamic array is specified at launch time [font=“Arial Black”]Func<<< Dg, Db, Ns >>>(…);[/font] where Ns is the size of the dynamic array.

Read the rather terse sections and 4.2.3 of the CUDA Programming Guide for details (including how to allocate multiple dynamic arrays). I had to read it a few times before it suddenly made sense. :wacko: