CUDA thread local array memory is not released after finished kernel execution

I have encountered a problem of which the cuda thread local array memory is not released after kernel execution.

I am using CUDA 9.1 (compute_61,sm_61) on Windows 10.

Below is the code snippet to query device memory:

void query_device_memory(const char * str)
  size_t free_byte;
  size_t total_byte;
  auto cuda_status = cudaMemGetInfo(&free_byte, &total_byte);

  if (cudaSuccess != cuda_status)

    printf("Error: cudaMemGetInfo fails, %s \n", cudaGetErrorString(cuda_status));

  double free_db = (double)free_byte;
  double total_db = (double)total_byte;
  double used_db = total_db - free_db;

  std::cout << "GPU memory usage: used = " << used_db / 1024.0 / 1024.0 << std::endl;

Below is the dummy kernel used to illustrate the problem:

__global__ void dummy_kernel(float * dumm)
  auto const index = threadIdx.x;
  int const val = *dumm;
  float buff_1[16384] = {};
  for (size_t i = 0; i < 16384; i++)
    buff_1[(index * val) % 16384] += *dumm;
  *dumm = buff_1[val % 16384];

int main()

  float * d_dumm;
  CHECK(cudaMalloc(&d_dumm, sizeof(float)));
  CHECK(cudaMemset(d_dumm, 0, sizeof(float)));
  query_device_memory("after malloc:");
  dummy_kernel << <1000, 32 >> > (d_dumm);
  float answer = 0.f;
  CHECK(cudaMemcpy(&answer, d_dumm, sizeof(float), cudaMemcpyDeviceToHost));
  return 0;

The output of the program:

GPU memory usage: used = 2204.38
GPU memory usage: used = 2206.38
GPU memory usage: used = 4878.38

This issue is still being worked on. I don’t have any information about a timeframe when the behavior may change.

In the meantime, a method to mitigate the effect is to issue:

cudaDeviceSetLimit(cudaLimitStackSize, 0);

after the kernel call where the memory is desired to be freed.

Using a value of 0 will reset the property to its “default” value for the architecture. Alternatively, if the stack size is needed to be some other value for a subsequent kernel call, that value can be used instead.

After running the above line of code, a subsequent call to cudaMemGetInfo should return results more in line with expectations.

Is this problem only in the values reported by


and the memory is actually available when using cudaMalloc, or is the memory not being freed at all untill calling the setDeviceLimit?