Tagging @JohannesGaessler for visibility!

TLDR:

I'm running imatrix.cpp (latest llama.cpp) with --ubatch-size 8192, but am getting CUDA errors. My suspicion is CUDA needs arguments < INT_MAX (2^31-1), but large physical batch sizes causes CUDA launch errors for MoEs. --ubatch-size 8191 works fine. 8192 does not.

Long form:

I'm running imatrix.cpp with large physical batch sizes (8192), but sadly I get errors with:

CUDA error: invalid configuration argument
  current device: 0, in function ggml_cuda_mul_mat_id at llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:2062
  cudaGetLastError()

ie the error is here:

get_rows_cuda(src1->data, src1->type, ids_to_sorted, src1_sorted.ptr, type_src1_sorted,
        ne10, nb11, nb12, nb13,
        ne_get_rows, 1, 1, sizeof(int32_t), ne_get_rows*sizeof(int32_t), ne_get_rows*sizeof(int32_t),
        ne10*ts_src1_sorted, ne_get_rows*ne10*ts_src1_sorted, ne_get_rows*ne10*ts_src1_sorted, stream);
CUDA_CHECK(cudaGetLastError());

Using --ubatch-size 8192 causes the error to occur on Qwen 3 30B MoE.

--ubatch-size 8191 works fine.

My suspicion is because CUDA I think requires arguments to be < INT_MAX It's because Qwen has 128 experts, 2048 in dim, so 8192 * 2048 * 128 = 2147483648 > 2147483647 (INT_MAX).

8191 * 2048 * 128 = 2147221504, so less than INT_MAX.

Ie one of the arguments:

ne10*ts_src1_sorted, ne_get_rows*ne10*ts_src1_sorted, ne_get_rows*ne10*ts_src1_sorted

is exceeding INT_MAX, thus causing CUDA to error out.