CUDA: fix crash on large batch size for MoE models#13384
Merged
JohannesGaessler merged 1 commit intoggml-org:masterfrom May 9, 2025
Merged
CUDA: fix crash on large batch size for MoE models#13384JohannesGaessler merged 1 commit intoggml-org:masterfrom
JohannesGaessler merged 1 commit intoggml-org:masterfrom
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I'm testing now! Great work as usual! |
Contributor
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@JohannesGaessler Looks like it works! Great work! |
CISC
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May 9, 2025
gabe-l-hart
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May 9, 2025
* origin/master: (39 commits) server : vision support via libmtmd (ggml-org#12898) sycl : implementation of reordered Q4_0 MMVQ for Intel GPUs (ggml-org#12858) metal : optimize MoE for large batches (ggml-org#13388) CUDA: FA support for Deepseek (Ampere or newer) (ggml-org#13306) llama : do not crash if there is no CPU backend (ggml-org#13395) CUDA: fix crash on large batch size for MoE models (ggml-org#13384) imatrix : Add --parse-special for enabling parsing of special tokens in imatrix calculation (ggml-org#13389) llama-run: add support for downloading models from ModelScope (ggml-org#13370) mtmd : fix batch_view for m-rope (ggml-org#13397) llama : one-off chat template fix for Mistral-Small-2503 (ggml-org#13398) rpc : add rpc_msg_set_tensor_hash_req (ggml-org#13353) vulkan: Allow up to 4096 elements for mul_mat_id row_ids (ggml-org#13326) server : (webui) rename has_multimodal --> modalities (ggml-org#13393) ci : limit write permission to only the release step + fixes (ggml-org#13392) mtmd : Expose helper_decode_image_chunk (ggml-org#13366) server : (webui) fix a very small misalignment (ggml-org#13387) server : (webui) revamp the input area, plus many small UI improvements (ggml-org#13365) convert : support rope_scaling type and rope_type (ggml-org#13349) mtmd : fix the calculation of n_tokens for smolvlm (ggml-org#13381) context : allow cache-less context for embeddings (ggml-org#13108) ...
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Fixes #13376 .
I was not able to reproduce the issue but what I think is happening is that the total number of columns being assembled for
MUL_MAT_IDis > 65535, the maximum dimension of CUDA grids in the y and z dimension. Presumably the issue can then be fixed by just swapping the x and y dimension since the limit for the x dimension is 2^31-1. @danielhanchen please confirm whether or not the fix works.