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vulkan: Optimize GGML_OP_CUMSUM (#18417)

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* vulkan: Optimize GGML_OP_CUMSUM

There are two paths: The preexisting one that does a whole row per workgroup
in a single shader, and one that splits each row into multiple blocks and does
two passes. The first pass computes partials within a block, the second adds
the block partials to compute the final result. The multipass shader is used
when there are a small number of large rows.

In the whole-row shader, handle multiple elements per invocation.

* use 2 ELEM_PER_THREAD for AMD/Intel

* address feedback
This commit is contained in:
Jeff Bolz
2026-01-02 15:32:30 -06:00
committed by GitHub
parent 706e3f93a6
commit 18ddaea2ae
5 changed files with 213 additions and 18 deletions
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ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
+2
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@@ -944,6 +944,8 @@ void process_shaders() {
string_to_spv("sum_rows_f32", "sum_rows.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("count_equal_i32", "count_equal.comp", merge_maps(base_dict, {{"A_TYPE", "int"}, {"B_TYPE", "int"}, {"D_TYPE", "int"}}));
string_to_spv("cumsum_f32", "cumsum.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("cumsum_multipass1_f32", "cumsum_multipass1.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("cumsum_multipass2_f32", "cumsum_multipass2.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("count_experts", "count_experts.comp", merge_maps(base_dict, {{"A_TYPE", "uint"}, {"D_TYPE", "uint"}}));