ggml-cpu: fix SVE leftover path in ggml_vec_dot_f32 (llama/24699)

* ggml-cpu: fix SVE leftover path in ggml_vec_dot_f32

2D convolutions with kernel size 9 produced different results on SVE
enabled ARM devices. After debugging it turned out that ggml_vec_dot_f32
was using data from inactive lanes.

Use svmla_f32_m(pg, sum1, ax1, ay1) so inactive lanes retain sum1.

* cont : clean-up

---------

Co-authored-by: Georgi Gerganov <redacted>

diff --git a/ggml/src/ggml-cpu/vec.cpp b/ggml/src/ggml-cpu/vec.cpp
index 67b6b05cac813acefd8cc78c8f841f220c9fbdb0..ff2b636df86c88a6170da53b6233774d38835ed2 100644 (file)
--- a/ggml/src/ggml-cpu/vec.cpp
+++ b/ggml/src/ggml-cpu/vec.cpp
@@ -75,12 +75,12 @@ void ggml_vec_dot_f32(int n, float * GGML_RESTRICT s, size_t bs, const float * G
             ay1 = GGML_F32_VEC_LOAD(y + i);
             sum1 = GGML_F32_VEC_FMA(sum1, ax1, ay1);
         }
-        // maximum number of leftover elements will be less that ggml_f32_epr. Apply predicated svmad on available elements only
+        // maximum number of leftover elements will be less that ggml_f32_epr. Apply predicated svmla on available elements only
         if (np2 < n) {
             svbool_t pg = svwhilelt_b32(np2, n);
             ax1 = svld1_f32(pg, x + np2);
             ay1 = svld1_f32(pg, y + np2);
-            sum1 = svmad_f32_m(pg, ax1, ay1, sum1);
+            sum1 = svmla_f32_m(pg, sum1, ax1, ay1);
         }
         // reduce sum1,sum2 to sum1
         GGML_F32_VEC_REDUCE(sumf, sum1, sum2, sum3, sum4, sum5, sum6, sum7, sum8);