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whisper : remove ggml_mul_mat padding (#3436)

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Georgi Gerganov 2025-09-29 16:42:08 +03:00 committed by GitHub
parent fcf0181ee2
commit b4909a6c78
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@ -252,45 +252,6 @@ static void whisper_set_i32_nd(struct ggml_tensor * t, int64_t i0, int64_t i1, i
*(int32_t *) data = v;
}
// faster matrix multiplications for tensors that do not have dimension 0 divisible by "pad"
// the idea is to represent the original matrix multiplication:
//
// Z = X @ Y
//
// with the sum of two matrix multiplications:
//
// Z = (X_0 @ Y_0) + (X_1 @ Y_1)
//
// here X_0 and Y_0 are views of X and Y that have dimension 0 divisible by "pad"
// and X_1 and Y_1 are the remaining views. X_1 and Y_1 end up being small matrices that can be processed with more
// general-purpose kernels
//
static struct ggml_tensor * ggml_mul_mat_pad(struct ggml_context * ctx, struct ggml_tensor * x, struct ggml_tensor * y, int pad = 32) {
// use padding only if dimension 0 is at least 8 times larger than the padding
// else we won't get much benefit from the optimization
const int n_pad_req = 8;
if (x->ne[0] % pad == 0 || x->ne[0] / pad < n_pad_req) {
return ggml_mul_mat(ctx, x, y);
}
struct ggml_tensor * x_0 = ggml_view_3d(ctx, x, (x->ne[0]/pad)*pad, x->ne[1], x->ne[2], x->nb[1], x->nb[2], 0);
struct ggml_tensor * x_1 = ggml_view_3d(ctx, x, x->ne[0]%pad, x->ne[1], x->ne[2], x->nb[1], x->nb[2], x_0->ne[0]*x_0->nb[0]);
struct ggml_tensor * y_0 = ggml_view_3d(ctx, y, (y->ne[0]/pad)*pad, y->ne[1], y->ne[2], y->nb[1], y->nb[2], 0);
struct ggml_tensor * y_1 = ggml_view_3d(ctx, y, y->ne[0]%pad, y->ne[1], y->ne[2], y->nb[1], y->nb[2], y_0->ne[0]*y_0->nb[0]);
return ggml_add(ctx,
ggml_mul_mat(ctx, x_0, y_0),
ggml_mul_mat(ctx, x_1, y_1));
}
// TODO: check if other platforms can benefit from this optimization
// TODO: CUDA is currently broken - seems ggml_mul_mat does not handle views correctly
#if defined(GGML_USE_METAL)
#define ggml_mul_mat ggml_mul_mat_pad
#endif
// available whisper models
enum e_model {
MODEL_UNKNOWN,