Use cblas_sgemm() to implement ggml_compute_forward_out_prod()

ggml.c

@@ -9598,6 +9598,35 @@ static void ggml_compute_forward_mul_mat(
 
 // ggml_compute_forward_out_prod
 
+#if defined(GGML_USE_ACCELERATE)
+    // helper function to determine if it is better to use BLAS or not
+    // based on ggml_compute_forward_mul_mat_use_blas()
+    // However, testing suggested that BLAS was never slower than the existing code
+static bool ggml_compute_forward_out_prod_use_blas(
+        const struct ggml_tensor * src0,
+        const struct ggml_tensor * src1,
+              struct ggml_tensor * dst) {
+
+    UNUSED(dst);
+//    const int64_t ne10 = src1->ne[0];
+//
+//    const int64_t ne0 = dst->ne[0];
+//    const int64_t ne1 = dst->ne[1];
+
+    if (ggml_is_matrix(src0) &&
+        ggml_is_matrix(src1) &&
+        ggml_is_contiguous(src0) &&
+        (ggml_is_contiguous(src1) || ggml_is_transposed(src1))){ //&&
+        //(ne0 >= 32 && ne1 >= 32 && ne10 >= 32)) {
+        return true;
+    }
+//    if (ne0 >= 32 && ne1 >= 32 && ne10 >= 32) {
+//        printf("Cannot use BLAS for large matrix at %s; ne0: %lld, ne1: %lld, ne10:, %lld", dst->name, ne0, ne1, ne10);
+//    }
+    return false;
+}
+#endif
+
 static void ggml_compute_forward_out_prod_f32(
         const struct ggml_compute_params * params,
         const struct ggml_tensor * src0,
@@ -9634,7 +9663,13 @@ static void ggml_compute_forward_out_prod_f32(
     // TODO: #if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
 
     if (params->type == GGML_TASK_INIT) {
-        ggml_vec_set_f32(ne0*ne1*ne2*ne3, dst->data, 0);
+#if !defined(GGML_USE_ACCELERATE) // gemm beta will do this
+        if (!ggml_compute_forward_out_prod_use_blas(src0, src1, dst)) {
+#endif
+            ggml_vec_set_f32(ne0*ne1*ne2*ne3, dst->data, 0);
+#if !defined(GGML_USE_ACCELERATE)
+        }
+#endif
         return;
     }
 
@@ -9642,6 +9677,50 @@ static void ggml_compute_forward_out_prod_f32(
         return;
     }
     
+#if defined(GGML_USE_ACCELERATE)
+    if (ggml_compute_forward_out_prod_use_blas(src0, src1, dst)) {
+        if (params->ith != 0) { // All threads other than the first do no work.
+            return;
+        }
+        // Arguments to ggml_compute_forward_out_prod (expressed as major,minor)
+        // src0: (k,n)
+        // src1: (k,m)
+        // dst:  (m,n)
+        //
+        // Arguments to sgemm (see https://github.com/Reference-LAPACK/lapack/blob/master/BLAS/SRC/sgemm.f)
+        // Also expressed as (major,minor)
+        // a: (m,k): so src1 transposed
+        // b: (k,n): so src0
+        // c: (m,n)
+        //
+        // However, if ggml_is_transposed(src1) is true, then
+        // src1->data already contains a transposed version, so sgemm mustn't
+        // transpose it further.
+        
+        int n = src0->ne[0];
+        int k = src0->ne[1];
+        int m = src1->ne[0];
+        
+        int transposeA, lda;
+        
+        if (!ggml_is_transposed(src1)) {
+            transposeA = CblasTrans;
+            lda = m;
+        } else {
+            transposeA = CblasNoTrans;
+            lda = k;
+        }
+        
+        float * a = (float *) ((char *) src1->data);
+        float * b = (float *) ((char *) src0->data);
+        float * c = (float *) ((char *) dst->data);
+  
+        cblas_sgemm(CblasRowMajor, transposeA, CblasNoTrans, m, n, k, 1.0, a, lda, b, n, 0.0, c, n);
+        
+        return;
+    }
+#endif
+
     // dst[:,:,:,:] = 0
     // for i2,i3:
     //   for i1: