ggml : add ggml_gelu_erf() CUDA kernel (#13719)

* ggml : add ggml_gelu_erf() CUDA kernel

* missing semicolon

Author: ngxson

ggml/src/ggml-cuda/ggml-cuda.cu

@@ -2192,6 +2192,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
                 case GGML_UNARY_OP_SILU:
                     ggml_cuda_op_silu(ctx, dst);
                     break;
+                case GGML_UNARY_OP_GELU_ERF:
+                    ggml_cuda_op_gelu_erf(ctx, dst);
+                    break;
                 case GGML_UNARY_OP_GELU_QUICK:
                     ggml_cuda_op_gelu_quick(ctx, dst);
                     break;
@@ -2977,6 +2980,7 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
                 case GGML_UNARY_OP_SIGMOID:
                 case GGML_UNARY_OP_HARDSIGMOID:
                 case GGML_UNARY_OP_HARDSWISH:
+                case GGML_UNARY_OP_GELU_ERF:
                 case GGML_UNARY_OP_GELU_QUICK:
                 case GGML_UNARY_OP_TANH:
                 case GGML_UNARY_OP_EXP:

ggml/src/ggml-cuda/unary.cu

@@ -23,6 +23,12 @@ static __device__ __forceinline__ float op_gelu(float x) {
     return 0.5f*x*(1.0f + tanhf(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x)));
 }
 
+static __device__ __forceinline__ float op_gelu_erf(float x) {
+    const float SQRT_2_INV = 0.70710678118654752440084436210484f;
+
+    return 0.5f*x*(1.0f + erff(x*SQRT_2_INV));
+}
+
 static __device__ __forceinline__ float op_gelu_quick(float x) {
     const float GELU_QUICK_COEF = -1.702f;
 
@@ -134,6 +140,10 @@ void ggml_cuda_op_gelu(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
     ggml_cuda_op_unary<op_gelu>(ctx, dst);
 }
 
+void ggml_cuda_op_gelu_erf(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    ggml_cuda_op_unary<op_gelu_erf>(ctx, dst);
+}
+
 void ggml_cuda_op_gelu_quick(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
     ggml_cuda_op_unary<op_gelu_quick>(ctx, dst);
 }

ggml/src/ggml-cuda/unary.cuh

@@ -30,6 +30,8 @@ void ggml_cuda_op_silu(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
 
 void ggml_cuda_op_silu_back(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
 
+void ggml_cuda_op_gelu_erf(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
+
 void ggml_cuda_op_gelu_quick(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
 
 void ggml_cuda_op_tanh(ggml_backend_cuda_context & ctx, ggml_tensor * dst);