opencl: fix for small models (#11950)

* opencl: fix small shape gemv, remove unused extensions

* opencl: fix `transpose_16`, `dump_tensor`, enforce subgroup size

* opencl: fix for token length < 4

* opencl: use wave size of 64 for all Adreno GPUs

---------

Co-authored-by: Shawn Gu <redacted>
Co-authored-by: Skyler Szot <redacted>

diff --git a/ggml/src/ggml-opencl/ggml-opencl.cpp b/ggml/src/ggml-opencl/ggml-opencl.cpp
index 7a0f94cf24cc230e2e37718191e02e83a2192199..f590624608c301fa24a53c151f912269694069fb 100644 (file)
--- a/ggml/src/ggml-opencl/ggml-opencl.cpp
+++ b/ggml/src/ggml-opencl/ggml-opencl.cpp
@@ -444,19 +444,8 @@ static ggml_backend_opencl_context * ggml_cl2_init(ggml_backend_dev_t dev) {
         backend_ctx->gpu_family = GPU_FAMILY::ADRENO;
         backend_ctx->adreno_gen = get_adreno_gpu_gen(default_device->name);
 
-        // Default wave size is 128, A8x uses 64.
-        if (backend_ctx->adreno_gen == ADRENO_GPU_GEN::A8X) {
-            backend_ctx->adreno_wave_size = 64;
-        } else if (backend_ctx->adreno_gen == ADRENO_GPU_GEN::A7X ||
-                   backend_ctx->adreno_gen == ADRENO_GPU_GEN::X1E) {
-            backend_ctx->adreno_wave_size = 128;
-        } else {
-            backend_ctx->adreno_wave_size = 128;
-            GGML_LOG_WARN("ggml_opencl: Unsupported Adreno GPU: %s, "
-                "using wave size %d, "
-                "may not work as expected\n",
-                backend_ctx->device_name.c_str(), backend_ctx->adreno_wave_size);
-        }
+        // Use wave size of 64 for all Adreno GPUs.
+        backend_ctx->adreno_wave_size = 64;
     } else if (strstr(default_device->name, "Intel")) {
         backend_ctx->gpu_family = GPU_FAMILY::INTEL;
     } else {
@@ -1376,6 +1365,11 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
         int M = tensor->ne[1];   // ne01
         int K = tensor->ne[0];   // ne00
 
+        //For matrix-vector multiplication kernel, we assume K is a multiple of 32
+        GGML_ASSERT(K % 32 == 0);
+        //For transpose kernels, we assume K is a multiple of 4 (satisfied by prior assert), and M is a multiple of 4
+        GGML_ASSERT(M % 4 == 0);
+
         // transpose is out of place, so we need to allocate transposed buffers
         // <----------------------------------------------------------------------------------> //
         // use sub_buffer of max buffer size instead
@@ -1416,36 +1410,36 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
         cl_mem qT_d_image1D;
         cl_mem dT_d_image1D;
 
-        cl_image_format img_fmt_1d = { CL_RGBA, CL_FLOAT };
+        cl_image_format img_fmt_1d = { CL_RGBA, CL_HALF_FLOAT };
         cl_image_desc img_desc_1d;
 
         memset(&img_desc_1d, 0, sizeof(img_desc_1d));
         img_desc_1d.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
-        img_desc_1d.image_width = M * K / 8 / 4;
+        img_desc_1d.image_width = M * K / 4 / 4;
         img_desc_1d.buffer = extra->q;
         q_d_image1D = clCreateImage(context, 0, &img_fmt_1d, &img_desc_1d, NULL, &err);
         CL_CHECK(err);
 
-        img_fmt_1d = { CL_RGBA, CL_FLOAT };
+        img_fmt_1d = { CL_RGBA, CL_HALF_FLOAT };
         memset(&img_desc_1d, 0, sizeof(img_desc_1d));
         img_desc_1d.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
-        img_desc_1d.image_width = M * K / 8 / 4;
+        img_desc_1d.image_width = M * K / 4 / 4;
         img_desc_1d.buffer = qT_d;
         qT_d_image1D = clCreateImage(context, 0, &img_fmt_1d, &img_desc_1d, NULL, &err);
         CL_CHECK(err);
 
-        img_fmt_1d = { CL_RGBA, CL_FLOAT };
+        img_fmt_1d = { CL_RGBA, CL_HALF_FLOAT };
         memset(&img_desc_1d, 0, sizeof(img_desc_1d));
         img_desc_1d.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
-        img_desc_1d.image_width = M * K / 32 / 4 / 2;
+        img_desc_1d.image_width = M * K / 32 / 4;
         img_desc_1d.buffer = extra->d;
         d_d_image1D = clCreateImage(context, 0, &img_fmt_1d, &img_desc_1d, NULL, &err);
         CL_CHECK(err);
 
-        img_fmt_1d = { CL_RGBA, CL_FLOAT };
+        img_fmt_1d = { CL_RGBA, CL_HALF_FLOAT };
         memset(&img_desc_1d, 0, sizeof(img_desc_1d));
         img_desc_1d.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
-        img_desc_1d.image_width = M * K / 32 / 4 / 2;
+        img_desc_1d.image_width = M * K / 32 / 4;
         img_desc_1d.buffer = dT_d;
         dT_d_image1D = clCreateImage(context, 0, &img_fmt_1d, &img_desc_1d, NULL, &err);
         CL_CHECK(err);
@@ -1454,8 +1448,8 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
         // set up and call the transpose kernels
         // <----------------------------------------------------------------------------------> //
         // weights
-        int height_q = M / 8;
-        int width_q = K / 8 / 4;
+        int height_q = M / 4;
+        int width_q = K / 4 / 4;
         kernel = backend_ctx->kernel_transpose_16;
 
         CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &q_d_image1D));
@@ -1469,8 +1463,8 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
         CL_CHECK(clWaitForEvents(1, &evt));
 
         // scales
-        int height_s = M / 8;
-        int width_s = K / 32 / 8;
+        int height_s = M / 4;
+        int width_s = K / 32 / 4;
 
         kernel = backend_ctx->kernel_transpose_16;
         CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &d_d_image1D));
@@ -1864,7 +1858,6 @@ static void dump_tensor(ggml_backend_t backend, const struct ggml_tensor * tenso
     void * buf_d;
 #endif
 
-#ifdef GGML_USE_OPENCL
     // Make sure everything is done.
     CL_CHECK(clFinish(queue));
 
@@ -1900,7 +1893,6 @@ static void dump_tensor(ggml_backend_t backend, const struct ggml_tensor * tenso
         extra->offset, ggml_nbytes(tensor), buf, 0, NULL, NULL));
     CL_CHECK(clFinish(queue));
 #endif // GGML_OPENCL_SOA_Q
-#endif // GGML_USE_OPENCL
 
     // Open file and dump.
     char fname[512];
@@ -2865,6 +2857,9 @@ static void ggml_cl_mul_mat(ggml_backend_t backend, const ggml_tensor * src0, co
             CL_CHECK(status);
 
             int height_B = N/4;
+            if (height_B == 0) {
+                height_B = 1;
+            }
             int width_B = K/4;
             int padded_height_B = (N + padding)/4;
 
@@ -3013,11 +3008,12 @@ static void ggml_cl_mul_mat(ggml_backend_t backend, const ggml_tensor * src0, co
         }
 
         if (N == 1) {
-            local_work_size[0] = backend_ctx->adreno_wave_size; // localsize
+            size_t wavesize = backend_ctx->adreno_wave_size;
+            local_work_size[0] = wavesize; // localsize
             local_work_size[1] = 4; // reduce factor
             local_work_size[2] = 1;
 
-            global_work_size[0] = M / 2;
+            global_work_size[0] = (((M / 2) + wavesize - 1) / wavesize) * wavesize;
             global_work_size[1] = 4; // reduce factor
             global_work_size[2] = 1;
         }

diff --git a/ggml/src/ggml-opencl/kernels/ggml-opencl.cl b/ggml/src/ggml-opencl/kernels/ggml-opencl.cl
index d3cfb2f91e1306154b997df22a5d7c9df90704d1..8882a8c9c6225675f972a3f04b946dbf34a14f79 100644 (file)
--- a/ggml/src/ggml-opencl/kernels/ggml-opencl.cl
+++ b/ggml/src/ggml-opencl/kernels/ggml-opencl.cl
@@ -1797,6 +1797,9 @@ kernel void kernel_mul_mat_f16_f16(
 //------------------------------------------------------------------------------
 // mul_mat_f16_f32_1row
 //------------------------------------------------------------------------------
+#ifdef ADRENO_GPU
+REQD_SUBGROUP_SIZE_64
+#endif
 kernel void kernel_mul_mat_f16_f32_1row(
         global char * src0,
         ulong offset0,

diff --git a/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle.cl b/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle.cl
index 5e195411d690e3562dc28e452197b5e7bb743067..ee5c79f000d695f0b34f2f0c4cdab6876ddd634c 100644 (file)
--- a/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle.cl
+++ b/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle.cl
@@ -1,9 +1,11 @@
 #pragma OPENCL EXTENSION cl_khr_fp16 : enable
 #pragma OPENCL EXTENSION cl_khr_subgroups : enable
-#pragma OPENCL EXTENSION cl_qcom_subgroup_uniform_load: enable
-#pragma OPENCL EXTENSION cl_qcom_subgroup_constant_load: enable
-#pragma OPENCL EXTENSION cl_qcom_extra_vector_types : enable
+
+#ifdef cl_qcom_reqd_sub_group_size
 #pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
+#define ADRENO_GPU 1
+#define REQD_SUBGROUP_SIZE_64 __attribute__((qcom_reqd_sub_group_size("half")))
+#endif
 
 // assume
 #define QK4_0 32
@@ -186,8 +188,9 @@
     total_sums.s1 += (((bits4.s7 & 0x0F00) >> 8) - 8) * scale.s1 * shared_y.s6; \
     total_sums.s1 += (((bits4.s7 & 0xF000) >> 12) - 8) * scale.s1 * shared_y.s7; \
 
-
-__attribute__((qcom_reqd_sub_group_size("full")))
+#ifdef ADRENO_GPU
+REQD_SUBGROUP_SIZE_64
+#endif
 __kernel void kernel_gemv_noshuffle(
         __read_only  image1d_buffer_t src0_q,  // quantized A
         global half2  * src0_d,  // A scales

diff --git a/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle_general.cl b/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle_general.cl
index 5bdd4d067639ab0e6fd31a4c0cd1e7d7f9873348..469d3edef00ccdd552894d4916c7e75825f74e1b 100644 (file)
--- a/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle_general.cl
+++ b/ggml/src/ggml-opencl/kernels/ggml-opencl_gemv_noshuffle_general.cl
@@ -1,9 +1,11 @@
 #pragma OPENCL EXTENSION cl_khr_fp16 : enable
 #pragma OPENCL EXTENSION cl_khr_subgroups : enable
-#pragma OPENCL EXTENSION cl_qcom_subgroup_uniform_load: enable
-#pragma OPENCL EXTENSION cl_qcom_subgroup_constant_load: enable
-#pragma OPENCL EXTENSION cl_qcom_extra_vector_types : enable
+
+#ifdef cl_qcom_reqd_sub_group_size
 #pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
+#define ADRENO_GPU 1
+#define REQD_SUBGROUP_SIZE_64 __attribute__((qcom_reqd_sub_group_size("half")))
+#endif
 
 // assume
 #define QK4_0 32
@@ -186,8 +188,9 @@
     total_sums.s1 += (((bits4.s7 & 0x0F00) >> 8) - 8) * scale.s1 * shared_y.s6; \
     total_sums.s1 += (((bits4.s7 & 0xF000) >> 12) - 8) * scale.s1 * shared_y.s7; \
 
-
-__attribute__((qcom_reqd_sub_group_size("full")))
+#ifdef ADRENO_GPU
+REQD_SUBGROUP_SIZE_64
+#endif
 __kernel void kernel_gemv_noshuffle(
         __read_only  image1d_buffer_t src0_q,  // quantized A
         global half2  * src0_d,  // A scales

diff --git a/ggml/src/ggml-opencl/kernels/ggml-opencl_mul_mat_Ab_Bi_8x4.cl b/ggml/src/ggml-opencl/kernels/ggml-opencl_mul_mat_Ab_Bi_8x4.cl
index 57768c80334eb95fe111f51ae64ce86270ce009a..ecb577b99333982e03e9ac2ef03cc020f5fd0327 100644 (file)
--- a/ggml/src/ggml-opencl/kernels/ggml-opencl_mul_mat_Ab_Bi_8x4.cl
+++ b/ggml/src/ggml-opencl/kernels/ggml-opencl_mul_mat_Ab_Bi_8x4.cl
@@ -7,7 +7,16 @@
 #pragma OPENCL EXTENSION cl_khr_fp16 : enable
 #pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
 
-__attribute__((qcom_reqd_sub_group_size("full")))
+#ifdef cl_qcom_reqd_sub_group_size
+#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
+#define ADRENO_GPU 1
+#define REQD_SUBGROUP_SIZE_128 __attribute__((qcom_reqd_sub_group_size("full")))
+#endif
+
+#ifdef ADRENO_GPU
+REQD_SUBGROUP_SIZE_128
+#endif
+
 kernel void kernel_mul_mat_Ab_Bi_8x4(
         global const ushort * src0_q,       // quantized A
         global const half  * src0_d,        // A scales

diff --git a/ggml/src/ggml-opencl/kernels/ggml-opencl_transpose_16.cl b/ggml/src/ggml-opencl/kernels/ggml-opencl_transpose_16.cl
index d59a0c05ddfd025425c3673f5fe1d3b32d7b6dcb..cd4e0afbad27988ca73ca1209a1ec63d2860477b 100644 (file)
--- a/ggml/src/ggml-opencl/kernels/ggml-opencl_transpose_16.cl
+++ b/ggml/src/ggml-opencl/kernels/ggml-opencl_transpose_16.cl
@@ -1,4 +1,6 @@
-// 16-bit transpose, loading/storing an 8x8 tile of elements
+// 16-bit transpose, loading/storing a 4x4 tile of elements
+
+#pragma OPENCL EXTENSION cl_khr_fp16 : enable
 
 kernel void kernel_transpose_16(
     __read_only image1d_buffer_t input,
@@ -9,24 +11,16 @@ kernel void kernel_transpose_16(
 
     const int i = get_global_id(0);
     const int j = get_global_id(1);
-    const int i_3 = i<<3;
-    const int j_3 = j<<3;
+    const int i_2 = i<<2;
+    const int j_2 = j<<2;
 
-    ushort8 temp0 = as_ushort8(read_imagef(input, (j_3+0)*cols+i));
-    ushort8 temp1 = as_ushort8(read_imagef(input, (j_3+1)*cols+i));
-    ushort8 temp2 = as_ushort8(read_imagef(input, (j_3+2)*cols+i));
-    ushort8 temp3 = as_ushort8(read_imagef(input, (j_3+3)*cols+i));
-    ushort8 temp4 = as_ushort8(read_imagef(input, (j_3+4)*cols+i));
-    ushort8 temp5 = as_ushort8(read_imagef(input, (j_3+5)*cols+i));
-    ushort8 temp6 = as_ushort8(read_imagef(input, (j_3+6)*cols+i));
-    ushort8 temp7 = as_ushort8(read_imagef(input, (j_3+7)*cols+i));
+    half4 temp0 = read_imageh(input, (j_2+0)*cols+i);
+    half4 temp1 = read_imageh(input, (j_2+1)*cols+i);
+    half4 temp2 = read_imageh(input, (j_2+2)*cols+i);
+    half4 temp3 = read_imageh(input, (j_2+3)*cols+i);
 
-    write_imagef(output, (i_3+0)*rows+j, as_float4((ushort8)(temp0.s0, temp1.s0, temp2.s0, temp3.s0, temp4.s0, temp5.s0, temp6.s0, temp7.s0)));
-    write_imagef(output, (i_3+1)*rows+j, as_float4((ushort8)(temp0.s1, temp1.s1, temp2.s1, temp3.s1, temp4.s1, temp5.s1, temp6.s1, temp7.s1)));
-    write_imagef(output, (i_3+2)*rows+j, as_float4((ushort8)(temp0.s2, temp1.s2, temp2.s2, temp3.s2, temp4.s2, temp5.s2, temp6.s2, temp7.s2)));
-    write_imagef(output, (i_3+3)*rows+j, as_float4((ushort8)(temp0.s3, temp1.s3, temp2.s3, temp3.s3, temp4.s3, temp5.s3, temp6.s3, temp7.s3)));
-    write_imagef(output, (i_3+4)*rows+j, as_float4((ushort8)(temp0.s4, temp1.s4, temp2.s4, temp3.s4, temp4.s4, temp5.s4, temp6.s4, temp7.s4)));
-    write_imagef(output, (i_3+5)*rows+j, as_float4((ushort8)(temp0.s5, temp1.s5, temp2.s5, temp3.s5, temp4.s5, temp5.s5, temp6.s5, temp7.s5)));
-    write_imagef(output, (i_3+6)*rows+j, as_float4((ushort8)(temp0.s6, temp1.s6, temp2.s6, temp3.s6, temp4.s6, temp5.s6, temp6.s6, temp7.s6)));
-    write_imagef(output, (i_3+7)*rows+j, as_float4((ushort8)(temp0.s7, temp1.s7, temp2.s7, temp3.s7, temp4.s7, temp5.s7, temp6.s7, temp7.s7)));
+    write_imageh(output, (i_2+0)*rows+j, (half4)(temp0.s0, temp1.s0, temp2.s0, temp3.s0));
+    write_imageh(output, (i_2+1)*rows+j, (half4)(temp0.s1, temp1.s1, temp2.s1, temp3.s1));
+    write_imageh(output, (i_2+2)*rows+j, (half4)(temp0.s2, temp1.s2, temp2.s2, temp3.s2));
+    write_imageh(output, (i_2+3)*rows+j, (half4)(temp0.s3, temp1.s3, temp2.s3, temp3.s3));
 }