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etnaviv: Use TP cores to accelerate tensor transformations

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Vivante NPUs can contain systolic arrays that can be used to perform
several kinds of tensor transformations.

Use these to offload the CPU.

Acked-by: Christian Gmeiner <cgmeiner@igalia.com>
Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/25714>
This commit is contained in:
Tomeu Vizoso
2023-11-16 14:41:03 +01:00
committed by Marge Bot
parent d6473ce28e
commit 60c2bcb8af
5 changed files with 873 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/gallium/drivers/etnaviv/etnaviv_ml.c
+50
View File
@@ -13,6 +13,7 @@
#include "etnaviv_debug.h"
#include "etnaviv_emit.h"
#include "etnaviv_ml_nn.h"
#include "etnaviv_ml_tp.h"
#include "etnaviv_ml.h"
struct pipe_resource *
@@ -60,6 +61,16 @@ etna_ml_create_tensor(struct etna_ml_subgraph *subgraph, unsigned idx, unsigned
ML_DBG("created resource %p for tensor %d with size %d\n", res, idx, size);
}
static bool
needs_reshuffle(const struct pipe_ml_operation *poperation)
{
bool has_stride = poperation->conv.stride_x > 1 || poperation->conv.stride_y > 1;
bool pointwise = poperation->conv.pointwise;
unsigned input_width = poperation->input_tensor->dims[1];
return has_stride && !(poperation->conv.depthwise && (input_width > 5 || input_width < 3)) && !pointwise;
}
static void
reference_tensor_with_offset(struct etna_ml_subgraph *subgraph,
unsigned src_tensor,
@@ -84,6 +95,10 @@ dump_graph(struct list_head *etna_operations)
unsigned i = 0;
list_for_each_entry(struct etna_operation, operation, etna_operations, link) {
switch(operation->type) {
case ETNA_JOB_TYPE_TP:
ML_DBG("%3d %-4s %3d %3d",
i, "TP", operation->input_tensor, operation->output_tensor);
break;
case ETNA_JOB_TYPE_NN:
ML_DBG("%3d %-4s %3d %3d in2: %3d",
i, "NN", operation->input_tensor, operation->output_tensor, operation->add_input_tensor);
@@ -107,6 +122,12 @@ lower_operations(struct etna_ml_subgraph *subgraph,
switch(poperation->type) {
case PIPE_ML_OPERATION_TYPE_CONVOLUTION: {
unsigned input_tensor = poperation->input_tensor->index;
if (needs_reshuffle(poperation)) {
struct etna_operation *operation = calloc(1, sizeof(*operation));
etna_ml_lower_reshuffle(subgraph, poperation, operation, &input_tensor);
list_addtail(&operation->link, etna_operations);
}
struct etna_operation *operation = calloc(1, sizeof(*operation));
etna_ml_lower_convolution(subgraph, poperation, operation);
operation->input_tensor = input_tensor;
@@ -129,6 +150,7 @@ lower_operations(struct etna_ml_subgraph *subgraph,
struct etna_operation *operation = calloc(1, sizeof(*operation));
unsigned input_tensor = poperations[0].input_tensor->index;
unsigned output_tensor;
etna_ml_lower_transpose(subgraph, &poperations[0], operation, &output_tensor);
list_for_each_entry(struct etna_operation, operation, etna_operations, link) {
if (operation->input_tensor == input_tensor)
operation->input_tensor = output_tensor;
@@ -150,6 +172,22 @@ lower_operations(struct etna_ml_subgraph *subgraph,
operation->input_tensor_size / 2);
}
/* Detranspose any output tensors that aren't inputs to other operations
* and have output channels, these are the outputs of the graph.
*/
list_for_each_entry_safe(struct etna_operation, operation, etna_operations, link) {
struct pipe_resource *res = etna_ml_get_tensor(subgraph, operation->output_tensor);
if (res != NULL)
continue;
if (operation->output_channels > 1) {
struct etna_operation *transpose_operation = calloc(1, sizeof(*operation));
etna_ml_lower_detranspose(subgraph, operation, transpose_operation);
operation->output_tensor = transpose_operation->input_tensor;
list_add(&transpose_operation->link, &operation->link);
}
}
/* Create any output tensors that aren't inputs to other operations, these
* are the outputs of the graph.
*/
@@ -236,6 +274,9 @@ etna_ml_subgraph_create(struct pipe_context *pcontext,
case ETNA_JOB_TYPE_NN:
etna_ml_compile_operation_nn(subgraph, operation, &instruction);
break;
case ETNA_JOB_TYPE_TP:
etna_ml_compile_operation_tp(subgraph, operation, &instruction);
break;
}
util_dynarray_append(&subgraph->operations, struct etna_vip_instruction, instruction);
@@ -359,6 +400,12 @@ etna_ml_subgraph_invoke(struct pipe_context *pctx, struct pipe_ml_subgraph *psub
if (DBG_ENABLED(ETNA_DBG_DUMP_SHADERS)) {
switch (operation->type) {
case ETNA_JOB_TYPE_TP:
for (unsigned j = 0; j < tp_core_count && operation->configs[j]; j++) {
dump_buffer(operation->configs[j], "tp", dump_id);
dump_id++;
}
break;
case ETNA_JOB_TYPE_NN:
dump_buffer(operation->configs[0], "nn", dump_id);
dump_buffer(operation->coefficients, "compressed", dump_id);
@@ -389,6 +436,9 @@ etna_ml_subgraph_invoke(struct pipe_context *pctx, struct pipe_ml_subgraph *psub
etna_cmd_stream_ref_bo(stream, etna_resource(operation->output)->bo, ETNA_RELOC_WRITE);
switch (operation->type) {
case ETNA_JOB_TYPE_TP:
etna_ml_emit_operation_tp(subgraph, operation, i);
break;
case ETNA_JOB_TYPE_NN:
etna_ml_emit_operation_nn(subgraph, operation, i);
break;
src/gallium/drivers/etnaviv/etnaviv_ml.h
+8
View File
@@ -13,6 +13,13 @@
enum etna_job_type {
ETNA_JOB_TYPE_NN,
ETNA_JOB_TYPE_TP,
};
enum etna_ml_tp_type {
ETNA_ML_TP_TRANSPOSE,
ETNA_ML_TP_DETRANSPOSE,
ETNA_ML_TP_RESHUFFLE,
};
struct etna_ml_subgraph {
@@ -40,6 +47,7 @@ struct etna_operation {
struct list_head link;
enum etna_job_type type;
enum etna_ml_tp_type tp_type;
bool addition;
bool depthwise;
src/gallium/drivers/etnaviv/etnaviv_ml_tp.c
+780
View File
@@ -0,0 +1,780 @@
/*
* Copyright (c) 2023-2024 Tomeu Vizoso <tomeu@tomeuvizoso.net>
* SPDX-License-Identifier: MIT
*/
#include "util/u_inlines.h"
#include "etnaviv_context.h"
#include "etnaviv_debug.h"
#include "etnaviv_emit.h"
#include "etnaviv_ml_tp.h"
#define FIELD(field, bits) uint32_t field : bits;
struct etna_tp_params {
/* 0 */
FIELD(in_image_x_size, 16)
FIELD(unused0, 16)
/* 1 */
FIELD(in_image_y_size, 16)
FIELD(in_image_z_size, 16)
/* 2 */
FIELD(in_image_stride, 16)
FIELD(unused1, 16)
/* 3 */
FIELD(in_image_slice, 32)
/* 4 */
FIELD(in_window_x_start, 16)
FIELD(in_window_y_start, 16)
/* 5 */
FIELD(in_window_x_end, 16)
FIELD(in_window_y_end, 16)
/* 6 */
FIELD(in_tile_sequence, 2)
FIELD(in_tile_global_mem, 1)
FIELD(in_image_global_mem, 1)
FIELD(alu_i2f_enable, 1)
FIELD(alu_square_enable, 1)
FIELD(alu_horz_processing, 3) /* Watch out, it is split in two in the blob */
FIELD(alu_horz_proc_count, 6)
FIELD(alu_horz_proc_stride, 1)
FIELD(alu_vert_processing, 2)
FIELD(unused2, 1)
FIELD(alu_vert_proc_count, 6)
FIELD(alu_vert_proc_stride, 1)
FIELD(alu_nms_enable, 1)
FIELD(alu_pwl_enable, 1)
FIELD(alu_mult_enable, 1)
FIELD(alu_f2i_enable, 1)
FIELD(alu_load_pwl_lut, 1)
FIELD(alu_load_pwl_lut_global_mem, 1)
/* 7 */
FIELD(in_tile_list_address, 32)
/* 8 */
FIELD(in_tile_x_size, 16)
FIELD(in_tile_y_size, 16)
/* 9 */
FIELD(in_tile_x_inc, 16)
FIELD(in_tile_y_inc, 16)
/* 10 */
FIELD(in_image_base_address, 32)
/* 11 */
FIELD(alu_load_pwl_lut_address, 32)
/* 12 */
FIELD(out_tile_skip_at_border, 1)
FIELD(out_image_global_mem, 1)
FIELD(out_loop_1_reset, 1)
FIELD(out_loop_2_reset, 1)
FIELD(out_loop_3_reset, 1)
FIELD(out_brick_mode, 1)
FIELD(alu_z_filter_mode, 1)
FIELD(unused3, 1)
FIELD(in_window_z_start_overfetch, 2)
FIELD(unused4, 1)
FIELD(in_window_z_end_overfetch, 2)
FIELD(unused5, 1)
FIELD(alu_square_preshift, 4)
FIELD(in_image_data_type, 3)
FIELD(out_image_data_type, 3)
FIELD(unused6, 4)
FIELD(alu_pwl_sign_support, 1)
FIELD(alu_relu_enable, 1)
FIELD(no_flush, 1)
FIELD(last, 1)
/* 13 */
FIELD(out_image_base_address, 32)
/* 14 */
FIELD(out_loop_0_inc, 32)
/* 15 */
FIELD(out_loop_1_inc, 32)
/* 16 */
FIELD(out_loop_0_count, 16)
FIELD(out_loop_1_count, 16)
/* 17 */
FIELD(out_loop_2_inc, 32)
/* 18 */
FIELD(out_loop_3_inc, 32)
/* 19 */
FIELD(out_loop_2_count, 16)
FIELD(out_loop_3_count, 16)
/* 20 */
FIELD(out_loop_4_inc, 32)
/* 21 */
FIELD(out_loop_5_inc, 32)
/* 22 */
FIELD(out_loop_4_count, 16)
FIELD(out_loop_5_count, 16)
/* 23 */
FIELD(out_loop_6_inc, 32)
/* 24 */
FIELD(alu_filter_pwl_swap, 1)
FIELD(flat_rounding_mode, 2)
FIELD(integer_rounding_mode, 2)
FIELD(alu_input_preshift, 5)
FIELD(alu_output_postshift, 5)
FIELD(alu_reorder_bits_used, 4)
FIELD(alu_reorder_loop_2_mode, 1)
FIELD(unused7, 4)
FIELD(in_image_border_mode, 2)
FIELD(alu_output_postshift_5_6, 2)
FIELD(unused8, 4)
/* 25 */
FIELD(in_image_circular_buf_size, 32) /* >> 6 */
/* 26 */
FIELD(in_image_circular_buf_end_address_plus_1, 32) /* >> 6 */
/* 27 */
FIELD(out_image_circular_buf_size, 32) /* >> 6 */
/* 28 */
FIELD(out_image_circular_buf_end_address_plus_1, 32) /* >> 6 */
/* 29 */
FIELD(in_image_border_const, 16)
FIELD(coef_zp, 8)
FIELD(in_zp, 8)
/* 30 */
FIELD(out_zp, 8)
FIELD(alu_output_post_multiplier, 15)
FIELD(unused9, 9)
};
static void
set_default_tp_config(struct etna_tp_params *map)
{
map->unused0 = 0x0;
map->unused1 = 0x0;
map->in_window_x_start = 0x0;
map->in_window_y_start = 0x0;
map->in_tile_sequence = 0x0;
map->in_tile_global_mem = 0x0;
map->in_image_global_mem = 0x1;
map->alu_i2f_enable = 0x1;
map->alu_square_enable = 0x0;
map->alu_horz_processing = 0x0;
map->alu_horz_proc_count = 0x0;
map->alu_horz_proc_stride = 0x0;
map->alu_vert_processing = 0x0;
map->unused2 = 0x0;
map->alu_vert_proc_count = 0x0;
map->alu_vert_proc_stride = 0x0;
map->alu_nms_enable = 0x0;
map->alu_pwl_enable = 0x0;
map->alu_mult_enable = 0x0;
map->alu_f2i_enable = 0x1;
map->alu_load_pwl_lut = 0x0;
map->alu_load_pwl_lut_global_mem = 0x0;
map->in_tile_list_address = 0x0;
map->in_tile_x_size = 0x1;
map->in_tile_x_inc = 0x1;
map->alu_load_pwl_lut_address = 0x0;
map->out_tile_skip_at_border = 0x0;
map->out_image_global_mem = 0x1;
map->out_loop_1_reset = 0x0;
map->out_loop_2_reset = 0x0;
map->out_loop_3_reset = 0x0;
map->out_brick_mode = 0x0;
map->alu_z_filter_mode = 0x0;
map->unused3 = 0x0;
map->in_window_z_start_overfetch = 0x0;
map->unused4 = 0x0;
map->in_window_z_end_overfetch = 0x0;
map->unused5 = 0x0;
map->alu_square_preshift = 0x0;
map->in_image_data_type = 0x0;
map->out_image_data_type = 0x0;
map->unused6 = 0x0;
map->alu_pwl_sign_support = 0x0;
map->alu_relu_enable = 0x0;
map->no_flush = 0x0;
map->last = 0x1;
map->out_loop_0_inc = 0x1;
map->out_loop_3_inc = 0x0;
map->out_loop_3_count = 0x1;
map->out_loop_4_inc = 0x0;
map->out_loop_5_inc = 0x0;
map->out_loop_4_count = 0x1;
map->out_loop_5_count = 0x1;
map->out_loop_6_inc = 0x0;
map->alu_filter_pwl_swap = 0x0;
map->flat_rounding_mode = 0x1;
map->integer_rounding_mode = 0x1;
map->alu_input_preshift = 0x0;
map->alu_output_postshift = 0x0;
map->alu_reorder_bits_used = 0x0;
map->alu_reorder_loop_2_mode = 0x0;
map->unused7 = 0x0;
map->in_image_border_mode = 0x0;
map->alu_output_postshift_5_6 = 0x0;
map->unused8 = 0x0;
map->in_image_border_const = 0x0;
map->coef_zp = 0x0;
map->alu_output_post_multiplier = 0x0;
map->unused9 = 0x0;
}
static struct etna_bo *
create_transpose_config(struct etna_ml_subgraph *subgraph, const struct etna_operation *operation)
{
struct etna_context *ctx = etna_context(subgraph->base.context);
struct etna_bo *bo = etna_bo_new(ctx->screen->dev,
sizeof(struct etna_tp_params),
DRM_ETNA_GEM_CACHE_WC);
etna_bo_cpu_prep(bo, DRM_ETNA_PREP_WRITE);
struct etna_tp_params *map = etna_bo_map(bo);
set_default_tp_config(map);
map->in_image_x_size = operation->input_channels;
map->in_image_y_size = operation->input_height;
map->in_image_z_size = operation->input_width;
map->in_image_stride = operation->input_channels;
map->in_image_slice = operation->input_width * operation->input_channels;
map->in_window_x_end = operation->input_channels - 1;
map->in_window_y_end = operation->input_height - 1;
map->in_tile_y_size = operation->input_height;
map->in_tile_y_inc = operation->input_height;
struct pipe_resource *input = etna_ml_get_tensor(subgraph, operation->input_tensor);
map->in_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
unsigned offset = etna_ml_get_offset(subgraph, operation->output_tensor);
map->out_image_base_address = etna_bo_gpu_va(etna_resource(output)->bo) + offset;
map->out_loop_1_inc = operation->input_width * operation->input_height;
map->out_loop_0_count = operation->input_height;
map->out_loop_1_count = operation->input_channels;
map->out_loop_2_inc = operation->input_height;
map->out_loop_2_count = operation->input_width;
map->in_image_circular_buf_size = 0x0;
map->in_image_circular_buf_end_address_plus_1 = 0xFFFFFFFF >> 6;
map->out_image_circular_buf_size = 0x0;
map->out_image_circular_buf_end_address_plus_1 = 0xFFFFFFFF >> 6;
map->in_zp = operation->input_zero_point;
map->out_zp = operation->input_zero_point;
map->no_flush = 0x0;
etna_bo_cpu_fini(bo);
return bo;
}
static struct etna_bo *
create_detranspose_config(struct etna_ml_subgraph *subgraph, const struct etna_operation *operation)
{
struct etna_context *ctx = etna_context(subgraph->base.context);
unsigned input_width = operation->input_width;
unsigned input_height = operation->input_height;
unsigned input_channels = operation->input_channels;
struct etna_bo *bo = etna_bo_new(ctx->screen->dev,
sizeof(struct etna_tp_params),
DRM_ETNA_GEM_CACHE_WC);
etna_bo_cpu_prep(bo, DRM_ETNA_PREP_WRITE);
struct etna_tp_params *map = etna_bo_map(bo);
set_default_tp_config(map);
map->in_image_x_size = input_width;
map->in_image_y_size = input_height * input_channels;
map->in_image_z_size = 0x1;
map->in_image_stride = input_width;
map->in_image_slice = input_width * input_height * input_channels;
map->in_window_x_end = input_width - 1;
map->in_window_y_end = input_height * input_channels - 1;
map->in_tile_y_size = 0x1;
map->in_tile_y_inc = 0x1;
struct pipe_resource *input = etna_ml_get_tensor(subgraph, operation->input_tensor);
map->in_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
map->out_image_base_address = etna_bo_gpu_va(etna_resource(output)->bo);
map->out_loop_0_inc = input_channels;
map->out_loop_1_inc = 0x0;
map->out_loop_0_count = input_height;
map->out_loop_1_count = 0x1;
map->out_loop_2_inc = input_height * input_channels;
map->out_loop_2_count = input_width;
map->out_loop_3_inc = 0x1;
map->out_loop_3_count = input_channels;
map->out_loop_4_inc = input_width * input_height * input_channels;
map->in_image_circular_buf_size = 0x0;
map->in_image_circular_buf_end_address_plus_1 = 0xFFFFFFFF >> 6;
map->out_image_circular_buf_size = 0x0;
map->out_image_circular_buf_end_address_plus_1 = 0xFFFFFFFF >> 6;
map->in_zp = operation->input_zero_point;
map->out_zp = operation->input_zero_point;
etna_bo_cpu_fini(bo);
return bo;
}
static void
set_input_size(const struct etna_operation *operation, struct etna_tp_params *map, unsigned tp_cores_used)
{
map->in_image_x_size = operation->input_width;
if (operation->padding_same && operation->input_channels > 1) {
map->in_image_y_size = operation->input_height;
map->in_image_z_size = operation->input_channels / tp_cores_used;
} else if (operation->padding_same && operation->input_channels == 1) {
switch(operation->input_width) {
case 3:
case 5:
map->in_image_y_size = operation->input_height;
break;
case 8:
switch(operation->weight_width) {
case 3:
map->in_image_y_size = operation->input_height;
break;
case 5:
map->in_image_y_size = 5;
break;
}
break;
case 80:
case 112:
switch(operation->weight_width) {
case 3:
map->in_image_y_size = operation->input_height / tp_cores_used + 2;
break;
case 5:
map->in_image_y_size = operation->input_height / tp_cores_used + 1;
break;
}
break;
default:
unreachable("Unsupported input width");
}
map->in_image_z_size = operation->input_channels;
} else {
map->in_image_y_size = operation->input_height / tp_cores_used;
map->in_image_z_size = operation->input_channels;
}
}
static struct etna_bo *
create_reshuffle_config(struct etna_ml_subgraph *subgraph, const struct etna_operation *operation,
unsigned tp_core, unsigned tp_cores_used)
{
struct etna_context *ctx = etna_context(subgraph->base.context);
unsigned tp_core_count = ctx->screen->specs.tp_core_count;
struct etna_bo *bo = etna_bo_new(ctx->screen->dev,
sizeof(struct etna_tp_params),
DRM_ETNA_GEM_CACHE_WC);
etna_bo_cpu_prep(bo, DRM_ETNA_PREP_WRITE);
struct etna_tp_params *map = etna_bo_map(bo);
set_default_tp_config(map);
set_input_size(operation, map, tp_cores_used);
map->in_image_stride = operation->input_width;
map->in_image_slice = operation->input_width * operation->input_height;
if (operation->padding_same && (operation->weight_width == 5 || operation->input_width < 8)) {
if (operation->weight_width == 5 && operation->input_width < 8) {
map->in_window_x_start = 0xfffe;
map->in_window_y_start = 0xfffe;
} else {
map->in_window_x_start = 0xffff;
map->in_window_y_start = 0xffff;
}
} else {
map->in_window_x_start = 0x0;
map->in_window_y_start = 0x0;
}
map->in_window_x_end = operation->input_width - 1;
map->in_window_y_end = (operation->input_height / tp_cores_used) - 1;
map->in_tile_x_size = operation->input_width;
map->in_tile_x_inc = operation->input_width;
if (operation->input_width <= 8 && operation->input_channels == 1) {
map->in_tile_y_size = operation->input_height;
map->in_tile_y_inc = operation->input_height;
} else {
map->in_tile_y_size = operation->input_height / tp_cores_used;
map->in_tile_y_inc = operation->input_height / tp_cores_used;
}
if (operation->padding_same) {
switch(operation->weight_width) {
case 3:
map->in_window_x_end += 2;
if (operation->input_width < 8) {
map->in_tile_x_size += 3;
map->in_tile_y_size += 1;
map->in_tile_y_inc += 1;
} else {
map->in_tile_x_size += 2;
}
break;
case 5:
map->in_window_x_end += 3;
if (operation->input_width < 8) {
map->in_tile_x_size += 5;
} else {
map->in_tile_x_size += 4;
}
break;
default:
unreachable("Unsupported weight size");
}
if (operation->input_width <= 8 && operation->input_channels == 1 && operation->weight_width >= 5)
map->in_tile_x_size = operation->input_width / tp_cores_used + 2;
if (operation->input_width > 8 && operation->input_channels == 1) {
switch(operation->weight_width) {
case 3:
map->in_window_y_end = (operation->input_height / tp_cores_used) + 1;
break;
case 5:
map->in_window_y_end = (operation->input_height / tp_cores_used);
break;
default:
unreachable("Unsupported weight size");
}
} else
map->in_window_y_end = map->in_window_x_end;
map->in_tile_x_inc = map->in_tile_x_size;
if (operation->input_channels > 1) {
map->in_tile_y_size = map->in_tile_x_size;
map->in_tile_y_inc = map->in_tile_x_size;
} else {
map->in_tile_y_size += 2;
map->in_tile_y_inc += 2;
}
} else {
if (operation->input_width < 8) {
map->in_window_x_end += 1;
map->in_window_y_end += 1;
map->in_tile_x_size += 1;
map->in_tile_y_size += 1;
map->in_tile_x_inc += 1;
map->in_tile_y_inc += 1;
}
}
struct pipe_resource *input = etna_ml_get_tensor(subgraph, operation->input_tensor);
map->in_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo);
if (operation->padding_same)
map->in_image_base_address += ((operation->input_width * operation->input_height * operation->input_channels) / tp_cores_used) * tp_core;
else
map->in_image_base_address += (operation->input_width * (operation->input_height / tp_cores_used)) * tp_core;
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
map->out_image_base_address = etna_bo_gpu_va(etna_resource(output)->bo);
if (operation->padding_same)
map->out_image_base_address += ((map->in_tile_x_size * map->in_tile_y_size * operation->input_channels) / tp_cores_used) * tp_core;
else
map->out_image_base_address += ((operation->input_width * operation->input_width) / (operation->stride * operation->stride * tp_cores_used)) * tp_core;
map->out_loop_1_reset = 0x1;
map->out_loop_2_reset = 0x0;
map->out_loop_3_reset = 0x1;
map->out_loop_0_inc = pow(round(operation->input_width / 2.0), 2);
map->out_loop_1_inc = 0x1;
map->out_loop_0_count = 0x2;
map->out_loop_1_count = round(operation->input_width / 2.0);
map->out_loop_2_count = 0x2;
map->out_loop_3_count = DIV_ROUND_UP(round(operation->input_width / 2.0), tp_cores_used);
if (operation->padding_same) {
switch(operation->weight_width) {
case 3:
map->out_loop_0_inc = pow(round(operation->input_width / 2.0) + 1, 2);
map->out_loop_1_count += 1;
break;
case 5:
map->out_loop_0_inc = pow(round(operation->input_width / 2.0) + 2, 2);
map->out_loop_1_count += 2;
break;
default:
unreachable("Unsupported weight size");
}
if (operation->input_channels == 1)
map->out_loop_3_count += 1;
else
map->out_loop_3_count = map->out_loop_1_count;
}
map->out_loop_2_inc = map->out_loop_0_inc * 2;
map->out_loop_3_inc = map->out_loop_1_count;
map->out_loop_6_inc = map->out_loop_0_inc * 4;
if (operation->padding_same && tp_cores_used > 1 && operation->input_channels == 1) {
if (tp_core > 0) {
map->in_image_y_size -= 2;
map->in_window_y_end -= 2;
map->in_tile_y_size -= 2;
map->in_tile_y_inc -= 2;
map->out_loop_3_count -= 1;
}
if (tp_core == tp_core_count - 1) {
map->in_image_y_size -= 2;
}
if (tp_core > 0) {
map->in_image_base_address += operation->input_width * 2;
map->out_image_base_address -= (tp_core - 1) * (round(operation->input_width / 2.0) + 1);
}
}
unsigned alu_size = operation->input_width;
if (operation->padding_same) {
alu_size += 1;
if (operation->weight_width == 5)
alu_size += 1;
if (operation->input_width == 5)
alu_size += 1;
}
map->alu_reorder_bits_used = sizeof(alu_size) * 8 - __builtin_clz(alu_size);
map->in_zp = operation->input_zero_point;
map->out_zp = operation->input_zero_point;
if (tp_cores_used > 1)
map->no_flush = tp_core < tp_cores_used - 1;
map->in_image_circular_buf_size = 0x0;
map->in_image_circular_buf_end_address_plus_1 = 0xFFFFFFFF >> 6;
map->out_image_circular_buf_size = 0x0;
map->out_image_circular_buf_end_address_plus_1 = 0xFFFFFFFF >> 6;
if (map->in_image_y_size < 2) {
map->in_image_y_size = operation->input_width;
map->in_image_z_size = (operation->input_width * operation->input_height * operation->input_channels) / (map->in_image_x_size * map->in_image_y_size) / tp_cores_used;
map->in_window_y_end = operation->input_width;
map->in_tile_y_size = operation->input_width + 1;
map->in_tile_y_inc = operation->input_width + 1;
map->out_loop_3_count += 1;
map->in_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo);
map->in_image_base_address += ((operation->input_width * operation->input_height * operation->input_channels) / tp_cores_used) * tp_core;
map->out_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo);
map->out_image_base_address += ((map->in_tile_x_size * map->in_tile_y_size * operation->input_channels) / tp_cores_used) * tp_core;
}
etna_bo_cpu_fini(bo);
return bo;
}
void
etna_ml_lower_transpose(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *first_operation,
struct etna_operation *operation,
unsigned *output_tensor)
{
operation->type = ETNA_JOB_TYPE_TP;
operation->tp_type = ETNA_ML_TP_TRANSPOSE;
operation->input_tensor = first_operation->input_tensor->index;
operation->input_width = first_operation->input_tensor->dims[1];
operation->input_height = first_operation->input_tensor->dims[2];
operation->input_channels = first_operation->input_tensor->dims[3];
operation->input_zero_point = first_operation->input_tensor->zero_point;
operation->input_scale = first_operation->input_tensor->scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels;
*output_tensor = etna_ml_allocate_tensor(subgraph);
operation->output_tensor = *output_tensor;
operation->output_width = first_operation->input_tensor->dims[1];
operation->output_height = first_operation->input_tensor->dims[2];
operation->output_channels = first_operation->input_tensor->dims[3];
operation->output_zero_point = first_operation->input_tensor->zero_point;
operation->output_scale = first_operation->input_tensor->scale;
}
void
etna_ml_lower_detranspose(struct etna_ml_subgraph *subgraph,
struct etna_operation *convolution,
struct etna_operation *operation)
{
operation->type = ETNA_JOB_TYPE_TP;
operation->tp_type = ETNA_ML_TP_DETRANSPOSE;
operation->input_tensor = etna_ml_allocate_tensor(subgraph);
operation->input_width = convolution->output_width;
operation->input_height = convolution->output_height;
operation->input_channels = convolution->output_channels;
operation->input_zero_point = convolution->output_zero_point;
operation->input_scale = convolution->output_scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels;
operation->output_tensor = convolution->output_tensor;
operation->output_width = convolution->output_width;
operation->output_height = convolution->output_height;
operation->output_channels = convolution->output_channels;
operation->output_zero_point = convolution->output_zero_point;
operation->output_scale = convolution->output_scale;
}
void
etna_ml_lower_reshuffle(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *convolution,
struct etna_operation *operation,
unsigned *output_tensor)
{
operation->type = ETNA_JOB_TYPE_TP;
operation->tp_type = ETNA_ML_TP_RESHUFFLE;
operation->stride = convolution->conv.stride_x;
operation->padding_same = convolution->conv.padding_same;
operation->input_tensor = convolution->input_tensor->index;
operation->input_width = convolution->input_tensor->dims[1];
operation->input_height = convolution->input_tensor->dims[2];
operation->input_channels = convolution->input_tensor->dims[3];
operation->input_zero_point = convolution->input_tensor->zero_point;
operation->input_scale = convolution->input_tensor->scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels;
*output_tensor = etna_ml_allocate_tensor(subgraph);
operation->output_tensor = *output_tensor;
operation->output_width = DIV_ROUND_UP(operation->input_width, operation->stride);
operation->output_height = DIV_ROUND_UP(operation->input_height, operation->stride);
operation->output_channels = operation->input_channels * operation->stride * operation->stride;
operation->output_zero_point = convolution->input_tensor->zero_point;
operation->output_scale = convolution->input_tensor->scale;
/* When destriding a convolution, the transformation to be made to the input
* tensor will depend on the size of the weight tensor.
*/
operation->weight_width = convolution->conv.weight_tensor->dims[1];
operation->weight_height = convolution->conv.weight_tensor->dims[2];
if (operation->padding_same) {
if (operation->weight_width == 5) {
operation->output_width += 2;
operation->output_height += 2;
} else {
operation->output_width += 1;
operation->output_height += 1;
}
}
}
void
etna_ml_compile_operation_tp(struct etna_ml_subgraph *subgraph,
const struct etna_operation *operation,
struct etna_vip_instruction *instruction)
{
struct etna_context *ctx = etna_context(subgraph->base.context);
struct pipe_resource *input = etna_ml_get_tensor(subgraph, operation->input_tensor);
assert(input);
pipe_resource_reference(&instruction->input, input);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
assert(output);
pipe_resource_reference(&instruction->output, output);
switch (operation->tp_type) {
case ETNA_ML_TP_TRANSPOSE:
instruction->configs[0] = create_transpose_config(subgraph, operation);
break;
case ETNA_ML_TP_DETRANSPOSE:
instruction->configs[0] = create_detranspose_config(subgraph, operation);
break;
case ETNA_ML_TP_RESHUFFLE: {
unsigned tp_core_count = ctx->screen->specs.tp_core_count;
unsigned tp_cores_used;
tp_cores_used = (operation->input_width > 8 || operation->input_channels > 1) ? tp_core_count : 1;
/* TODO: Run among the 4 cores for faster performance */
if ((operation->input_width == 320 || operation->input_width == 224) &&
operation->input_channels == 3)
tp_cores_used = 1;
ML_DBG("reshuffle: input_width %d tp_cores_used %d\n", operation->input_width, tp_cores_used);
for (unsigned i = 0; i < tp_cores_used; i++) {
instruction->configs[i] = create_reshuffle_config(subgraph, operation, i, tp_cores_used);
}
break;
}
}
instruction->type = ETNA_JOB_TYPE_TP;
}
void
etna_ml_emit_operation_tp(struct etna_ml_subgraph *subgraph,
struct etna_vip_instruction *operation,
unsigned idx)
{
struct etna_context *ctx = etna_context(subgraph->base.context);
unsigned tp_core_count = ctx->screen->specs.tp_core_count;
struct etna_cmd_stream *stream = ctx->stream;
bool more_than_one_tp_job = operation->configs[1] != NULL;
bool parallel = !DBG_ENABLED(ETNA_DBG_NPU_NO_PARALLEL);
for (unsigned j = 0; j < tp_core_count && operation->configs[j]; j++) {
unsigned offset = parallel ? idx + 1 : 0;
if (more_than_one_tp_job && (j < tp_core_count - 1))
offset = parallel ? 0x1f : 0x1;
etna_set_state(stream, VIVS_GL_OCB_REMAP_START, 0x0);
etna_set_state(stream, VIVS_GL_OCB_REMAP_END, 0x0);
etna_set_state(stream, VIVS_GL_TP_CONFIG, 0x0);
etna_set_state_reloc(stream, VIVS_PS_TP_INST_ADDR, &(struct etna_reloc) {
.bo = operation->configs[j],
.flags = ETNA_RELOC_READ,
.offset = offset,
});
}
etna_set_state(stream, VIVS_PS_UNK10A4, parallel ? idx + 1 : 0x0);
}
src/gallium/drivers/etnaviv/etnaviv_ml_tp.h
+33
View File
@@ -0,0 +1,33 @@
/*
* Copyright (c) 2023-2024 Tomeu Vizoso <tomeu@tomeuvizoso.net>
* SPDX-License-Identifier: MIT
*/
#include "etnaviv_ml.h"
void
etna_ml_lower_transpose(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *first_operation,
struct etna_operation *operation,
unsigned *output_tensor);
void
etna_ml_lower_detranspose(struct etna_ml_subgraph *subgraph,
struct etna_operation *convolution,
struct etna_operation *operation);
void
etna_ml_lower_reshuffle(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *first_operation,
struct etna_operation *operation,
unsigned *output_tensor);
void
etna_ml_compile_operation_tp(struct etna_ml_subgraph *subgraph,
const struct etna_operation *operation,
struct etna_vip_instruction *instruction);
void
etna_ml_emit_operation_tp(struct etna_ml_subgraph *subgraph,
struct etna_vip_instruction *operation,
unsigned idx);
src/gallium/drivers/etnaviv/meson.build
+2
View File
@@ -61,6 +61,8 @@ files_etnaviv = files(
'etnaviv_ml.h',
'etnaviv_ml_nn.c',
'etnaviv_ml_nn.h',
'etnaviv_ml_tp.c',
'etnaviv_ml_tp.h',
'etnaviv_nir_lower_source_mods.c',
'etnaviv_nir_lower_texture.c',
'etnaviv_nir_lower_ubo_to_uniform.c',