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[ET-VK] Tuning local workgroup size calculation for conv2d pw to improve performance. #11188

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91 changes: 54 additions & 37 deletions backends/vulkan/runtime/graph/ops/glsl/conv2d_pw.glsl
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@

#define TILE_SIZE_X ${TILE_SIZE_X}
#define TILE_SIZE_Y ${TILE_SIZE_Y}
#define LOCAL_WG_SIZE 64

#define op(X, A, B) ${OPERATOR}

Expand All @@ -39,10 +38,7 @@ layout(push_constant) uniform restrict Block {

layout(local_size_x_id = 0, local_size_y_id = 1, local_size_z_id = 2) in;

// For performance improvement, reduce register usage by caching positions in shared memory.
// Offset index by 1 every 16 points to avoid bank access conflict.
#define offset_pos_index(index) (index + ((index) >> 4))
shared ivec3 pos_shared[offset_pos_index(LOCAL_WG_SIZE * TILE_SIZE_X * TILE_SIZE_Y)];
#extension GL_EXT_control_flow_attributes : require

/*
* Computes a 2D pointwise convolution of an NxN output tile. Calculating an
Expand All @@ -51,47 +47,55 @@ shared ivec3 pos_shared[offset_pos_index(LOCAL_WG_SIZE * TILE_SIZE_X * TILE_SIZE
*/
void main() {
const ivec2 out_limits_scaled = (out_limits.xy + ivec2(TILE_SIZE_X - 1, TILE_SIZE_Y - 1)) / ivec2(TILE_SIZE_X, TILE_SIZE_Y);
const uint shared_mem_stride = LOCAL_WG_SIZE;

const uint div_by_x = gl_GlobalInvocationID.x / out_limits_scaled.x;
const ivec3 gpos = ivec3(
gl_GlobalInvocationID.x % out_limits_scaled.x,
div_by_x % out_limits_scaled.y,
div_by_x / out_limits_scaled.y);
div_by_x,
gl_GlobalInvocationID.y);

// If the top left position is out of bounds, then this invocation will have
// no work to do.
if (gpos.y >= out_limits_scaled.y || gpos.z >= out_limits.z) {
return;
}

// Output position for TILE_SIZE = 2
// +--------+--------+
// | pos[0] | pos[1] |
// +--------+--------+
// | pos[2] | pos[3] |
// +--------+--------+
ivec2 pos[TILE_SIZE_X * TILE_SIZE_Y];
int pos[TILE_SIZE_X * TILE_SIZE_Y * 2];
for (int y = 0, i = 0; y < TILE_SIZE_Y; ++y) {
for (int x = 0; x < TILE_SIZE_X; ++x) {
pos[i] = ivec2(gpos.x * TILE_SIZE_X + x, gpos.y * TILE_SIZE_Y + y);
pos_shared[offset_pos_index((shared_mem_stride * i) + gl_LocalInvocationIndex)] = ivec3(pos[i], gpos.z);
pos[i * 2] = gpos.x * TILE_SIZE_X + x;
pos[i * 2 + 1] = gpos.y * TILE_SIZE_Y + y;
i++;
}
}

// If the top left position is out of bounds, then this invocation will have
// no work to do.
if (gpos.z >= out_limits.z) {
return;
}

// Compute the index of the input texture that needs to be loaded for each
// output position. Note that negative indices can be produced indicating that
// the top-left element is in a region added by padding.
ivec2 ipos[TILE_SIZE_X * TILE_SIZE_Y];
int ipos[TILE_SIZE_X * TILE_SIZE_Y * 2];
for (int i = 0; i < TILE_SIZE_X * TILE_SIZE_Y; ++i) {
ipos[i] = pos[i] * stride - padding;
ipos[i * 2] = pos[i * 2] * stride.x - padding.x;
ipos[i * 2 + 1] = pos[i * 2 + 1] * stride.y - padding.y;
}

vec4 sum[TILE_SIZE_X * TILE_SIZE_Y];
sum[0] = texelFetch(t_bias, ivec2(gpos.z, 0), 0);
for (int i = 1; i < TILE_SIZE_X * TILE_SIZE_Y; ++i) {
sum[i] = sum[0];
// Final output array where each element is a tensor value.
// Tuple of consecutive 4 elements represents a single output texel.
float sum[TILE_SIZE_X * TILE_SIZE_Y * 4];

const vec4 bias = texelFetch(t_bias, ivec2(gpos.z, 0), 0);

// Initialize the output array with the bias value
for (int i = 0; i < TILE_SIZE_X * TILE_SIZE_Y * 4; i += 4) {
sum[i] = bias.x;
sum[i + 1] = bias.y;
sum[i + 2] = bias.z;
sum[i + 3] = bias.w;
}

int z4 = 0;
Expand All @@ -100,14 +104,26 @@ void main() {
// During prepacking, the weight tensor has been permuted so that the
// channel (IC) dim is along the x-axis, and the batch (OC) dim is along
// the z-axis.
const vec4 ktex_0 = texelFetchOffset(t_kernel, ivec2(z, gpos.z), 0, ivec2(0, 0));
const vec4 ktex_1 = texelFetchOffset(t_kernel, ivec2(z, gpos.z), 0, ivec2(1, 0));
const vec4 ktex_2 = texelFetchOffset(t_kernel, ivec2(z, gpos.z), 0, ivec2(2, 0));
const vec4 ktex_3 = texelFetchOffset(t_kernel, ivec2(z, gpos.z), 0, ivec2(3, 0));
float kernel_values[4 * 4]; // 4 channels, 4 elements per channel

// Load kernel values from texels to array
[[unroll]] for (int i = 0; i < 4; ++i) {
const vec4 k_tex = texelFetch(t_kernel, ivec2(z + i, gpos.z), 0);
kernel_values[i * 4 + 0] = k_tex.x;
kernel_values[i * 4 + 1] = k_tex.y;
kernel_values[i * 4 + 2] = k_tex.z;
kernel_values[i * 4 + 3] = k_tex.w;
}

#pragma unroll
for (int i = 0; i < TILE_SIZE_X * TILE_SIZE_Y; ++i) {
const vec4 in_tex = texelFetch(t_in, ivec3(ipos[i], z4), 0);
const vec4 in_tex = texelFetch(t_in, ivec3(ipos[i * 2], ipos[i * 2 + 1], z4), 0);
// Load the input texel into an array
float tex_values[4];
tex_values[0] = in_tex.x;
tex_values[1] = in_tex.y;
tex_values[2] = in_tex.z;
tex_values[3] = in_tex.w;

// For 2x2 tile size algorithm works as follows.
// To explain the calculations below, the contents of one in_tex and the
// group of 4 texels loaded from t_kernel are shown:
Expand Down Expand Up @@ -141,18 +157,19 @@ void main() {
//
// which is what is expressed in the following calculations. This is done
// for each output position.
sum[i] = fma(in_tex.xxxx, ktex_0, sum[i]);
sum[i] = fma(in_tex.yyyy, ktex_1, sum[i]);
sum[i] = fma(in_tex.zzzz, ktex_2, sum[i]);
sum[i] = fma(in_tex.wwww, ktex_3, sum[i]);
for (int j = 0; j < 4; ++j) {
sum[i * 4 + j] = tex_values[0] * kernel_values[0 + j] + sum[i * 4 + j];
sum[i * 4 + j] = tex_values[1] * kernel_values[4 + j] + sum[i * 4 + j];
sum[i * 4 + j] = tex_values[2] * kernel_values[8 + j] + sum[i * 4 + j];
sum[i * 4 + j] = tex_values[3] * kernel_values[12 + j] + sum[i * 4 + j];
}
}
}

for (int i = 0; i < TILE_SIZE_X * TILE_SIZE_Y; ++i) {
const uint index = (shared_mem_stride * i) + gl_LocalInvocationIndex;
const ivec3 pos = pos_shared[offset_pos_index(index)];
if (all(lessThan(pos, out_limits.xyz))) {
imageStore(t_out, pos, op(sum[i], out_min, out_max));
const ivec3 pos_l = ivec3(pos[i * 2], pos[i * 2 + 1], gpos.z);
if (all(lessThan(pos_l, out_limits.xyz))) {
imageStore(t_out, pos_l, op(vec4(sum[i * 4], sum[i * 4 + 1], sum[i * 4 + 2], sum[i * 4 + 3]), out_min, out_max));
}
}
}
4 changes: 2 additions & 2 deletions backends/vulkan/runtime/graph/ops/glsl/conv2d_pw.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,8 @@ conv2d_pw:
OPERATOR: X
NDIM: 3
DTYPE: float
TILE_SIZE_X: 2
TILE_SIZE_Y: 2
TILE_SIZE_X: 1
TILE_SIZE_Y: 4
generate_variant_forall:
DTYPE:
- VALUE: half
Expand Down
25 changes: 21 additions & 4 deletions backends/vulkan/runtime/graph/ops/impl/Convolution.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -305,8 +305,8 @@ utils::uvec3 create_conv2d_global_wg_size(
if (method == Conv2dMethod::Pointwise) {
const utils::uvec3 image_extents = graph.logical_limits_of(out);
return {
utils::div_up(image_extents[0u], 2u),
utils::div_up(image_extents[1u], 2u),
utils::div_up(image_extents[0u], 1u),
utils::div_up(image_extents[1u], 4u),
image_extents[2u]};
} else if (method == Conv2dMethod::Depthwise && stride_equals_dilation) {
const utils::uvec3 image_extents = graph.create_global_wg_size(out);
Expand Down Expand Up @@ -398,8 +398,25 @@ void add_conv2d_node(
utils::uvec3 wg_size = create_conv2d_global_wg_size(
graph, method, out, weight_data, stride_equals_dilation);

if (method == Conv2dMethod::Pointwise || method == Conv2dMethod::Depthwise) {
if (method == Conv2dMethod::Depthwise) {
wg_size = {wg_size[0] * wg_size[1] * wg_size[2], 1, 1};
} else if (method == Conv2dMethod::Pointwise) {
wg_size = {wg_size[0] * wg_size[1], wg_size[2], 1};
}

utils::uvec3 local_wg_size;
if (method == Conv2dMethod::Pointwise) {
uint32_t local_wg_size_y = 1;
if (wg_size[1] % 8 == 0) {
local_wg_size_y = 8;
} else if (wg_size[1] % 4 == 0) {
local_wg_size_y = 4;
} else if (wg_size[1] % 2 == 0) {
local_wg_size_y = 2;
}
local_wg_size = {64 / local_wg_size_y, local_wg_size_y, 1};
} else {
local_wg_size = graph.create_local_wg_size(wg_size);
}

vkapi::ParamsBindList param_buffers;
Expand Down Expand Up @@ -462,7 +479,7 @@ void add_conv2d_node(
graph,
shader,
wg_size,
graph.create_local_wg_size(wg_size),
local_wg_size,
// Inputs and Outputs
{{out, vkapi::kWrite}, {{in, arg_weight, arg_bias}, vkapi::kRead}},
// Shader params buffers
Expand Down
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