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llama.cpp/ggml/src/ggml-vulkan/vulkan-shaders/group_norm.comp
T
AclyandJeff Bolz e29acf74fe vulkan : incremental shader builds (#16341)
* vulkan (DRAFT): split shader generation by GLSL source file, to improve incremental build times

* support dep-files so shaders are recompiled if their included files change

* rename shader files which are used as "headers" to use .glsl extension
* move glslc extension detection shaders to separate folders
* the above is to prevent them from getting glob'd with the actual compute shaders that need to be compiled

* vulkan : only write embedded shader .hpp/.cpp when they change

* avoid recompiling ggml-vulkan.cpp when editing shaders
* pass single --source argument instead of --input-dir & --filter to shader gen
* check for source file match earlier

* fix hang in vulkan-shaders-gen when there are compilation errors

* early out did not decrement compile_count

* clean up

* fix glslc integer dot product test

* unconditionally write the embedded shader cpp output

* replace output filepath in generated dep-files to match output in CMakeLists

---------

Co-authored-by: Jeff Bolz <jbolz@nvidia.com>
2025-10-04 11:42:56 +02:00

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#version 450
#include "generic_head.glsl"
#include "types.glsl"
#extension GL_EXT_control_flow_attributes : enable
#define BLOCK_SIZE 512
layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
layout (binding = 1) writeonly buffer D {D_TYPE data_d[];};
shared float tmp[BLOCK_SIZE];
void main() {
const uint group_size = p.KX;
const float eps = p.param1;
const uint tid = gl_LocalInvocationID.x;
const uint start = gl_WorkGroupID.x * group_size + tid;
const uint end = (gl_WorkGroupID.x + 1) * group_size;
tmp[tid] = 0.0f;
// Calculate mean
[[unroll]] for (uint col = start; col < end; col += BLOCK_SIZE) {
tmp[tid] += float(data_a[col]);
}
// tmp up partial tmps and write back result
barrier();
[[unroll]] for (int s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
if (tid < s) {
tmp[tid] += tmp[tid + s];
}
barrier();
}
const float mean = tmp[0] / group_size;
barrier();
tmp[tid] = 0.0f;
// Calculate variance
[[unroll]] for (uint col = start; col < end; col += BLOCK_SIZE) {
const float xi = float(data_a[col]) - mean;
data_d[col] = D_TYPE(xi);
tmp[tid] += xi * xi;
}
// sum up partial sums and write back result
barrier();
[[unroll]] for (int s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
if (tid < s) {
tmp[tid] += tmp[tid + s];
}
barrier();
}
const float variance = tmp[0] / group_size;
const float scale = inversesqrt(variance + eps);
[[unroll]] for (uint col = start; col < end; col += BLOCK_SIZE) {
data_d[col] *= D_TYPE(scale);
}
}