diff options
author | Kawrakow <48489457+ikawrakow@users.noreply.github.com> | 2024-07-27 07:55:01 +0200 |
---|---|---|
committer | GitHub <noreply@github.com> | 2024-07-27 07:55:01 +0200 |
commit | 154e0d75fccf1784fe9ff6fd76a630b66563da3d (patch) | |
tree | 81ce6dbb5b1900c1aa78a879f0593c694cab9d27 /ggml/src/vulkan-shaders/norm.comp | |
parent | 0684c3e9c70d49323b4fc517128cbe222cab7f96 (diff) |
Merge mainline llama.cpp (#3)
* Merging mainline - WIP
* Merging mainline - WIP
AVX2 and CUDA appear to work.
CUDA performance seems slightly (~1-2%) lower as it is so often
the case with llama.cpp/ggml after some "improvements" have been made.
* Merging mainline - fix Metal
* Remove check
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Diffstat (limited to 'ggml/src/vulkan-shaders/norm.comp')
-rw-r--r-- | ggml/src/vulkan-shaders/norm.comp | 44 |
1 files changed, 44 insertions, 0 deletions
diff --git a/ggml/src/vulkan-shaders/norm.comp b/ggml/src/vulkan-shaders/norm.comp new file mode 100644 index 00000000..803dbdcb --- /dev/null +++ b/ggml/src/vulkan-shaders/norm.comp @@ -0,0 +1,44 @@ +#version 450 + +#include "generic_head.comp" +#include "types.comp" + +#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 vec2 sum[BLOCK_SIZE]; + +void main() { + const uint row = gl_WorkGroupID.x; + const uint tid = gl_LocalInvocationID.x; + + sum[tid] = vec2(0.0f, 0.0f); + + [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) { + const float xi = float(data_a[row*p.KX + col]); + sum[tid].x += xi; + sum[tid].y += 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) { + sum[tid] += sum[tid + s]; + } + barrier(); + } + + const float mean = sum[0].x / p.KX; + const float var = sum[0].y / p.KX - mean * mean; + const float inv_std = inversesqrt(var + p.param1); + + [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) { + data_d[row*p.KX + col] = D_TYPE((float(data_a[row*p.KX + col]) - mean) * inv_std); + } +} |