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* vulkan: implement GGML_OP_ROPE_BACK * vulkan: implement GGML_OP_RMS_NORM_BACK * vulkan: implement GGML_OP_SILU_BACK * vulkan: implement GGML_OP_SOFTMAX_BACK
56 lines
1.8 KiB
Plaintext
56 lines
1.8 KiB
Plaintext
#version 450
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#include "generic_head.comp"
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#include "types.comp"
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#extension GL_EXT_control_flow_attributes : enable
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#define BLOCK_SIZE 512
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layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
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layout (binding = 0) readonly buffer G {A_TYPE data_a[];};
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layout (binding = 1) readonly buffer X {B_TYPE data_b[];};
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layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};
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shared FLOAT_TYPE sum_xx[BLOCK_SIZE];
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shared FLOAT_TYPE sum_xg[BLOCK_SIZE];
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void main() {
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const uint row = gl_WorkGroupID.z * 262144 + gl_WorkGroupID.y * 512 + gl_WorkGroupID.x;
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const uint tid = gl_LocalInvocationID.x;
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// Compute derivative of x[i]/norm(x) = g[i]/norm(x) - x[i] dot(x,g)/KX / norm(x)^1.5
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// partial sums for thread in warp
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sum_xx[tid] = FLOAT_TYPE(0.0f);
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sum_xg[tid] = FLOAT_TYPE(0.0f);
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[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
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const FLOAT_TYPE gi = FLOAT_TYPE(data_a[row*p.KX + col]);
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const FLOAT_TYPE xi = FLOAT_TYPE(data_b[row*p.KX + col]);
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sum_xx[tid] += xi * xi;
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sum_xg[tid] += xi * gi;
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}
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// sum up partial sums and write back result
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barrier();
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[[unroll]] for (int s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
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if (tid < s) {
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sum_xx[tid] += sum_xx[tid + s];
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sum_xg[tid] += sum_xg[tid + s];
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}
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barrier();
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}
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const FLOAT_TYPE eps = FLOAT_TYPE(p.param1);
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const FLOAT_TYPE mean = sum_xx[0] / FLOAT_TYPE(p.KX);
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const FLOAT_TYPE scale_g = inversesqrt(mean + eps);
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const FLOAT_TYPE scale_x = -scale_g * sum_xg[0] / (sum_xx[0] + FLOAT_TYPE(p.KX) * eps);
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[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
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data_d[row*p.KX + col] = D_TYPE(
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scale_g * FLOAT_TYPE(data_a[row*p.KX + col]) +
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scale_x * FLOAT_TYPE(data_b[row*p.KX + col]));
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}
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}
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