mirror of
https://github.com/ggerganov/llama.cpp.git
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7c7836d9d4
* Refactor shaders, extract GLSL code from ggml_vk_generate_shaders.py into vulkan-shaders directory * Improve debug log code * Add memory debug output option * Fix flake8 * Fix unnecessary high llama-3 VRAM use
67 lines
4.3 KiB
Plaintext
67 lines
4.3 KiB
Plaintext
#version 450
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#include "mul_mat_vec_base.comp"
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layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in;
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shared FLOAT_TYPE tmp[32];
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void main() {
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const uint row = gl_WorkGroupID.x;
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uint a_offset, b_offset, d_offset;
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get_offsets(a_offset, b_offset, d_offset);
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const uint num_blocks_per_row = p.ncols / QUANT_K;
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const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row;
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const uint tid = gl_LocalInvocationID.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16
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const uint ix = gl_LocalInvocationID.x%K_QUANTS_PER_ITERATION; // 0 or 0, 1
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const uint step = 16/K_QUANTS_PER_ITERATION; // 16 or 8
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const uint v_im = tid/step; // 0 or 1. 0 computes 0..., 1 computes 128...
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const uint v_in = tid - step*v_im; // 0...15 or 0...7
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const uint8_t m = uint8_t(1 << (4 * v_im));
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const uint l0 = K_QUANTS_PER_ITERATION*v_in; // 0...15
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const uint q_offset = 32*v_im + l0;
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const uint y_offset = 128*v_im + l0;
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tmp[16 * ix + tid] = FLOAT_TYPE(0.0); // partial sum for thread in warp
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const uint s_shift = 4 * v_im;
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[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
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const uint y_idx = i * QUANT_K + y_offset;
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const FLOAT_TYPE d = FLOAT_TYPE(data_a[ib0 + i].d);
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FLOAT_TYPE sum = FLOAT_TYPE(0.0);
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for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
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sum += FLOAT_TYPE(data_b[b_offset + y_idx + l + 0]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[0] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 8] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] ) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 0)) != 0) ? 0 : 4))
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+ FLOAT_TYPE(data_b[b_offset + y_idx + l + 32]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[2] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[10] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 2) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 1)) != 0) ? 0 : 4))
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+ FLOAT_TYPE(data_b[b_offset + y_idx + l + 64]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[4] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 8] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 4) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 2)) != 0) ? 0 : 4))
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+ FLOAT_TYPE(data_b[b_offset + y_idx + l + 96]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[6] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[10] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 6) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 3)) != 0) ? 0 : 4))
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+ FLOAT_TYPE(data_b[b_offset + y_idx + l + 16]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[1] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 9] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] ) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 0)) != 0) ? 0 : 4))
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+ FLOAT_TYPE(data_b[b_offset + y_idx + l + 48]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[3] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[11] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 2) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 1)) != 0) ? 0 : 4))
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+ FLOAT_TYPE(data_b[b_offset + y_idx + l + 80]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[5] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 9] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 4) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 2)) != 0) ? 0 : 4))
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+ FLOAT_TYPE(data_b[b_offset + y_idx + l +112]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[7] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[11] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 6) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 3)) != 0) ? 0 : 4));
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}
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tmp[16 * ix + tid] += d * sum;
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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 (uint s = 16; s > 0; s >>= 1) {
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if (tid < s) {
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tmp[tid] += tmp[tid + s];
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}
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barrier();
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}
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if (tid == 0) {
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data_d[d_offset + row] = D_TYPE(tmp[0]);
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}
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}
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