mirror of
https://github.com/RYDE-WORK/llama.cpp.git
synced 2026-01-28 11:03:14 +08:00
716bd6dec3
Make the mul_mat_vec shaders support N>1 (as a spec constant, NUM_COLS) where the batch_strides are overloaded to hold the row strides. Put the loads from the B matrix in the innermost loop because it should cache better. Share some code for reducing the result values to memory in mul_mat_vec_base.
134 lines
6.3 KiB
Plaintext
134 lines
6.3 KiB
Plaintext
#version 450
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#extension GL_EXT_shader_explicit_arithmetic_types : require
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#include "mul_mat_vec_base.comp"
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layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
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void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
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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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// 16 threads are used to process each block
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const uint it_size = gl_WorkGroupSize.x/16;
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const uint tid = gl_LocalInvocationID.x;
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const uint itid = tid%16; // 0...16
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const uint ix = tid/16;
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const uint step = 4;
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const uint il = itid/step; // 0...3
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const uint ir = itid - step*il; // 0...7 or 0...3
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const uint n = 4;
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const uint v_im = il / 2; // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224
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const uint v_in = il % 2;
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const uint l0 = n * (2 * ir + v_in); // 0...15
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const uint q_offset = 32*v_im + l0;
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const uint y_offset = 64*v_im + l0;
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FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
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[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
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[[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
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temp[j][i] = FLOAT_TYPE(0);
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}
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}
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[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += it_size) {
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const uint y1_idx = i * QUANT_K + y_offset;
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const uint y2_idx = y1_idx + 128;
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[[unroll]] for (uint n = 0; n < num_rows; ++n) {
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const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
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f16vec2 d = data_a[ib0 + i].d;
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const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
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const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
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uint32_t scale0_u32 = data_a_packed16[ib0 + i].scales[v_im ];
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uint32_t scale4_u32 = data_a_packed16[ib0 + i].scales[v_im + 2];
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uint32_t scale8_u32 = data_a_packed16[ib0 + i].scales[v_im + 4];
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uvec4 scale0 = uvec4(unpack8(scale0_u32));
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uvec4 scale4 = uvec4(unpack8(scale4_u32));
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uvec4 scale8 = uvec4(unpack8(scale8_u32));
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const uint32_t sc0 = ( scale0.x & 0x3f);
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const uint32_t sc1 = ( scale0.y & 0x3f);
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const uint32_t sc2 = ( scale4.x & 0x3f);
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const uint32_t sc3 = ( scale4.y & 0x3f);
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const uint32_t sc4 = (( scale8.x & 0x0f) | ((scale0.x & 0xc0) >> 2));
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const uint32_t sc5 = (( scale8.y & 0x0f) | ((scale0.y & 0xc0) >> 2));
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const uint32_t sc6 = (((scale8.x >> 4) & 0x0f) | ((scale4.x & 0xc0) >> 2));
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const uint32_t sc7 = (((scale8.y >> 4) & 0x0f) | ((scale4.y & 0xc0) >> 2));
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uint32_t qs0_u32 = data_a_packed32[ib0 + i].qs[q_offset / 4];
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uint32_t qs64_u32 = data_a_packed32[ib0 + i].qs[q_offset / 4 + 16];
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uint32_t qs0_u32_lo4 = qs0_u32 & 0x0F0F0F0F;
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uint32_t qs0_u32_hi4 = (qs0_u32 >> 4) & 0x0F0F0F0F;
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uint32_t qs64_u32_lo4 = qs64_u32 & 0x0F0F0F0F;
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uint32_t qs64_u32_hi4 = (qs64_u32 >> 4) & 0x0F0F0F0F;
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uvec4 qs0_lo4 = uvec4(unpack8(qs0_u32_lo4));
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uvec4 qs64_lo4 = uvec4(unpack8(qs64_u32_lo4));
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uvec4 qs0_hi4 = uvec4(unpack8(qs0_u32_hi4));
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uvec4 qs64_hi4 = uvec4(unpack8(qs64_u32_hi4));
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const uint32_t q4_0 = qs0_lo4.x;
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const uint32_t q4_1 = qs0_lo4.y;
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const uint32_t q4_2 = qs0_lo4.z;
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const uint32_t q4_3 = qs0_lo4.w;
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const uint32_t q4_4 = qs0_hi4.x;
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const uint32_t q4_5 = qs0_hi4.y;
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const uint32_t q4_6 = qs0_hi4.z;
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const uint32_t q4_7 = qs0_hi4.w;
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const uint32_t q4_8 = qs64_lo4.x;
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const uint32_t q4_9 = qs64_lo4.y;
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const uint32_t q4_10 = qs64_lo4.z;
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const uint32_t q4_11 = qs64_lo4.w;
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const uint32_t q4_12 = qs64_hi4.x;
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const uint32_t q4_13 = qs64_hi4.y;
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const uint32_t q4_14 = qs64_hi4.z;
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const uint32_t q4_15 = qs64_hi4.w;
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[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
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B_TYPE_VEC4 by10 = data_b_v4[(j*p.batch_stride_b + b_offset + y1_idx) / 4];
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B_TYPE_VEC4 by132 = data_b_v4[(j*p.batch_stride_b + b_offset + y1_idx) / 4 + 8];
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B_TYPE_VEC4 by20 = data_b_v4[(j*p.batch_stride_b + b_offset + y2_idx) / 4];
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B_TYPE_VEC4 by232 = data_b_v4[(j*p.batch_stride_b + b_offset + y2_idx) / 4 + 8];
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const FLOAT_TYPE sx = fma(FLOAT_TYPE(by10.x), q4_0, fma(FLOAT_TYPE(by10.y), q4_1, fma(FLOAT_TYPE(by10.z), q4_2, FLOAT_TYPE(by10.w) * q4_3)));
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const FLOAT_TYPE sy = fma(FLOAT_TYPE(by132.x), q4_4, fma(FLOAT_TYPE(by132.y), q4_5, fma(FLOAT_TYPE(by132.z), q4_6, FLOAT_TYPE(by132.w) * q4_7)));
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const FLOAT_TYPE sz = fma(FLOAT_TYPE(by20.x), q4_8, fma(FLOAT_TYPE(by20.y), q4_9, fma(FLOAT_TYPE(by20.z), q4_10, FLOAT_TYPE(by20.w) * q4_11)));
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const FLOAT_TYPE sw = fma(FLOAT_TYPE(by232.x), q4_12, fma(FLOAT_TYPE(by232.y), q4_13, fma(FLOAT_TYPE(by232.z), q4_14, FLOAT_TYPE(by232.w) * q4_15)));
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const FLOAT_TYPE smin =
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fma(FLOAT_TYPE(by10.x), sc2, fma(FLOAT_TYPE(by132.x), sc3, fma(FLOAT_TYPE(by20.x), sc6, fma(FLOAT_TYPE(by232.x), sc7,
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fma(FLOAT_TYPE(by10.y), sc2, fma(FLOAT_TYPE(by132.y), sc3, fma(FLOAT_TYPE(by20.y), sc6, fma(FLOAT_TYPE(by232.y), sc7,
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fma(FLOAT_TYPE(by10.z), sc2, fma(FLOAT_TYPE(by132.z), sc3, fma(FLOAT_TYPE(by20.z), sc6, fma(FLOAT_TYPE(by232.z), sc7,
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fma(FLOAT_TYPE(by10.w), sc2, fma(FLOAT_TYPE(by132.w), sc3, fma(FLOAT_TYPE(by20.w), sc6, FLOAT_TYPE(by232.w) * sc7)))))))))))))));
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temp[j][n] = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp[j][n]));
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}
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}
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}
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reduce_result(temp, d_offset, first_row, num_rows, tid);
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}
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void main() {
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const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
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// do NUM_ROWS at a time, unless there aren't enough remaining rows
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if (first_row + NUM_ROWS <= p.stride_d) {
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compute_outputs(first_row, NUM_ROWS);
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} else {
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if (first_row >= p.stride_d) {
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return;
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}
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compute_outputs(first_row, p.stride_d - first_row);
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}
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}
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