mirror of
https://github.com/RYDE-WORK/llama.cpp.git
synced 2026-01-31 04:33:15 +08:00
Compute two result elements per workgroup (for Q{4,5}_{0,1}). This reuses
the B loads across the rows and also reuses some addressing calculations.
This required manually partially unrolling the loop, since the compiler
is less willing to unroll outer loops.
Add bounds-checking on the last iteration of the loop. I think this was at
least partly broken before.
Optimize the Q4_K shader to vectorize most loads and reduce the number of
bit twiddling instructions.
144 lines
6.2 KiB
Plaintext
144 lines
6.2 KiB
Plaintext
#version 450
|
|
|
|
#extension GL_EXT_shader_explicit_arithmetic_types : require
|
|
|
|
#include "mul_mat_vec_base.comp"
|
|
|
|
layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in;
|
|
|
|
shared FLOAT_TYPE tmp[32];
|
|
|
|
// Declare aliased versions of A and B bindings that can use 16b/32b loads for
|
|
// the quantized values, and vec4 loads for B.
|
|
struct block_q4_K_u32
|
|
{
|
|
f16vec2 d;
|
|
uint32_t scales[3*QUANT_K/64/4];
|
|
uint32_t qs[QUANT_K/2/4];
|
|
};
|
|
|
|
struct block_q4_K_u16
|
|
{
|
|
f16vec2 d;
|
|
uint16_t scales[3*QUANT_K/64/2];
|
|
uint16_t qs[QUANT_K/2/2];
|
|
};
|
|
|
|
layout (binding = 0) readonly buffer A_u32 {block_q4_K_u32 data_a_u32[];};
|
|
layout (binding = 0) readonly buffer A_u16 {block_q4_K_u16 data_a_u16[];};
|
|
layout (binding = 1) readonly buffer BV4 {B_TYPE_VEC4 data_b_v4[];};
|
|
|
|
// This shader assumes K_QUANTS_PER_ITERATION == 2 for alignment of loads
|
|
void main() {
|
|
const uint row = gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z;
|
|
|
|
uint a_offset, b_offset, d_offset;
|
|
get_offsets(a_offset, b_offset, d_offset);
|
|
|
|
const uint num_blocks_per_row = p.ncols / QUANT_K;
|
|
const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row;
|
|
|
|
const uint tid = gl_LocalInvocationID.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16
|
|
const uint ix = gl_LocalInvocationID.x%K_QUANTS_PER_ITERATION; // 0 or 0, 1
|
|
|
|
const uint step = 8/K_QUANTS_PER_ITERATION; // 8 or 4
|
|
|
|
const uint il = tid/step; // 0...3
|
|
const uint ir = tid - step*il; // 0...7 or 0...3
|
|
const uint n = 2 * K_QUANTS_PER_ITERATION; // 2 or 4
|
|
|
|
const uint v_im = il / 2; // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224
|
|
const uint v_in = il % 2;
|
|
|
|
const uint l0 = n * (2 * ir + v_in); // 0...15
|
|
const uint q_offset = 32*v_im + l0;
|
|
const uint y_offset = 64*v_im + l0;
|
|
|
|
FLOAT_TYPE temp = FLOAT_TYPE(0.0); // partial sum for thread in warp
|
|
|
|
[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
|
|
const uint y1_idx = i * QUANT_K + y_offset;
|
|
const uint y2_idx = y1_idx + 128;
|
|
|
|
f16vec2 d = data_a[ib0 + i].d;
|
|
const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
|
|
const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
|
|
|
|
uint32_t scale0_u32 = data_a_u16[ib0 + i].scales[v_im ];
|
|
uint32_t scale4_u32 = data_a_u16[ib0 + i].scales[v_im + 2];
|
|
uint32_t scale8_u32 = data_a_u16[ib0 + i].scales[v_im + 4];
|
|
uvec4 scale0 = uvec4(unpack8(scale0_u32));
|
|
uvec4 scale4 = uvec4(unpack8(scale4_u32));
|
|
uvec4 scale8 = uvec4(unpack8(scale8_u32));
|
|
|
|
const uint32_t sc0 = ( scale0.x & 0x3f);
|
|
const uint32_t sc1 = ( scale0.y & 0x3f);
|
|
const uint32_t sc2 = ( scale4.x & 0x3f);
|
|
const uint32_t sc3 = ( scale4.y & 0x3f);
|
|
const uint32_t sc4 = (( scale8.x & 0x0f) | ((scale0.x & 0xc0) >> 2));
|
|
const uint32_t sc5 = (( scale8.y & 0x0f) | ((scale0.y & 0xc0) >> 2));
|
|
const uint32_t sc6 = (((scale8.x >> 4) & 0x0f) | ((scale4.x & 0xc0) >> 2));
|
|
const uint32_t sc7 = (((scale8.y >> 4) & 0x0f) | ((scale4.y & 0xc0) >> 2));
|
|
|
|
uint32_t qs0_u32 = data_a_u32[ib0 + i].qs[q_offset / 4];
|
|
uint32_t qs64_u32 = data_a_u32[ib0 + i].qs[q_offset / 4 + 16];
|
|
|
|
uint32_t qs0_u32_lo4 = qs0_u32 & 0x0F0F0F0F;
|
|
uint32_t qs0_u32_hi4 = (qs0_u32 >> 4) & 0x0F0F0F0F;
|
|
uint32_t qs64_u32_lo4 = qs64_u32 & 0x0F0F0F0F;
|
|
uint32_t qs64_u32_hi4 = (qs64_u32 >> 4) & 0x0F0F0F0F;
|
|
|
|
uvec4 qs0_lo4 = uvec4(unpack8(qs0_u32_lo4));
|
|
uvec4 qs64_lo4 = uvec4(unpack8(qs64_u32_lo4));
|
|
uvec4 qs0_hi4 = uvec4(unpack8(qs0_u32_hi4));
|
|
uvec4 qs64_hi4 = uvec4(unpack8(qs64_u32_hi4));
|
|
|
|
const uint32_t q4_0 = qs0_lo4.x;
|
|
const uint32_t q4_1 = qs0_lo4.y;
|
|
const uint32_t q4_2 = qs0_lo4.z;
|
|
const uint32_t q4_3 = qs0_lo4.w;
|
|
const uint32_t q4_4 = qs0_hi4.x;
|
|
const uint32_t q4_5 = qs0_hi4.y;
|
|
const uint32_t q4_6 = qs0_hi4.z;
|
|
const uint32_t q4_7 = qs0_hi4.w;
|
|
const uint32_t q4_8 = qs64_lo4.x;
|
|
const uint32_t q4_9 = qs64_lo4.y;
|
|
const uint32_t q4_10 = qs64_lo4.z;
|
|
const uint32_t q4_11 = qs64_lo4.w;
|
|
const uint32_t q4_12 = qs64_hi4.x;
|
|
const uint32_t q4_13 = qs64_hi4.y;
|
|
const uint32_t q4_14 = qs64_hi4.z;
|
|
const uint32_t q4_15 = qs64_hi4.w;
|
|
|
|
B_TYPE_VEC4 by10 = data_b_v4[(b_offset + y1_idx) / 4];
|
|
B_TYPE_VEC4 by132 = data_b_v4[(b_offset + y1_idx) / 4 + 8];
|
|
B_TYPE_VEC4 by20 = data_b_v4[(b_offset + y2_idx) / 4];
|
|
B_TYPE_VEC4 by232 = data_b_v4[(b_offset + y2_idx) / 4 + 8];
|
|
|
|
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)));
|
|
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)));
|
|
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)));
|
|
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)));
|
|
const FLOAT_TYPE smin =
|
|
fma(FLOAT_TYPE(by10.x), sc2, fma(FLOAT_TYPE(by132.x), sc3, fma(FLOAT_TYPE(by20.x), sc6, fma(FLOAT_TYPE(by232.x), sc7,
|
|
fma(FLOAT_TYPE(by10.y), sc2, fma(FLOAT_TYPE(by132.y), sc3, fma(FLOAT_TYPE(by20.y), sc6, fma(FLOAT_TYPE(by232.y), sc7,
|
|
fma(FLOAT_TYPE(by10.z), sc2, fma(FLOAT_TYPE(by132.z), sc3, fma(FLOAT_TYPE(by20.z), sc6, fma(FLOAT_TYPE(by232.z), sc7,
|
|
fma(FLOAT_TYPE(by10.w), sc2, fma(FLOAT_TYPE(by132.w), sc3, fma(FLOAT_TYPE(by20.w), sc6, FLOAT_TYPE(by232.w) * sc7)))))))))))))));
|
|
temp = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp));
|
|
}
|
|
|
|
tmp[gl_LocalInvocationID.x] = temp;
|
|
|
|
// sum up partial sums and write back result
|
|
barrier();
|
|
[[unroll]] for (uint s = 16; s > 0; s >>= 1) {
|
|
if (tid < s) {
|
|
tmp[tid] += tmp[tid + s];
|
|
}
|
|
barrier();
|
|
}
|
|
if (tid == 0) {
|
|
data_d[d_offset + row] = D_TYPE(tmp[0]);
|
|
}
|
|
}
|