#version 450
#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require

#include "mul_mat_vec_base.glsl"

layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;

shared FLOAT_TYPE sccache1[2][BLOCK_SIZE/16][16];
shared FLOAT_TYPE sccache2[2][BLOCK_SIZE/16][16];

FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
uint csel = 0;

void calc_superblock(const uint a_offset, const uint b_offset, const uint itid, const uint v_im, const uint ix, const uint q_offset, const uint y_offset, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows, const bool all_threads) {
    const uint y_idx = i * QUANT_K + y_offset;

    [[unroll]] for (uint n = 0; n < num_rows; ++n) {
        const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
        csel ^= 1;

        if (!all_threads) { // when we don't have enough blocks to use all threads
            if (i < num_blocks_per_row) {
                const uint32_t scale = uint32_t(data_a[ib0 + i].scales[itid]);
                sccache1[csel][ix][itid] = FLOAT_TYPE(scale & 0xF);
                sccache2[csel][ix][itid] = FLOAT_TYPE((scale >> 4) & 0xF);
            }
            barrier();

            if (i >= num_blocks_per_row)
                continue;
        } else {
            const uint32_t scale = uint32_t(data_a[ib0 + i].scales[itid]);
            sccache1[csel][ix][itid] = FLOAT_TYPE(scale & 0xF);
            sccache2[csel][ix][itid] = FLOAT_TYPE((scale >> 4) & 0xF);
            barrier();
        }

        const uint32_t qs_u32 = uint32_t(data_a_packed16[ib0 + i].qs[q_offset / 2]) | (uint32_t(data_a_packed16[ib0 + i].qs[q_offset / 2 + 8]) << 16);
        const vec4 qs_u32_0 = vec4(unpack8(qs_u32 & 0x03030303));
        const vec4 qs_u32_2 = vec4(unpack8((qs_u32 >> 2) & 0x03030303));
        const vec4 qs_u32_4 = vec4(unpack8((qs_u32 >> 4) & 0x03030303));
        const vec4 qs_u32_6 = vec4(unpack8((qs_u32 >> 6) & 0x03030303));

        vec2 d = vec2(data_a[ib0 + i].d);
        const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
        const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);

        [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
            vec2 b0 =   vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 +  0]);
            vec2 b16 =  vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 +  8]);
            vec2 b32 =  vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 + 16]);
            vec2 b48 =  vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 + 24]);
            vec2 b64 =  vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 + 32]);
            vec2 b80 =  vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 + 40]);
            vec2 b96 =  vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 + 48]);
            vec2 b112 = vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 + 56]);

            FLOAT_TYPE sum1 = FLOAT_TYPE(0.0);
            FLOAT_TYPE sum2 = FLOAT_TYPE(0.0);
            [[unroll]] for (int l = 0; l < 2; ++l) {
                sum1 = fma(FLOAT_TYPE(b0[l]),   sccache1[csel][ix][    8*v_im] * qs_u32_0[l  ],
                       fma(FLOAT_TYPE(b16[l]),  sccache1[csel][ix][1 + 8*v_im] * qs_u32_0[l+2],
                       fma(FLOAT_TYPE(b32[l]),  sccache1[csel][ix][2 + 8*v_im] * qs_u32_2[l  ],
                       fma(FLOAT_TYPE(b48[l]),  sccache1[csel][ix][3 + 8*v_im] * qs_u32_2[l+2],
                       fma(FLOAT_TYPE(b64[l]),  sccache1[csel][ix][4 + 8*v_im] * qs_u32_4[l  ],
                       fma(FLOAT_TYPE(b80[l]),  sccache1[csel][ix][5 + 8*v_im] * qs_u32_4[l+2],
                       fma(FLOAT_TYPE(b96[l]),  sccache1[csel][ix][6 + 8*v_im] * qs_u32_6[l  ],
                       fma(FLOAT_TYPE(b112[l]), sccache1[csel][ix][7 + 8*v_im] * qs_u32_6[l+2], sum1))))))));
                sum2 = fma(FLOAT_TYPE(b0[l]),   sccache2[csel][ix][    8*v_im],
                       fma(FLOAT_TYPE(b16[l]),  sccache2[csel][ix][1 + 8*v_im],
                       fma(FLOAT_TYPE(b32[l]),  sccache2[csel][ix][2 + 8*v_im],
                       fma(FLOAT_TYPE(b48[l]),  sccache2[csel][ix][3 + 8*v_im],
                       fma(FLOAT_TYPE(b64[l]),  sccache2[csel][ix][4 + 8*v_im],
                       fma(FLOAT_TYPE(b80[l]),  sccache2[csel][ix][5 + 8*v_im],
                       fma(FLOAT_TYPE(b96[l]),  sccache2[csel][ix][6 + 8*v_im],
                       fma(FLOAT_TYPE(b112[l]), sccache2[csel][ix][7 + 8*v_im], sum2))))))));
            }
            temp[j][n] = fma(dall, sum1, fma(-dmin, sum2, temp[j][n]));
        }
    }
}

void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
    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;

    // 16 threads are used to process each block
    const uint it_size = gl_WorkGroupSize.x/16;
    const uint tid = gl_LocalInvocationID.x;
    const uint itid = tid%16;  // 0...15
    const uint ix = tid/16;

    const uint v_im = itid/8;                                // 0 or 1. 0 computes 0..., 1 computes 128...
    const uint v_in = itid - 8*v_im;                         // 0...7

    const uint l0 = 2*v_in;                                  // 0...15
    const uint q_offset = 32*v_im + l0;
    const uint y_offset = 128*v_im + l0;

    [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
        [[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
            temp[j][i] = FLOAT_TYPE(0);
        }
    }

    const uint nbr_par_th = num_blocks_per_row%it_size;
    const uint nbr_all_th = num_blocks_per_row - nbr_par_th;
    uint i0 = 0;
    [[unroll]] for (; i0 < nbr_all_th; i0 += it_size)
        calc_superblock(a_offset, b_offset, itid, v_im, ix, q_offset, y_offset, i0 + ix, num_blocks_per_row, first_row, num_rows, true);
    calc_superblock(a_offset, b_offset, itid, v_im, ix, q_offset, y_offset, i0 + ix, num_blocks_per_row, first_row, num_rows, false);

    reduce_result(temp, d_offset, first_row, num_rows, tid);
}

void main() {
    const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);

    // do NUM_ROWS at a time, unless there aren't enough remaining rows
    if (first_row + NUM_ROWS <= p.stride_d) {
        compute_outputs(first_row, NUM_ROWS);
    } else {
        if (first_row >= p.stride_d) {
            return;
        }
        compute_outputs(first_row, p.stride_d - first_row);
    }
}
