fix a bug: out-of-bound batch

fix a bug: out-of-bound batch

/*******************************************************************************
 *
 * MIT License
 *
 * Copyright (c) 2017 Advanced Micro Devices, Inc.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 *
 *******************************************************************************/

#define PPCAT_NX(A, B) A##B
#define PPCAT(A, B) PPCAT_NX(A, B)
#define TWO 2
#define FOUR 4
#define EIGHT 8

#if MIOPEN_USE_FP16 == 1
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
#define _FLOAT half
#ifndef HALF_MAX
#define MAX_VAL 65504 /* max value */
#else
#define MAX_VAL HALF_MAX
#endif
#endif
#if MIOPEN_USE_FP32 == 1
#define _FLOAT float
#ifndef FLT_MAX
#define MAX_VAL 3.402823466e+38F /* max value */
#else
#define MAX_VAL FLT_MAX
#endif
#endif

#define _FLOAT2 PPCAT(_FLOAT, TWO)
#define _FLOAT4 PPCAT(_FLOAT, FOUR)
#define _FLOAT8 PPCAT(_FLOAT, EIGHT)

#define UNUSED __attribute__((__unused__))

#define DBG_OUT_OF_RNGE 0

#define MLO_N_OUT_HORIZ_READS ((MLO_OUT_WIDTH + MLO_IN_TILE0 - 1) / MLO_IN_TILE0)
#define MLO_N_SPANS_PER_SCAN (MLO_N_OUT_HORIZ_READS)
#define MLO_N_OUT_HORIZ_PIX_READS (MLO_N_OUT_HORIZ_READS * MLO_IN_TILE0)
#define MLO_OUT_N_PIXS_OFF (MLO_OUT_WIDTH - ((MLO_OUT_WIDTH / MLO_IN_TILE0) * MLO_IN_TILE0))
#define MLO_N_OUT_VERTICAL_READS (MLO_FILTER_SIZE1)
// won't run non-border blocks if  MLO_IN_N_VERT_LOOPS < 2
#if MLO_FILTER_PAD1 > 0

#if MLO_IN_N_VERT_LOOPS >= 2
#define MLO_N_GENERIC_LOOPS (MLO_IN_N_VERT_LOOPS - 2)
#define MLO_IN_VERT_READS (MLO_IN_EXTENT1 + MLO_FILTER_PAD1)
#else
#define MLO_N_GENERIC_LOOPS 0
#define MLO_IN_VERT_READS MLO_IN_EXTENT1
#endif

#else
#define MLO_N_GENERIC_LOOPS (MLO_IN_N_VERT_LOOPS)
#define MLO_IN_VERT_READS MLO_IN_EXTENT1
#endif

// there is an assumption that the scanline fits into LDS
#define MLO_N_IN_HORIZ_PIX_READS (MLO_IN_WIDTH)
#define MLO_N_IN_HORIZ_READS ((MLO_N_IN_HORIZ_PIX_READS + MLO_READ_UNIT - 1) / MLO_READ_UNIT)
#define MLO_IN_N_PIXS_OFF \
    (MLO_N_IN_HORIZ_PIX_READS - (MLO_N_IN_HORIZ_PIX_READS / MLO_READ_UNIT) * MLO_READ_UNIT)
#define MLO_IN_LCL_WIDTH (MLO_N_IN_HORIZ_READS * MLO_READ_UNIT + 2 * MLO_FILTER_PAD0)
#define MLO_IN_LCL_HEIGHT MLO_IN_VERT_READS
#define MLO_IN_LCL_SZ (MLO_IN_LCL_WIDTH * MLO_IN_LCL_HEIGHT)
#define MLO_TOTAL_IN_LCL_SZ (MLO_N_LCL_BATCHS * MLO_N_LCL_IN_MAPS * MLO_IN_LCL_SZ)

#define MLO_WEI_LCL_SZ (MLO_GRP_SZ * MLO_FILTER_SIZE0)
#if MLO_TOTAL_IN_LCL_SZ > MLO_WEI_LCL_SZ
#define MLO_LCL_SZ (MLO_TOTAL_IN_LCL_SZ)
#else
#define MLO_LCL_SZ (MLO_WEI_LCL_SZ)
#endif

__attribute__((always_inline)) uint iDiv(uint v, uint d)
{
    uint r = v / d; //(uint)((float)v * (1.0f / (float)d) + 0.00001f);
    return (r);
}

__attribute__((always_inline)) uint iMod(uint v, uint u, uint d)
{
    uint r = v - mul24((uint)u, (uint)d);
    return (r);
}

__attribute__((always_inline)) void ReduceKernel(__local _FLOAT* lcl_blob,
                                                 __private _FLOAT* weights_accum,
                                                 uint lcl_id,
                                                 uint scan_lcl,
                                                 uint sum_stride,
                                                 uint unit_len,
                                                 UNUSED bool debug)
{
    // read first half
    if(scan_lcl < (sum_stride >> 1))
    {
        for(uint i = 0; i < unit_len; ++i)
        {
            weights_accum[i] = lcl_blob[(lcl_id + scan_lcl) * unit_len + i];
        }
    }
    // add second half
    // appload accumulated value so far
    for(uint j = (sum_stride >> 1); j > 0; j >>= 1)
    {
        barrier(CLK_LOCAL_MEM_FENCE);
        if(scan_lcl < j)
        {
            for(uint i = 0; i < unit_len; ++i)
            {
                weights_accum[i] += lcl_blob[(lcl_id + j) * unit_len + i];

                lcl_blob[lcl_id * unit_len + i] = weights_accum[i];
            }
        }
    }
}

/*
        group cooperative read
        read by MLO_READ_UNIT
        handle out of range both horizontally and vertically (by fixed number of veryical reads)

        no guard against number of inputs
*/
__attribute__((always_inline)) void readInput(uint lcl_id,
                                              uint gbl_in_scan_off,
                                              uint n_v_reads,
                                              const __global _FLOAT* __restrict bot,
                                              __local _FLOAT* __restrict lcl_bot)
{
    for(uint p4 = lcl_id; p4 < MLO_N_LCL_IN_MAPS * MLO_N_IN_HORIZ_READS * n_v_reads;
        p4 += MLO_GRP_SZ)
    {
        __private _FLOAT in_rd_data[MLO_READ_UNIT];
        // TODO : more than 1 input
        uint c    = 0;
        uint t_p4 = p4;
#if MLO_N_LCL_IN_MAPS > 1
        c    = p4 / (MLO_N_IN_HORIZ_READS * n_v_reads);
        t_p4 = iMod(p4, c, (MLO_N_IN_HORIZ_READS * n_v_reads));
#endif

        uint c_scan = t_p4 / (MLO_N_IN_HORIZ_READS);

#if MLO_N_IN_HORIZ_READS & (MLO_N_IN_HORIZ_READS - 1)
        uint c_pix4 = iMod(t_p4, c_scan, (MLO_N_IN_HORIZ_READS));
#else
        uint c_pix4 = t_p4 & (MLO_N_IN_HORIZ_READS - 1);
#endif

        //		if (c < MLO_N_INPUTS)

        {
            uint bot_off = gbl_in_scan_off + c * MLO_IN_CHANNEL_STRIDE + c_scan * MLO_IN_STRIDE +
                           c_pix4 * MLO_READ_UNIT;
            const __global _FLOAT* bot_p = &bot[bot_off];
#if MLO_IN_N_PIXS_OFF > 0

            if(c_pix4 == MLO_N_IN_HORIZ_READS - 1)
            {
                for(uint i = 0; i < MLO_IN_N_PIXS_OFF; ++i)
                {
#if 1
                    in_rd_data[i] = bot_p[i];
#else
                    in_rd_data[i] = bot[0];
#endif

#if DBG_OUT_OF_RNGE
                    if(bot_off + i >= MLO_IN_BATCH_STRIDE * MLO_BATCH_SZ)
                    {
                        printf("k:out-of-range: %d %d\n", bot_off, i);
                    }
#endif
                }

                for(uint i = MLO_IN_N_PIXS_OFF; i < MLO_READ_UNIT; ++i)
                {
                    in_rd_data[i] = 0;
                }
            }
            else
#endif
            {

                for(uint i = 0; i < MLO_READ_UNIT; ++i)
                {
#if 1
                    in_rd_data[i] = bot_p[i];
#else
                    in_rd_data[i] = bot[0];
#endif

#if DBG_OUT_OF_RNGE
                    if(bot_off + i >= MLO_IN_BATCH_STRIDE * MLO_BATCH_SZ)
                    {
                        printf("k:out-of-range: %d %d\n", bot_off, i);
                    }
#endif
                }
            }

            // MLO_N_LCL_IN_MAPS inputs
            for(uint i = 0; i < MLO_READ_UNIT; ++i)
            {
                int lcl_in_off = c * MLO_IN_LCL_SZ + c_scan * MLO_IN_LCL_WIDTH + MLO_FILTER_PAD0 +
                                 c_pix4 * MLO_READ_UNIT + i;
#if 1
                lcl_bot[lcl_in_off] = in_rd_data[i];
#else
                lcl_bot[0] = in_rd_data[i];
#endif
            }
        }

    } // for (int p4 = lcl_id; p4 < MLO_N_LCL_IN_MAPS * MLO_N_IN_HORIZ_READS * MLO_IN_VERT_READS;

    barrier(CLK_LOCAL_MEM_FENCE);
}

/*
        core processing loop
        bot - input, from local (1 span)
        top - output diff, from global (array of spans, filters vertical size)

        loop over filter vertical size

*/
__attribute__((always_inline)) void Processing(UNUSED uint sc,
                                               uint sc_lcl_off,
                                               uint top_lim,
                                               int bot_lim,
                                               __private _FLOAT* __restrict pvt_accum,
                                               __local _FLOAT* __restrict lcl_bot,
                                               __private _FLOAT* __restrict top_dat)
{
    for(int l = top_lim; l >= bot_lim; --l)
    {
        for(uint m = 0; m < MLO_IN_TILE0; ++m)
        {
            for(uint n = 0; n < MLO_FILTER_SIZE0; ++n)
            {
                for(uint c = 0; c < MLO_N_LCL_IN_MAPS; ++c)
                {
                    int bot_off    = sc_lcl_off + c * MLO_IN_LCL_SZ + n + m;
#if 1
                    _FLOAT bot_val = lcl_bot[bot_off];
#else
                    _FLOAT bot_val = lcl_bot[0];
#endif
                    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
                    {
                        uint pvt_top_off =
                            k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + (top_lim - l) * MLO_IN_TILE0 + m;
                        uint pvt_accum_off =
                            (k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0 +
                            l * MLO_FILTER_SIZE0 + n;

                        _FLOAT top_val = top_dat[pvt_top_off];

                        pvt_accum[pvt_accum_off]
                            // each wk-it process an input
                            += bot_val * top_val;
                    }
                }
            }
        }
    }
}

__attribute__((always_inline)) void moveOutputUp(__private _FLOAT* __restrict top_dat)
{
    // move up output to reduce overfetch
    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
    {
        for(uint j = 0; j < MLO_FILTER_SIZE1 - 1; ++j)
        {
            for(uint i = 0; i < MLO_IN_TILE0; ++i)
            {
                uint pvt_off_n = k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + j * MLO_IN_TILE0 + i;
                uint pvt_off_o = k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + (j + 1) * MLO_IN_TILE0 + i;
                top_dat[pvt_off_n] = top_dat[pvt_off_o];
            }
        }
    }
}

__attribute__((always_inline)) void
spanReadingOutput(int spn,
                  int k,
                  int j,
                  int top_df_off,
                  _FLOAT mask,
                  __private _FLOAT* __restrict top_dat,
                  const __global _FLOAT* __restrict top_df)
{
    int pvt_off                     = k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + j * MLO_IN_TILE0;
    const __global _FLOAT* top_df_p = &top_df[top_df_off];
#if MLO_OUT_N_PIXS_OFF > 0
    if(spn == MLO_N_SPANS_PER_SCAN - 1)
    {
        uint i = 0;
        for(; i < MLO_OUT_N_PIXS_OFF; ++i)
        {
#if 1
            top_dat[pvt_off + i] = top_df_p[i] * mask;
#else
            top_dat[pvt_off + i] = top_df[0] * mask;
#endif

#if DBG_OUT_OF_RNGE
            if(top_df_off + i >= MLO_OUT_BATCH_STRIDE * MLO_BATCH_SZ)
            {
                printf("k:err:out-of-range\n");
            }
#endif
        }
        for(; i < MLO_IN_TILE0; ++i)
        {
            top_dat[pvt_off + i] = 0;
        }
    }
    else
#else
    (void)spn;
#endif
    {
        for(uint i = 0; i < MLO_IN_TILE0; ++i)
        {
#if 1
            top_dat[pvt_off + i] = top_df_p[i] * mask;
#else
            top_dat[pvt_off + i] = top_df[0] * mask;
#endif

#if DBG_OUT_OF_RNGE
            if(top_df_off + i >= MLO_OUT_BATCH_STRIDE * MLO_BATCH_SZ)
            {
                printf("k:err:out-of-range\n");
            }
#endif
        }
    }
}

/*********************************************************************************************************
// wrw algorithm for large filters
// idea:
// split output scan-line on number of spans by the  MLO_IN_TILE0 (2 for example)
// 1 scan-line has ((MLO_OUT_WIDTH + MLO_IN_TILE0 - 1/MLO_IN_TILE0) spans
// group will process MLO_GRP_SZ/((MLO_OUT_WIDTH + MLO_IN_TILE0 - 1/MLO_IN_TILE0) output maps

// alg
// load a block of input map (or full map) into LDS
// loop
// read MLO_FILTER_SIZE1 number of spans from output map into VGPRs (for example 5 *2 = 10)
// read 1 input line for  maps into LDS
// accumulate

// accumulate all spans at the end
// start new loop for the next batch (if defined)
// write out

// kerenl handles 5x5, 3x3 with padding
// small images in 1 short- MLO_N_GENERIC_LOOPS == 0
// big images  in 2 blocks - MLO_IN_N_VERT_LOOPS == 2 or multiple blocks - MLO_IN_N_VERT_LOOPS > 2
// there are prolog and apilog that deal with top/bottom padding.
// left/right padding handles as a LDS border pixels zeroed at the beginning.

**********************************************************************************************************/

__attribute__((reqd_work_group_size(MLO_GRP_SZ0, MLO_GRP_SZ1, MLO_GRP_SZ2))) __kernel void
MIOpenCvBwdWrW(const __global _FLOAT* __restrict top_df,
               const __global _FLOAT* __restrict bot,
               __global _FLOAT* __restrict weights_df,
#if MLO_CONV_BIAS
               __global _FLOAT* __restrict bias_df,
#endif
               UNUSED _FLOAT padding_val)
{

    // input/output tiles + reduce buffer

    __local _FLOAT lcl[(MLO_LCL_SZ) + 1];
    __local _FLOAT* lcl_bot = lcl;

    uint lcl_id = get_local_id(0);

    uint c_idx_base = get_group_id(0); // input map index base

    uint o_idx_base = get_group_id(1); // output map index base

    uint ib_base = get_group_id(2);

    uint ib = ib_base * (MLO_N_BATCH_LOOPS * MLO_N_LCL_BATCHS);

    uint c_idx = c_idx_base * MLO_N_LCL_IN_MAPS; // input map index

    uint o_idx = o_idx_base * (MLO_N_LCL_OUT_MAPS * MLO_OUT_STACKS); // output map index

    uint gbl_in_off  = c_idx * MLO_IN_CHANNEL_STRIDE + ib * MLO_IN_BATCH_STRIDE;
    uint gbl_out_off = o_idx * MLO_OUT_CHANNEL_STRIDE + ib * MLO_OUT_BATCH_STRIDE;
    // 1 span per wk_item, total scanline with MLO_N_SPANS_PER_SCAN spans
    // TODO: more than 1 input
    uint o = lcl_id / MLO_N_SPANS_PER_SCAN;
#if MLO_N_SPANS_PER_SCAN & (MLO_N_SPANS_PER_SCAN - 1)
    uint spn = iMod(lcl_id, o, MLO_N_SPANS_PER_SCAN);
#else
    uint spn         = lcl_id & (MLO_N_SPANS_PER_SCAN - 1);
#endif
    //	bool scan_lead = (o*MLO_N_SPANS_PER_SCAN == lcl_id);

    uint lcl_bot_off     = spn * MLO_IN_TILE0;
    uint out_wk_item_off = o * MLO_OUT_CHANNEL_STRIDE + lcl_bot_off;
    gbl_out_off += out_wk_item_off;
    // no output out of range
    gbl_out_off = (o_idx + o < MLO_N_OUTPUTS && o < MLO_OUT_STACKS) ? gbl_out_off : 0;

#define MLO_TOP_DAT_SZ (MLO_N_LCL_OUT_MAPS * MLO_IN_TILE0 * MLO_FILTER_SIZE1)

    __private _FLOAT top_dat[MLO_TOP_DAT_SZ];

    for(uint i = 0; i < MLO_TOP_DAT_SZ; ++i)
    {
        top_dat[i] = 0;
    }

#define MLO_ACCUM_SZ (MLO_N_LCL_OUT_MAPS * MLO_N_LCL_IN_MAPS * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0)

    __private _FLOAT pvt_accum[MLO_ACCUM_SZ];

    for(uint i = 0; i < MLO_ACCUM_SZ; ++i)
    {
        pvt_accum[i] = 0;
    }

    // zero out LDS
    for(uint i = lcl_id; i < (MLO_LCL_SZ); i += MLO_GRP_SZ)
    {
#if 1
        lcl[i] = 0;
#else
        lcl[0] = 0;
#endif
    }

    // over all batches
    uint bbegin = ib;
    uint bend   = ib + MLO_N_BATCH_LOOPS * MLO_N_LCL_BATCHS;
    bend = bend > MLO_BATCH_SZ ? MLO_BATCH_SZ : bend;

    for(uint b = bbegin; b < bend; ++b,
             gbl_in_off += MLO_N_LCL_BATCHS * MLO_IN_BATCH_STRIDE,
             gbl_out_off += MLO_N_LCL_BATCHS * MLO_OUT_BATCH_STRIDE)
    {
        barrier(CLK_LOCAL_MEM_FENCE);
        // top border input block
        uint gbl_in_scan_off  = gbl_in_off;
        uint gbl_out_scan_off = gbl_out_off;

#if DBG_OUT_OF_RNGE
        if((get_local_id(0) == 0 || get_local_id(0) == get_local_size(0)-1))
        {
            printf("1: b %5d, group_id (%5d %5d %5d), local_id (%5d): gbl_in_scan_off %10d, gbl_out_scan_off %10d\n",
                    b,
                    get_group_id(0), get_group_id(1), get_group_id(2),
                    get_local_id(0),
                    gbl_in_scan_off, gbl_out_scan_off);
        }
#endif

#if 1
        // read input map
        readInput(lcl_id, gbl_in_scan_off, MLO_IN_VERT_READS, bot, lcl_bot);
#endif
        // move input pointer
        gbl_in_scan_off += MLO_IN_STRIDE * MLO_IN_EXTENT1;

        for(uint i = 0; i < MLO_TOP_DAT_SZ; ++i)
        {
            top_dat[i] = 0;
        }

        // prefetch output

        int gbl_out_scan_off1 = gbl_out_scan_off;
        for(uint k = 0; k < MLO_N_LCL_OUT_MAPS;
            ++k, gbl_out_scan_off1 += MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE)
        {
            for(uint j = 0; j < MLO_FILTER_SIZE1 - 1; ++j)
            {
                // loop around all output maps
                uint top_df_off = gbl_out_scan_off1 + j * MLO_OUT_STRIDE;
                _FLOAT mask     = 1;
#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT || MLO_FILTER_SIZE1 - 1 > MLO_OUT_HEIGHT
                top_df_off = (j < MLO_OUT_HEIGHT) ? top_df_off : 0;
                mask       = (j < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                spanReadingOutput(spn, k, j, top_df_off, mask, top_dat, top_df);
#endif
            }
        }

        gbl_out_scan_off += (MLO_FILTER_SIZE1 - 1) * MLO_OUT_STRIDE;

        uint sc         = 0;
        uint sc_lcl_off = lcl_bot_off;

        // prolog
        // handling padding

        // top padding
        for(; sc < MLO_FILTER_SIZE1 - MLO_FILTER_PAD1 - 1; ++sc, sc_lcl_off += MLO_IN_LCL_WIDTH)
        {
            Processing(sc, sc_lcl_off, sc + MLO_FILTER_PAD1, 0, pvt_accum, lcl_bot, top_dat);
        }

#ifdef __AMDGCN__
#pragma unroll 2
#endif
        for(; sc < MLO_IN_EXTENT1
#if MLO_IN_N_VERT_LOOPS == 1
                       -
                       MLO_FILTER_PAD1
#endif
            ;
            ++sc, gbl_out_scan_off += MLO_OUT_STRIDE, sc_lcl_off += MLO_IN_LCL_WIDTH)
        {

            for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
            {
                uint top_df_off = gbl_out_scan_off + k * MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE;
                _FLOAT mask     = 1;

#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT || MLO_FILTER_SIZE1 - 1 > MLO_OUT_HEIGHT
                top_df_off = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? top_df_off : 0;
                mask       = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                spanReadingOutput(
                    spn, k, (MLO_FILTER_SIZE1 - 1), top_df_off, mask, top_dat, top_df);
#endif
            }

            // processing
            Processing(sc, sc_lcl_off, MLO_FILTER_SIZE1 - 1, 0, pvt_accum, lcl_bot, top_dat);

            // move up output to reduce overfetch
            moveOutputUp(top_dat);
        }

        // non-border input blocks
        for(uint i_loop = 0; i_loop < MLO_N_GENERIC_LOOPS - 1;
            ++i_loop, gbl_in_scan_off += MLO_IN_STRIDE * MLO_IN_EXTENT1)
        {
            barrier(CLK_LOCAL_MEM_FENCE);

#if DBG_OUT_OF_RNGE
            if((get_local_id(0) == 0 || get_local_id(0) == get_local_size(0)-1))
            {
                printf("2: b %5d, group_id (%5d %5d %5d), local_id (%5d): gbl_in_scan_off %10d, gbl_out_scan_off %10d\n",
                        b,
                        get_group_id(0), get_group_id(1), get_group_id(2),
                        get_local_id(0),
                        gbl_in_scan_off, gbl_out_scan_off);
            }
#endif

#if 1
            readInput(lcl_id, gbl_in_scan_off, MLO_IN_VERT_READS, bot, lcl_bot);
#endif

            // point to the start of the local buffer

            sc_lcl_off = lcl_bot_off;

            for(; sc < (i_loop + 2) * MLO_IN_EXTENT1;
                ++sc, gbl_out_scan_off += MLO_OUT_STRIDE, sc_lcl_off += MLO_IN_LCL_WIDTH)
            {

                for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
                {
                    uint top_df_off =
                        gbl_out_scan_off + k * MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE;
                    _FLOAT mask = 1;

#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT
                    top_df_off = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? top_df_off : 0;
                    mask       = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                    spanReadingOutput(
                        spn, k, (MLO_FILTER_SIZE1 - 1), top_df_off, mask, top_dat, top_df);
#endif
                }

                // processing
                Processing(sc, sc_lcl_off, MLO_FILTER_SIZE1 - 1, 0, pvt_accum, lcl_bot, top_dat);

                // move up output to reduce overfetch
                moveOutputUp(top_dat);
            }
        }

        // bottom border block

        for(int i_loop = 0; i_loop < (MLO_IN_N_VERT_LOOPS - MLO_N_GENERIC_LOOPS - 1);
            ++i_loop, gbl_in_scan_off += MLO_IN_STRIDE * MLO_IN_EXTENT1)
        {

            barrier(CLK_LOCAL_MEM_FENCE);
// read 1 scan line less
// padding processing takes care of the bottom border.

#define MLO_LAST_VERT_READS (MLO_IN_HEIGHT - MLO_IN_EXTENT1 * (MLO_IN_N_VERT_LOOPS - 1))

#if DBG_OUT_OF_RNGE
        if((get_local_id(0) == 0 || get_local_id(0) == get_local_size(0)-1))
        {
            printf("3: b %5d, group_id (%5d %5d %5d), local_id (%5d): gbl_in_scan_off %10d, gbl_out_scan_off %10d\n",
                    b,
                    get_group_id(0), get_group_id(1), get_group_id(2),
                    get_local_id(0),
                    gbl_in_scan_off, gbl_out_scan_off);
        }
#endif

#if 1
            readInput(lcl_id, gbl_in_scan_off, MLO_LAST_VERT_READS, bot, lcl_bot);
#endif

            // point to the start of the local buffer
            sc_lcl_off = lcl_bot_off;

#pragma unroll 3
            for(; sc < MLO_OUT_HEIGHT - MLO_FILTER_PAD1;
                ++sc, gbl_out_scan_off += MLO_OUT_STRIDE, sc_lcl_off += MLO_IN_LCL_WIDTH)
            {

                for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
                {
                    uint top_df_off =
                        gbl_out_scan_off + k * MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE;
                    _FLOAT mask = 1;

#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT
                    top_df_off = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? top_df_off : 0;
                    mask       = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                    spanReadingOutput(
                        spn, k, (MLO_FILTER_SIZE1 - 1), top_df_off, mask, top_dat, top_df);
#endif
                }

                // processing
                Processing(sc, sc_lcl_off, MLO_FILTER_SIZE1 - 1, 0, pvt_accum, lcl_bot, top_dat);

                // move up output to reduce overfetch
                moveOutputUp(top_dat);
            }
        }

        // epilog
        // handling padding

        for(; sc < MLO_IN_HEIGHT; ++sc, sc_lcl_off += MLO_IN_LCL_WIDTH)
        {

            // processing
            Processing(sc,
                       sc_lcl_off,
                       MLO_FILTER_SIZE1 - 1,
                       (MLO_FILTER_PAD1 + 1 - (MLO_IN_HEIGHT - sc)),
                       pvt_accum,
                       lcl_bot,
                       top_dat);
            // move up output to reduce overfetch
            moveOutputUp(top_dat);

        } // for (; sc < MLO_OUT_HEIGHT - MLO_FILTER_PAD1 + 2; ++sc, gbl_out_scan_off +=
          // MLO_OUT_CHANNEL_STRIDE, gbl_in_scan_off += MLO_IN_CHANNEL_STRIDE)

    } // 	for (int b = 0;

    // final summation over all output maps and each filter row
    // this coudl be done with log but it negligeble anyway
    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
    {
        for(uint c = 0; c < MLO_N_LCL_IN_MAPS; ++c)
        {

            for(uint l = 0; l < MLO_FILTER_SIZE1; ++l)
            {

                barrier(CLK_LOCAL_MEM_FENCE);
                for(uint n = 0; n < MLO_FILTER_SIZE0; ++n)
                {
                    uint pvt_off =
                        (k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0 +
                        l * MLO_FILTER_SIZE0 + n;
#if 1
                    lcl[lcl_id * MLO_FILTER_SIZE0 + n] = pvt_accum[pvt_off];
#else
                    lcl[0] = pvt_accum[pvt_off];
#endif
                }

                barrier(CLK_LOCAL_MEM_FENCE);

                if(spn == 0)
                {
                    for(uint s = 0; s < MLO_N_SPANS_PER_SCAN - 1; ++s)
                    {

                        for(uint n = 0; n < MLO_FILTER_SIZE0; ++n)
                        {
                            uint pvt_off =
                                (k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0 +
                                l * MLO_FILTER_SIZE0 + n;
#if 1
                            pvt_accum[pvt_off] += lcl[(lcl_id + s + 1) * MLO_FILTER_SIZE0 + n];
#else
                            pvt_accum[pvt_off] += lcl[0];
#endif
                        }
                    }
                }
            }
        }
    }

    // output
    // inputs are outputs
    // TODO : for more than 1 input

    uint wei_df_off =
        (((ib / MLO_N_BATCH_LOOPS) * MLO_N_OUTPUTS + o_idx + o) * (uint)MLO_WEI_BATCH_STRIDE)
        // this input channel
        + mul24(c_idx, (uint)MLO_WEI_CHANNEL_STRIDE);
    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
    {
        if(spn == 0 && o_idx + o + k * MLO_OUT_STACKS < MLO_N_OUTPUTS && o < MLO_OUT_STACKS)
        {
            for(uint c = 0; c < MLO_N_LCL_IN_MAPS; ++c)
            {
                for(uint i = 0; i < (MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0); ++i)
                {
#if 1
                    weights_df[wei_df_off + k * MLO_OUT_STACKS * MLO_WEI_BATCH_STRIDE +
                               c * MLO_WEI_CHANNEL_STRIDE + i] =
                        pvt_accum[(k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 *
                                      MLO_FILTER_SIZE0 +
                                  i];
#endif
                }
            }
        }
    }
}

// final reduction kernel
// add filters over batches
__attribute__((reqd_work_group_size(MLO_UT_GRP_SZ0, 1, 1))) __kernel void
MIOpenCvBwdWrW_rdc(const __global _FLOAT* __restrict weight_df_tmp,
                   __global _FLOAT* __restrict weights_df)
{
    uint gbl_id   = get_global_id(0);
    uint wei_idx0 = gbl_id * MLO_UT_READ_UNIT;

#if MLO_WEI_CHANNEL_STRIDE & (MLO_WEI_CHANNEL_STRIDE - 1)
    uint wei_blk_idx = iDiv(wei_idx0, MLO_WEI_CHANNEL_STRIDE);
    uint wei_idx     = iMod(wei_idx0, wei_blk_idx, MLO_WEI_CHANNEL_STRIDE);
#else
    uint wei_blk_idx = wei_idx0 / MLO_WEI_CHANNEL_STRIDE;
    uint wei_idx     = wei_idx0 & (MLO_WEI_CHANNEL_STRIDE - 1);
#endif

    _FLOAT pvt_accum_wei[MLO_UT_READ_UNIT] = {MLO_UT_READ_UNIT * (_FLOAT)0};
    //	for (uint i = 0; i < MLO_UT_READ_UNIT; ++i)
    //	{
    //		pvt_accum_wei[i] = 0;
    //	}

    int batch_loop = (MLO_BATCH_SZ + (MLO_N_BATCH_LOOPS * MLO_N_LCL_BATCHS) - 1) /
                     (MLO_N_BATCH_LOOPS * MLO_N_LCL_BATCHS);
    for(uint i = 0; i < batch_loop; ++i)
    {
        for(uint j = 0; j < MLO_UT_READ_UNIT; ++j)
        {
            pvt_accum_wei[j] += weight_df_tmp[(wei_blk_idx * MLO_WEI_CHANNEL_STRIDE +
                                               i * MLO_N_OUTPUTS * MLO_WEI_BATCH_STRIDE) +
                                              wei_idx + j];
        }
    }

    for(uint j = 0; j < MLO_UT_READ_UNIT; ++j)
    {
        weights_df[wei_idx0 + j] = pvt_accum_wei[j];
    }
}

/*******************************************************************************
 *
 * MIT License
 *
 * Copyright (c) 2017 Advanced Micro Devices, Inc.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 *
 *******************************************************************************/

#define PPCAT_NX(A, B) A##B
#define PPCAT(A, B) PPCAT_NX(A, B)
#define TWO 2
#define FOUR 4
#define EIGHT 8

#if MIOPEN_USE_FP16 == 1
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
#define _FLOAT half
#ifndef HALF_MAX
#define MAX_VAL 65504 /* max value */
#else
#define MAX_VAL HALF_MAX
#endif
#endif
#if MIOPEN_USE_FP32 == 1
#define _FLOAT float
#ifndef FLT_MAX
#define MAX_VAL 3.402823466e+38F /* max value */
#else
#define MAX_VAL FLT_MAX
#endif
#endif

#define _FLOAT2 PPCAT(_FLOAT, TWO)
#define _FLOAT4 PPCAT(_FLOAT, FOUR)
#define _FLOAT8 PPCAT(_FLOAT, EIGHT)

#define UNUSED __attribute__((__unused__))

#define DBG_OUT_OF_RNGE 0

#define MLO_N_OUT_HORIZ_READS ((MLO_OUT_WIDTH + MLO_IN_TILE0 - 1) / MLO_IN_TILE0)
#define MLO_N_SPANS_PER_SCAN (MLO_N_OUT_HORIZ_READS)
#define MLO_N_OUT_HORIZ_PIX_READS (MLO_N_OUT_HORIZ_READS * MLO_IN_TILE0)
#define MLO_OUT_N_PIXS_OFF (MLO_OUT_WIDTH - ((MLO_OUT_WIDTH / MLO_IN_TILE0) * MLO_IN_TILE0))
#define MLO_N_OUT_VERTICAL_READS (MLO_FILTER_SIZE1)
// won't run non-border blocks if  MLO_IN_N_VERT_LOOPS < 2
#if MLO_FILTER_PAD1 > 0

#if MLO_IN_N_VERT_LOOPS >= 2
#define MLO_N_GENERIC_LOOPS (MLO_IN_N_VERT_LOOPS - 2)
#define MLO_IN_VERT_READS (MLO_IN_EXTENT1 + MLO_FILTER_PAD1)
#else
#define MLO_N_GENERIC_LOOPS 0
#define MLO_IN_VERT_READS MLO_IN_EXTENT1
#endif

#else
#define MLO_N_GENERIC_LOOPS (MLO_IN_N_VERT_LOOPS)
#define MLO_IN_VERT_READS MLO_IN_EXTENT1
#endif

// there is an assumption that the scanline fits into LDS
#define MLO_N_IN_HORIZ_PIX_READS (MLO_IN_WIDTH)
#define MLO_N_IN_HORIZ_READS ((MLO_N_IN_HORIZ_PIX_READS + MLO_READ_UNIT - 1) / MLO_READ_UNIT)
#define MLO_IN_N_PIXS_OFF \
    (MLO_N_IN_HORIZ_PIX_READS - (MLO_N_IN_HORIZ_PIX_READS / MLO_READ_UNIT) * MLO_READ_UNIT)
#define MLO_IN_LCL_WIDTH (MLO_N_IN_HORIZ_READS * MLO_READ_UNIT + 2 * MLO_FILTER_PAD0)
#define MLO_IN_LCL_HEIGHT MLO_IN_VERT_READS
#define MLO_IN_LCL_SZ (MLO_IN_LCL_WIDTH * MLO_IN_LCL_HEIGHT)
#define MLO_TOTAL_IN_LCL_SZ (MLO_N_LCL_BATCHS * MLO_N_LCL_IN_MAPS * MLO_IN_LCL_SZ)

#define MLO_WEI_LCL_SZ (MLO_GRP_SZ * MLO_FILTER_SIZE0)
#if MLO_TOTAL_IN_LCL_SZ > MLO_WEI_LCL_SZ
#define MLO_LCL_SZ (MLO_TOTAL_IN_LCL_SZ)
#else
#define MLO_LCL_SZ (MLO_WEI_LCL_SZ)
#endif

__attribute__((always_inline)) uint iDiv(uint v, uint d)
{
    uint r = v / d; //(uint)((float)v * (1.0f / (float)d) + 0.00001f);
    return (r);
}

__attribute__((always_inline)) uint iMod(uint v, uint u, uint d)
{
    uint r = v - mul24((uint)u, (uint)d);
    return (r);
}

__attribute__((always_inline)) void ReduceKernel(__local _FLOAT* lcl_blob,
                                                 __private _FLOAT* weights_accum,
                                                 uint lcl_id,
                                                 uint scan_lcl,
                                                 uint sum_stride,
                                                 uint unit_len,
                                                 UNUSED bool debug)
{
    // read first half
    if(scan_lcl < (sum_stride >> 1))
    {
        for(uint i = 0; i < unit_len; ++i)
        {
            weights_accum[i] = lcl_blob[(lcl_id + scan_lcl) * unit_len + i];
        }
    }
    // add second half
    // appload accumulated value so far
    for(uint j = (sum_stride >> 1); j > 0; j >>= 1)
    {
        barrier(CLK_LOCAL_MEM_FENCE);
        if(scan_lcl < j)
        {
            for(uint i = 0; i < unit_len; ++i)
            {
                weights_accum[i] += lcl_blob[(lcl_id + j) * unit_len + i];

                lcl_blob[lcl_id * unit_len + i] = weights_accum[i];
            }
        }
    }
}

/*
        group cooperative read
        read by MLO_READ_UNIT
        handle out of range both horizontally and vertically (by fixed number of veryical reads)

        no guard against number of inputs
*/
__attribute__((always_inline)) void readInput(uint lcl_id,
                                              uint gbl_in_scan_off,
                                              uint n_v_reads,
                                              const __global _FLOAT* __restrict bot,
                                              __local _FLOAT* __restrict lcl_bot)
{
    for(uint p4 = lcl_id; p4 < MLO_N_LCL_IN_MAPS * MLO_N_IN_HORIZ_READS * n_v_reads;
        p4 += MLO_GRP_SZ)
    {
        __private _FLOAT in_rd_data[MLO_READ_UNIT];
        // TODO : more than 1 input
        uint c    = 0;
        uint t_p4 = p4;
#if MLO_N_LCL_IN_MAPS > 1
        c    = p4 / (MLO_N_IN_HORIZ_READS * n_v_reads);
        t_p4 = iMod(p4, c, (MLO_N_IN_HORIZ_READS * n_v_reads));
#endif

        uint c_scan = t_p4 / (MLO_N_IN_HORIZ_READS);

#if MLO_N_IN_HORIZ_READS & (MLO_N_IN_HORIZ_READS - 1)
        uint c_pix4 = iMod(t_p4, c_scan, (MLO_N_IN_HORIZ_READS));
#else
        uint c_pix4 = t_p4 & (MLO_N_IN_HORIZ_READS - 1);
#endif

        //		if (c < MLO_N_INPUTS)

        {
            uint bot_off = gbl_in_scan_off + c * MLO_IN_CHANNEL_STRIDE + c_scan * MLO_IN_STRIDE +
                           c_pix4 * MLO_READ_UNIT;
            const __global _FLOAT* bot_p = &bot[bot_off];
#if MLO_IN_N_PIXS_OFF > 0

            if(c_pix4 == MLO_N_IN_HORIZ_READS - 1)
            {
                for(uint i = 0; i < MLO_IN_N_PIXS_OFF; ++i)
                {
#if 0
                    in_rd_data[i] = bot_p[i];
#else
                    in_rd_data[i] = bot[0];
#endif

#if DBG_OUT_OF_RNGE
                    if(bot_off + i >= MLO_IN_BATCH_STRIDE * MLO_BATCH_SZ)
                    {
                        printf("k:err:in-of-range\n");
                    }
#endif
                }

                for(uint i = MLO_IN_N_PIXS_OFF; i < MLO_READ_UNIT; ++i)
                {
                    in_rd_data[i] = 0;
                }
            }
            else
#endif
            {

                for(uint i = 0; i < MLO_READ_UNIT; ++i)
                {
#if 0
                    in_rd_data[i] = bot_p[i];
#else
                    in_rd_data[i] = bot[0];
#endif

#if DBG_OUT_OF_RNGE
                    if(bot_off + i >= MLO_IN_BATCH_STRIDE * MLO_BATCH_SZ)
                    {
                        printf("k:err:in-of-range %d %d\n", bot_off, i);
                    }
#endif
                }
            }

            // MLO_N_LCL_IN_MAPS inputs
            for(uint i = 0; i < MLO_READ_UNIT; ++i)
            {
                int lcl_in_off = c * MLO_IN_LCL_SZ + c_scan * MLO_IN_LCL_WIDTH + MLO_FILTER_PAD0 +
                                 c_pix4 * MLO_READ_UNIT + i;
#if 1
                lcl_bot[lcl_in_off] = in_rd_data[i];
#else
                lcl_bot[0] = in_rd_data[i];
#endif
            }
        }

    } // for (int p4 = lcl_id; p4 < MLO_N_LCL_IN_MAPS * MLO_N_IN_HORIZ_READS * MLO_IN_VERT_READS;

    barrier(CLK_LOCAL_MEM_FENCE);
}

/*
        core processing loop
        bot - input, from local (1 span)
        top - output diff, from global (array of spans, filters vertical size)

        loop over filter vertical size

*/
__attribute__((always_inline)) void Processing(UNUSED uint sc,
                                               uint sc_lcl_off,
                                               uint top_lim,
                                               int bot_lim,
                                               __private _FLOAT* __restrict pvt_accum,
                                               __local _FLOAT* __restrict lcl_bot,
                                               __private _FLOAT* __restrict top_dat)
{
    for(int l = top_lim; l >= bot_lim; --l)
    {
        for(uint m = 0; m < MLO_IN_TILE0; ++m)
        {
            for(uint n = 0; n < MLO_FILTER_SIZE0; ++n)
            {
                for(uint c = 0; c < MLO_N_LCL_IN_MAPS; ++c)
                {
                    int bot_off    = sc_lcl_off + c * MLO_IN_LCL_SZ + n + m;
#if 1
                    _FLOAT bot_val = lcl_bot[bot_off];
#else
                    _FLOAT bot_val = lcl_bot[0];
#endif
                    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
                    {
                        uint pvt_top_off =
                            k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + (top_lim - l) * MLO_IN_TILE0 + m;
                        uint pvt_accum_off =
                            (k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0 +
                            l * MLO_FILTER_SIZE0 + n;

                        _FLOAT top_val = top_dat[pvt_top_off];

                        pvt_accum[pvt_accum_off]
                            // each wk-it process an input
                            += bot_val * top_val;
                    }
                }
            }
        }
    }
}

__attribute__((always_inline)) void moveOutputUp(__private _FLOAT* __restrict top_dat)
{
    // move up output to reduce overfetch
    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
    {
        for(uint j = 0; j < MLO_FILTER_SIZE1 - 1; ++j)
        {
            for(uint i = 0; i < MLO_IN_TILE0; ++i)
            {
                uint pvt_off_n = k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + j * MLO_IN_TILE0 + i;
                uint pvt_off_o = k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + (j + 1) * MLO_IN_TILE0 + i;
                top_dat[pvt_off_n] = top_dat[pvt_off_o];
            }
        }
    }
}

__attribute__((always_inline)) void
spanReadingOutput(int spn,
                  int k,
                  int j,
                  int top_df_off,
                  _FLOAT mask,
                  __private _FLOAT* __restrict top_dat,
                  const __global _FLOAT* __restrict top_df)
{
    int pvt_off                     = k * MLO_IN_TILE0 * MLO_FILTER_SIZE1 + j * MLO_IN_TILE0;
    const __global _FLOAT* top_df_p = &top_df[top_df_off];
#if MLO_OUT_N_PIXS_OFF > 0
    if(spn == MLO_N_SPANS_PER_SCAN - 1)
    {
        uint i = 0;
        for(; i < MLO_OUT_N_PIXS_OFF; ++i)
        {
#if 0
            top_dat[pvt_off + i] = top_df_p[i] * mask;
#else
            top_dat[pvt_off + i] = top_df[0] * mask;
#endif

#if DBG_OUT_OF_RNGE
            if(top_df_off + i >= MLO_OUT_BATCH_STRIDE * MLO_BATCH_SZ)
            {
                printf("k:err:out-of-range\n");
            }
#endif
        }
        for(; i < MLO_IN_TILE0; ++i)
        {
            top_dat[pvt_off + i] = 0;
        }
    }
    else
#else
    (void)spn;
#endif
    {
        for(uint i = 0; i < MLO_IN_TILE0; ++i)
        {
#if 0
            top_dat[pvt_off + i] = top_df_p[i] * mask;
#else
            top_dat[pvt_off + i] = top_df[0] * mask;
#endif

#if DBG_OUT_OF_RNGE
            if(top_df_off + i >= MLO_OUT_BATCH_STRIDE * MLO_BATCH_SZ)
            {
                printf("k:err:out-of-range\n");
            }
#endif
        }
    }
}

/*********************************************************************************************************
// wrw algorithm for large filters
// idea:
// split output scan-line on number of spans by the  MLO_IN_TILE0 (2 for example)
// 1 scan-line has ((MLO_OUT_WIDTH + MLO_IN_TILE0 - 1/MLO_IN_TILE0) spans
// group will process MLO_GRP_SZ/((MLO_OUT_WIDTH + MLO_IN_TILE0 - 1/MLO_IN_TILE0) output maps

// alg
// load a block of input map (or full map) into LDS
// loop
// read MLO_FILTER_SIZE1 number of spans from output map into VGPRs (for example 5 *2 = 10)
// read 1 input line for  maps into LDS
// accumulate

// accumulate all spans at the end
// start new loop for the next batch (if defined)
// write out

// kerenl handles 5x5, 3x3 with padding
// small images in 1 short- MLO_N_GENERIC_LOOPS == 0
// big images  in 2 blocks - MLO_IN_N_VERT_LOOPS == 2 or multiple blocks - MLO_IN_N_VERT_LOOPS > 2
// there are prolog and apilog that deal with top/bottom padding.
// left/right padding handles as a LDS border pixels zeroed at the beginning.

**********************************************************************************************************/

__attribute__((reqd_work_group_size(MLO_GRP_SZ0, MLO_GRP_SZ1, MLO_GRP_SZ2))) __kernel void
MIOpenCvBwdWrW(const __global _FLOAT* __restrict top_df,
               const __global _FLOAT* __restrict bot,
               __global _FLOAT* __restrict weights_df,
#if MLO_CONV_BIAS
               __global _FLOAT* __restrict bias_df,
#endif
               UNUSED _FLOAT padding_val)
{

    // input/output tiles + reduce buffer

    __local _FLOAT lcl[(MLO_LCL_SZ) + 1];
    __local _FLOAT* lcl_bot = lcl;

    uint lcl_id = get_local_id(0);

    uint c_idx_base = get_group_id(0); // input map index base

    uint o_idx_base = get_group_id(1); // output map index base

    uint ib_base = get_group_id(2);

    uint ib = ib_base * (MLO_N_BATCH_LOOPS * MLO_N_LCL_BATCHS);

    uint c_idx = c_idx_base * MLO_N_LCL_IN_MAPS; // input map index

    uint o_idx = o_idx_base * (MLO_N_LCL_OUT_MAPS * MLO_OUT_STACKS); // output map index

    uint gbl_in_off  = c_idx * MLO_IN_CHANNEL_STRIDE + ib * MLO_IN_BATCH_STRIDE;
    uint gbl_out_off = o_idx * MLO_OUT_CHANNEL_STRIDE + ib * MLO_OUT_BATCH_STRIDE;
    // 1 span per wk_item, total scanline with MLO_N_SPANS_PER_SCAN spans
    // TODO: more than 1 input
    uint o = lcl_id / MLO_N_SPANS_PER_SCAN;
#if MLO_N_SPANS_PER_SCAN & (MLO_N_SPANS_PER_SCAN - 1)
    uint spn = iMod(lcl_id, o, MLO_N_SPANS_PER_SCAN);
#else
    uint spn         = lcl_id & (MLO_N_SPANS_PER_SCAN - 1);
#endif
    //	bool scan_lead = (o*MLO_N_SPANS_PER_SCAN == lcl_id);

    uint lcl_bot_off     = spn * MLO_IN_TILE0;
    uint out_wk_item_off = o * MLO_OUT_CHANNEL_STRIDE + lcl_bot_off;
    gbl_out_off += out_wk_item_off;
    // no output out of range
    gbl_out_off = (o_idx + o < MLO_N_OUTPUTS && o < MLO_OUT_STACKS) ? gbl_out_off : 0;

#define MLO_TOP_DAT_SZ (MLO_N_LCL_OUT_MAPS * MLO_IN_TILE0 * MLO_FILTER_SIZE1)

    __private _FLOAT top_dat[MLO_TOP_DAT_SZ];

    for(uint i = 0; i < MLO_TOP_DAT_SZ; ++i)
    {
        top_dat[i] = 0;
    }

#define MLO_ACCUM_SZ (MLO_N_LCL_OUT_MAPS * MLO_N_LCL_IN_MAPS * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0)

    __private _FLOAT pvt_accum[MLO_ACCUM_SZ];

    for(uint i = 0; i < MLO_ACCUM_SZ; ++i)
    {
        pvt_accum[i] = 0;
    }

    // zero out LDS
    for(uint i = lcl_id; i < (MLO_LCL_SZ); i += MLO_GRP_SZ)
    {
#if 1
        lcl[i] = 0;
#else
        lcl[0] = 0;
#endif
    }

    // over all batches
    for(uint b = 0; b < MLO_N_BATCH_LOOPS; ++b,
             gbl_in_off += MLO_N_LCL_BATCHS * MLO_IN_BATCH_STRIDE,
             gbl_out_off += MLO_N_LCL_BATCHS * MLO_OUT_BATCH_STRIDE)
    {
        barrier(CLK_LOCAL_MEM_FENCE);
        // top border input block
        uint gbl_in_scan_off  = gbl_in_off;
        uint gbl_out_scan_off = gbl_out_off;

#if 1
        // read input map
        readInput(lcl_id, gbl_in_scan_off, MLO_IN_VERT_READS, bot, lcl_bot);
#endif
        // move input pointer
        gbl_in_scan_off += MLO_IN_STRIDE * MLO_IN_EXTENT1;

        for(uint i = 0; i < MLO_TOP_DAT_SZ; ++i)
        {
            top_dat[i] = 0;
        }

        // prefetch output

        int gbl_out_scan_off1 = gbl_out_scan_off;
        for(uint k = 0; k < MLO_N_LCL_OUT_MAPS;
            ++k, gbl_out_scan_off1 += MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE)
        {
            for(uint j = 0; j < MLO_FILTER_SIZE1 - 1; ++j)
            {
                // loop around all output maps
                uint top_df_off = gbl_out_scan_off1 + j * MLO_OUT_STRIDE;
                _FLOAT mask     = 1;
#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT || MLO_FILTER_SIZE1 - 1 > MLO_OUT_HEIGHT
                top_df_off = (j < MLO_OUT_HEIGHT) ? top_df_off : 0;
                mask       = (j < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                spanReadingOutput(spn, k, j, top_df_off, mask, top_dat, top_df);
#endif
            }
        }

        gbl_out_scan_off += (MLO_FILTER_SIZE1 - 1) * MLO_OUT_STRIDE;

        uint sc         = 0;
        uint sc_lcl_off = lcl_bot_off;

        // prolog
        // handling padding

        // top padding
        for(; sc < MLO_FILTER_SIZE1 - MLO_FILTER_PAD1 - 1; ++sc, sc_lcl_off += MLO_IN_LCL_WIDTH)
        {
            Processing(sc, sc_lcl_off, sc + MLO_FILTER_PAD1, 0, pvt_accum, lcl_bot, top_dat);
        }

#ifdef __AMDGCN__
#pragma unroll 2
#endif
        for(; sc < MLO_IN_EXTENT1
#if MLO_IN_N_VERT_LOOPS == 1
                       -
                       MLO_FILTER_PAD1
#endif
            ;
            ++sc, gbl_out_scan_off += MLO_OUT_STRIDE, sc_lcl_off += MLO_IN_LCL_WIDTH)
        {

            for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
            {
                uint top_df_off = gbl_out_scan_off + k * MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE;
                _FLOAT mask     = 1;

#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT || MLO_FILTER_SIZE1 - 1 > MLO_OUT_HEIGHT
                top_df_off = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? top_df_off : 0;
                mask       = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                spanReadingOutput(
                    spn, k, (MLO_FILTER_SIZE1 - 1), top_df_off, mask, top_dat, top_df);
#endif
            }

            // processing
            Processing(sc, sc_lcl_off, MLO_FILTER_SIZE1 - 1, 0, pvt_accum, lcl_bot, top_dat);

            // move up output to reduce overfetch
            moveOutputUp(top_dat);
        }

        // non-border input blocks
        for(uint i_loop = 0; i_loop < MLO_N_GENERIC_LOOPS - 1;
            ++i_loop, gbl_in_scan_off += MLO_IN_STRIDE * MLO_IN_EXTENT1)
        {
            barrier(CLK_LOCAL_MEM_FENCE);

#if 1
            readInput(lcl_id, gbl_in_scan_off, MLO_IN_VERT_READS, bot, lcl_bot);
#endif

            // point to the start of the local buffer

            sc_lcl_off = lcl_bot_off;

            for(; sc < (i_loop + 2) * MLO_IN_EXTENT1;
                ++sc, gbl_out_scan_off += MLO_OUT_STRIDE, sc_lcl_off += MLO_IN_LCL_WIDTH)
            {

                for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
                {
                    uint top_df_off =
                        gbl_out_scan_off + k * MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE;
                    _FLOAT mask = 1;

#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT
                    top_df_off = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? top_df_off : 0;
                    mask       = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                    spanReadingOutput(
                        spn, k, (MLO_FILTER_SIZE1 - 1), top_df_off, mask, top_dat, top_df);
#endif
                }

                // processing
                Processing(sc, sc_lcl_off, MLO_FILTER_SIZE1 - 1, 0, pvt_accum, lcl_bot, top_dat);

                // move up output to reduce overfetch
                moveOutputUp(top_dat);
            }
        }

        // bottom border block

        for(int i_loop = 0; i_loop < (MLO_IN_N_VERT_LOOPS - MLO_N_GENERIC_LOOPS - 1);
            ++i_loop, gbl_in_scan_off += MLO_IN_STRIDE * MLO_IN_EXTENT1)
        {

            barrier(CLK_LOCAL_MEM_FENCE);
// read 1 scan line less
// padding processing takes care of the bottom border.

#define MLO_LAST_VERT_READS (MLO_IN_HEIGHT - MLO_IN_EXTENT1 * (MLO_IN_N_VERT_LOOPS - 1))

#if 1
            readInput(lcl_id, gbl_in_scan_off, MLO_LAST_VERT_READS, bot, lcl_bot);
#endif

            // point to the start of the local buffer
            sc_lcl_off = lcl_bot_off;

#pragma unroll 3
            for(; sc < MLO_OUT_HEIGHT - MLO_FILTER_PAD1;
                ++sc, gbl_out_scan_off += MLO_OUT_STRIDE, sc_lcl_off += MLO_IN_LCL_WIDTH)
            {

                for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
                {
                    uint top_df_off =
                        gbl_out_scan_off + k * MLO_OUT_STACKS * MLO_OUT_CHANNEL_STRIDE;
                    _FLOAT mask = 1;

#if MLO_IN_HEIGHT != MLO_OUT_HEIGHT
                    top_df_off = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? top_df_off : 0;
                    mask       = ((sc + MLO_FILTER_PAD1) < MLO_OUT_HEIGHT) ? 1 : 0;
#endif

#if 1
                    spanReadingOutput(
                        spn, k, (MLO_FILTER_SIZE1 - 1), top_df_off, mask, top_dat, top_df);
#endif
                }

                // processing
                Processing(sc, sc_lcl_off, MLO_FILTER_SIZE1 - 1, 0, pvt_accum, lcl_bot, top_dat);

                // move up output to reduce overfetch
                moveOutputUp(top_dat);
            }
        }

        // epilog
        // handling padding

        for(; sc < MLO_IN_HEIGHT; ++sc, sc_lcl_off += MLO_IN_LCL_WIDTH)
        {

            // processing
            Processing(sc,
                       sc_lcl_off,
                       MLO_FILTER_SIZE1 - 1,
                       (MLO_FILTER_PAD1 + 1 - (MLO_IN_HEIGHT - sc)),
                       pvt_accum,
                       lcl_bot,
                       top_dat);
            // move up output to reduce overfetch
            moveOutputUp(top_dat);

        } // for (; sc < MLO_OUT_HEIGHT - MLO_FILTER_PAD1 + 2; ++sc, gbl_out_scan_off +=
          // MLO_OUT_CHANNEL_STRIDE, gbl_in_scan_off += MLO_IN_CHANNEL_STRIDE)

    } // 	for (int b = 0;

    // final summation over all output maps and each filter row
    // this coudl be done with log but it negligeble anyway
    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
    {
        for(uint c = 0; c < MLO_N_LCL_IN_MAPS; ++c)
        {

            for(uint l = 0; l < MLO_FILTER_SIZE1; ++l)
            {

                barrier(CLK_LOCAL_MEM_FENCE);
                for(uint n = 0; n < MLO_FILTER_SIZE0; ++n)
                {
                    uint pvt_off =
                        (k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0 +
                        l * MLO_FILTER_SIZE0 + n;
#if 1
                    lcl[lcl_id * MLO_FILTER_SIZE0 + n] = pvt_accum[pvt_off];
#else
                    lcl[0] = pvt_accum[pvt_off];
#endif
                }

                barrier(CLK_LOCAL_MEM_FENCE);

                if(spn == 0)
                {
                    for(uint s = 0; s < MLO_N_SPANS_PER_SCAN - 1; ++s)
                    {

                        for(uint n = 0; n < MLO_FILTER_SIZE0; ++n)
                        {
                            uint pvt_off =
                                (k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0 +
                                l * MLO_FILTER_SIZE0 + n;
#if 1
                            pvt_accum[pvt_off] += lcl[(lcl_id + s + 1) * MLO_FILTER_SIZE0 + n];
#else
                            pvt_accum[pvt_off] += lcl[0];
#endif
                        }
                    }
                }
            }
        }
    }

    // output
    // inputs are outputs
    // TODO : for more than 1 input

    uint wei_df_off =
        (((ib / MLO_N_BATCH_LOOPS) * MLO_N_OUTPUTS + o_idx + o) * (uint)MLO_WEI_BATCH_STRIDE)
        // this input channel
        + mul24(c_idx, (uint)MLO_WEI_CHANNEL_STRIDE);
    for(uint k = 0; k < MLO_N_LCL_OUT_MAPS; ++k)
    {
        if(spn == 0 && o_idx + o + k * MLO_OUT_STACKS < MLO_N_OUTPUTS && o < MLO_OUT_STACKS)
        {
            for(uint c = 0; c < MLO_N_LCL_IN_MAPS; ++c)
            {
                for(uint i = 0; i < (MLO_FILTER_SIZE1 * MLO_FILTER_SIZE0); ++i)
                {
#if 1
                    weights_df[wei_df_off + k * MLO_OUT_STACKS * MLO_WEI_BATCH_STRIDE +
                               c * MLO_WEI_CHANNEL_STRIDE + i] =
                        pvt_accum[(k * MLO_N_LCL_IN_MAPS + c) * MLO_FILTER_SIZE1 *
                                      MLO_FILTER_SIZE0 +
                                  i];
#endif
                }
            }
        }
    }
}

// final reduction kernel
// add filters over batches
__attribute__((reqd_work_group_size(MLO_UT_GRP_SZ0, 1, 1))) __kernel void
MIOpenCvBwdWrW_rdc(const __global _FLOAT* __restrict weight_df_tmp,
                   __global _FLOAT* __restrict weights_df)
{
    uint gbl_id   = get_global_id(0);
    uint wei_idx0 = gbl_id * MLO_UT_READ_UNIT;

#if MLO_WEI_CHANNEL_STRIDE & (MLO_WEI_CHANNEL_STRIDE - 1)
    uint wei_blk_idx = iDiv(wei_idx0, MLO_WEI_CHANNEL_STRIDE);
    uint wei_idx     = iMod(wei_idx0, wei_blk_idx, MLO_WEI_CHANNEL_STRIDE);
#else
    uint wei_blk_idx = wei_idx0 / MLO_WEI_CHANNEL_STRIDE;
    uint wei_idx     = wei_idx0 & (MLO_WEI_CHANNEL_STRIDE - 1);
#endif

    _FLOAT pvt_accum_wei[MLO_UT_READ_UNIT] = {MLO_UT_READ_UNIT * (_FLOAT)0};
    //	for (uint i = 0; i < MLO_UT_READ_UNIT; ++i)
    //	{
    //		pvt_accum_wei[i] = 0;
    //	}

    int batch_loop = (MLO_BATCH_SZ + (MLO_N_BATCH_LOOPS * MLO_N_LCL_BATCHS) - 1) /
                     (MLO_N_BATCH_LOOPS * MLO_N_LCL_BATCHS);
    for(uint i = 0; i < batch_loop; ++i)
    {
        for(uint j = 0; j < MLO_UT_READ_UNIT; ++j)
        {
            pvt_accum_wei[j] += weight_df_tmp[(wei_blk_idx * MLO_WEI_CHANNEL_STRIDE +
                                               i * MLO_N_OUTPUTS * MLO_WEI_BATCH_STRIDE) +
                                              wei_idx + j];
        }
    }

    for(uint j = 0; j < MLO_UT_READ_UNIT; ++j)
    {
        weights_df[wei_idx0 + j] = pvt_accum_wei[j];
    }
}


cl cleanups

cl cleanups

// Doesn't return 0 so that rays can bounce without bumping.
float sphere_toi(
  const float3 eye,
  const float3 look,

  const float3 center,
  const float radius)
{
  // quadratic coefficients
  float a = dot(look, look);
  float b = 2 * dot(eye - center, look);
  float c = dot(center, center) + dot(eye, eye) - dot(eye, center) - radius * radius;

  // discriminant
  float d = b*b - 4*a*c;

  if (d < 0) {
    return HUGE_VALF;
  }

  float s1 = (sqrt(d) - b) / (2 * a);
  if (s1 <= 0) {
    s1 = HUGE_VALF;
  }

  float s2 = (-sqrt(d) - b) / (2 * a);
  if (s1 < s2 || s2 <= 0) {
    return s1;
  }

  return s2;
}

float3 rotate_vec(
  const float3 vec,
  const float3 axis)
{
  float3 r1 = {2*axis[0]*axis[0] - 1, 2*axis[0]*axis[1], 2*axis[0]*axis[2]};
  float3 r2 = {2*axis[0]*axis[1], 2*axis[1]*axis[1] - 1, 2*axis[1]*axis[2]};
  float3 r3 = {2*axis[0]*axis[2], 2*axis[1]*axis[2], 2*axis[2]*axis[2] - 1};

  float3 r = {dot(r1, vec), dot(r2, vec), dot(r3, vec)};
  return r;
}

typedef struct {
  float4 row1;
  float4 row2;
  float4 row3;
  float4 row4;
} mat4;

float4 vmult(mat4 m, float4 v) {
  return
    (float4)(
      dot(m.row1, v),
      dot(m.row2, v),
      dot(m.row3, v),
      dot(m.row4, v)
    );
}

mat4 screen_to_view(unsigned int w, unsigned int h, float fovy) {
  float aspect = (float)w / (float)h;

  float b = tan(fovy / 2);
  float a = 2 * b / h;
  b = -b;

  mat4 r;
  // We divide both x and y by h, to take aspect ratio into account.
  // An increase in image width will cause wider rays to be shot.
  r.row1 = (float4)(a, 0, 0, b * aspect);
  r.row2 = (float4)(0, a, 0, b);
  r.row3 = (float4)(0, 0, 1, 0);
  r.row4 = (float4)(0, 0, 0, 1);

  return r;
}

mat4 view_to_world(float3 eye, float3 look, float3 up) {
  float4 x = (float4)(cross(look, up), 0);
  float4 y = (float4)(up, 0);
  float4 z = (float4)(look, 0);
  float4 w = (float4)(eye, 1);

  // Change of basis

  mat4 r;
  r.row1.x = x.x;
  r.row2.x = x.y;
  r.row3.x = x.z;
  r.row4.x = x.w;

  r.row1.y = y.x;
  r.row2.y = y.y;
  r.row3.y = y.z;
  r.row4.y = y.w;

  r.row1.z = z.x;
  r.row2.z = z.y;
  r.row3.z = z.z;
  r.row4.z = z.w;

  r.row1.w = w.x;
  r.row2.w = w.y;
  r.row3.w = w.z;
  r.row4.w = w.w;

  return r;
}

typedef struct {
  float r;
  float g;
  float b;
} RGB;

RGB rgb(float3 xyz) {
  RGB r;
  r.r = xyz.x;
  r.g = xyz.y;
  r.b = xyz.z;
  return r;
}

typedef struct { float x, y, z } float3_parse;

float3 pack_float3(float3_parse f) {
  return (float3)(f.x, f.y, f.z);
}

typedef struct {
  float3_parse center;
  float radius;
  float3_parse color;
} Object;

float parse_float(__global const float** data) {
  float r = **data;
  ++*data;
  return r;
}

float3_parse parse_float3(__global const float** data) {
  float3_parse r;
  r.x = parse_float(data);
  r.y = parse_float(data);
  r.z = parse_float(data);
  return r;
}

Object parse_object(__global const float* data) {
  Object r;
  r.center = parse_float3(&data);
  r.radius = parse_float(&data);
  r.color = parse_float3(&data);
  return r;
}

typedef struct {
  float3 origin;
  float3 direction;
} Ray;

void raycast(
  Ray ray,

  __global const float* objects,
  const unsigned int num_objects,

  float* toi,
  Object* collision
) {
  *toi = HUGE_VALF;

  for (unsigned int i = 0; i < num_objects; ++i) {
    Object object = parse_object((Object*)objects + i);
    float this_toi = sphere_toi(ray.origin, ray.direction, pack_float3(object.center), object.radius);

    if (this_toi >= *toi) {
      continue;
    }

    *toi = this_toi;
    *collision = object;
  }
}

float3 raytrace(
  Ray ray,

  __global const float* objects,
  const unsigned int num_objects
) {
  float toi;
  Object collision;

  raycast(ray, objects, num_objects, &toi, &collision);

  if (toi == HUGE_VALF) {
    return (float3)(0, 0, 0);
  }

  return pack_float3(collision.color);
}

__kernel void render(
  const unsigned int window_width,
  const unsigned int window_height,

  const float fovy,
  float3 eye,
  const float3 look,
  const float3 up,

  __global const float* objects,
  const unsigned int num_objects,

  __global RGB * output)
{
  int id = get_global_id(0);

  const int x_pix = id % window_width;
  const int y_pix = id / window_width;

  float4 world_pos =
    vmult(view_to_world(eye, look, up),
    vmult(screen_to_view(window_width, window_height, fovy),
    (float4)(x_pix, y_pix, 1, 1)
  ));

  Ray ray;
  ray.origin = eye;
  ray.direction = normalize((world_pos / world_pos.w).xyz - eye);

  output[id] = rgb(raytrace(ray, objects, num_objects));
}

// Doesn't return 0 so that rays can bounce without bumping.
float sphere_toi(
  const float3 eye,
  const float3 look,

  const float3 center,
  const float radius)
{
  // quadratic coefficients
  float a = dot(look, look);
  float b = 2 * dot(eye - center, look);
  float c = dot(center, center) + dot(eye, eye) - dot(eye, center) - radius * radius;

  // discriminant
  float d = b*b - 4*a*c;

  if (d < 0) {
    return HUGE_VALF;
  }

  float s1 = (sqrt(d) - b) / (2 * a);
  if (s1 <= 0) {
    s1 = HUGE_VALF;
  }

  float s2 = (-sqrt(d) - b) / (2 * a);
  if (s1 < s2 || s2 <= 0) {
    return s1;
  }

  return s2;
}

float3 rotate_vec(
  const float3 vec,
  const float3 axis)
{
  float3 r1 = {2*axis[0]*axis[0] - 1, 2*axis[0]*axis[1], 2*axis[0]*axis[2]};
  float3 r2 = {2*axis[0]*axis[1], 2*axis[1]*axis[1] - 1, 2*axis[1]*axis[2]};
  float3 r3 = {2*axis[0]*axis[2], 2*axis[1]*axis[2], 2*axis[2]*axis[2] - 1};

  float3 r = {dot(r1, vec), dot(r2, vec), dot(r3, vec)};
  return r;
}

typedef struct {
  float4 row1;
  float4 row2;
  float4 row3;
  float4 row4;
} mat4;

float4 vmult(mat4 m, float4 v) {
  return
    (float4)(
      dot(m.row1, v),
      dot(m.row2, v),
      dot(m.row3, v),
      dot(m.row4, v)
    );
}

mat4 screen_to_view(unsigned int w, unsigned int h, float fovy) {
  float aspect = (float)w / (float)h;

  float b = tan(fovy / 2);
  float a = 2 * b / h;
  b = -b;

  mat4 r;
  // We divide both x and y by h, to take aspect ratio into account.
  // An increase in image width will cause wider rays to be shot.
  r.row1 = (float4)(a, 0, 0, b * aspect);
  r.row2 = (float4)(0, a, 0, b);
  r.row3 = (float4)(0, 0, 1, 0);
  r.row4 = (float4)(0, 0, 0, 1);

  return r;
}

mat4 view_to_world(float3 eye, float3 look, float3 up) {
  float4 x = (float4)(cross(look, up), 0);
  float4 y = (float4)(up, 0);
  float4 z = (float4)(look, 0);
  float4 w = (float4)(eye, 1);

  // Change of basis

  mat4 r;
  r.row1.x = x.x;
  r.row2.x = x.y;
  r.row3.x = x.z;
  r.row4.x = x.w;

  r.row1.y = y.x;
  r.row2.y = y.y;
  r.row3.y = y.z;
  r.row4.y = y.w;

  r.row1.z = z.x;
  r.row2.z = z.y;
  r.row3.z = z.z;
  r.row4.z = z.w;

  r.row1.w = w.x;
  r.row2.w = w.y;
  r.row3.w = w.z;
  r.row4.w = w.w;

  return r;
}

typedef struct {
  float r;
  float g;
  float b;
} RGB;

RGB rgb(float3 xyz) {
  RGB r;
  r.r = xyz.x;
  r.g = xyz.y;
  r.b = xyz.z;
  return r;
}

typedef struct { float x, y, z } float3_parse;

float3 pack_float3(float3_parse f) {
  return (float3)(f.x, f.y, f.z);
}

typedef struct {
  float3_parse center;
  float radius;
  float3_parse color;
} Object;

float parse_float(__global const float** data) {
  float r = **data;
  ++*data;
  return r;
}

float3_parse parse_float3(__global const float** data) {
  float3_parse r;
  r.x = parse_float(data);
  r.y = parse_float(data);
  r.z = parse_float(data);
  return r;
}

Object parse_object(__global const float* data) {
  Object r;
  r.center = parse_float3(&data);
  r.radius = parse_float(&data);
  r.color = parse_float3(&data);
  return r;
}

float3 raytrace(
  float3 eye,
  float3 direction,

  __global const float* objects,
  const unsigned int num_objects
) {
  float toi = HUGE_VALF;
  float3 r = (float3)(0, 0, 0);

  for (unsigned int i = 0; i < num_objects; ++i) {
    Object object = parse_object((Object*)objects + i);
    float this_toi = sphere_toi(eye, direction, pack_float3(object.center), object.radius);

    if (this_toi >= toi) {
      continue;
    }

    toi = this_toi;
    r = pack_float3(object.color);
  }

  return r;
}

__kernel void render(
  const unsigned int window_width,
  const unsigned int window_height,

  const float fovy,
  float3 eye,
  const float3 look,
  const float3 up,

  __global const float* objects,
  const unsigned int num_objects,

  __global RGB * output)
{
  int id = get_global_id(0);

  const int x_pix = id % window_width;
  const int y_pix = id / window_width;

  float4 world_pos =
    vmult(view_to_world(eye, look, up),
    vmult(screen_to_view(window_width, window_height, fovy),
    (float4)(x_pix, y_pix, 1, 1)
  ));

  float3 ray = normalize((world_pos / world_pos.w).xyz - eye);

  output[id] = rgb(raytrace(eye, ray, objects, num_objects));
}