vulkan: multi-row k quants (#10846)
* multi row k quant shaders! * better row selection * more row choices * readjust row selection * rm_kq=2 by default
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6 changed files with 472 additions and 367 deletions
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@ -7,21 +7,15 @@
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layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
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layout (constant_id = 0) const uint BLOCK_SIZE = 32;
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layout (constant_id = 1) const uint NUM_ROWS = 1;
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shared FLOAT_TYPE tmp[BLOCK_SIZE];
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void main() {
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const uint row = gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z;
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if (row >= p.stride_d) {
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return;
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}
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shared FLOAT_TYPE tmpsh[NUM_ROWS][BLOCK_SIZE];
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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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const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row;
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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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@ -42,69 +36,95 @@ void main() {
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const uint s_offset = 8*v_im + is;
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const uint y_offset = 128*v_im + l0;
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FLOAT_TYPE temp = FLOAT_TYPE(0.0); // partial sum for thread in warp
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FLOAT_TYPE temp[NUM_ROWS];
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[[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
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temp[i] = FLOAT_TYPE(0);
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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 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 scales[4];
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scales[0] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0]);
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scales[1] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2]);
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scales[2] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4]);
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scales[3] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6]);
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uint32_t ql0_u32 = uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2]) | (uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2 + 1]) << 16);
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uint32_t ql32_u32 = uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2 + 16]) | (uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2 + 17]) << 16);
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uint32_t ql0_u32_lo4 = ql0_u32 & 0x0F0F0F0F;
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uint32_t ql0_u32_hi4 = (ql0_u32 >> 4) & 0x0F0F0F0F;
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uint32_t ql32_u32_lo4 = ql32_u32 & 0x0F0F0F0F;
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uint32_t ql32_u32_hi4 = (ql32_u32 >> 4) & 0x0F0F0F0F;
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uint32_t qh_u32 = uint32_t(data_a_packed16[ib0 + i].qh[qh_offset / 2]) | (uint32_t(data_a_packed16[ib0 + i].qh[qh_offset / 2 + 1]) << 16);
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uint32_t qh0_u32 = (qh_u32 & 0x03030303) << 4;
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uint32_t qh2_u32 = (qh_u32 & 0x0C0C0C0C) << 2;
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uint32_t qh4_u32 = (qh_u32 & 0x30303030) << 0;
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uint32_t qh6_u32 = (qh_u32 & 0xC0C0C0C0) >> 2;
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uint32_t q0_u32 = ql0_u32_lo4 | qh0_u32;
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uint32_t q1_u32 = ql32_u32_lo4 | qh2_u32;
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uint32_t q2_u32 = ql0_u32_hi4 | qh4_u32;
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uint32_t q3_u32 = ql32_u32_hi4 | qh6_u32;
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uvec4 q0 = uvec4(unpack8(q0_u32));
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uvec4 q1 = uvec4(unpack8(q1_u32));
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uvec4 q2 = uvec4(unpack8(q2_u32));
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uvec4 q3 = uvec4(unpack8(q3_u32));
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const uint y_idx = i * QUANT_K + y_offset;
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B_TYPE_VEC4 by0 = data_b_v4[(b_offset + y_idx) / 4];
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B_TYPE_VEC4 by32 = data_b_v4[(b_offset + y_idx) / 4 + 8];
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B_TYPE_VEC4 by64 = data_b_v4[(b_offset + y_idx) / 4 + 16];
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B_TYPE_VEC4 by96 = data_b_v4[(b_offset + y_idx) / 4 + 24];
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FLOAT_TYPE sum = FLOAT_TYPE(0.0);
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[[unroll]] for (int l = 0; l < 4; ++l) {
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sum = fma(FLOAT_TYPE(by0[l]) * scales[0], FLOAT_TYPE(int8_t(q0[l]) - 32),
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fma(FLOAT_TYPE(by32[l]) * scales[1], FLOAT_TYPE(int8_t(q1[l]) - 32),
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fma(FLOAT_TYPE(by64[l]) * scales[2], FLOAT_TYPE(int8_t(q2[l]) - 32),
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fma(FLOAT_TYPE(by96[l]) * scales[3], FLOAT_TYPE(int8_t(q3[l]) - 32), sum))));
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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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const FLOAT_TYPE d = FLOAT_TYPE(data_a[ib0 + i].d);
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FLOAT_TYPE scales[4];
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scales[0] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0]);
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scales[1] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2]);
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scales[2] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4]);
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scales[3] = FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6]);
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uint32_t ql0_u32 = uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2]) | (uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2 + 1]) << 16);
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uint32_t ql32_u32 = uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2 + 16]) | (uint32_t(data_a_packed16[ib0 + i].ql[ql_offset / 2 + 17]) << 16);
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uint32_t ql0_u32_lo4 = ql0_u32 & 0x0F0F0F0F;
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uint32_t ql0_u32_hi4 = (ql0_u32 >> 4) & 0x0F0F0F0F;
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uint32_t ql32_u32_lo4 = ql32_u32 & 0x0F0F0F0F;
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uint32_t ql32_u32_hi4 = (ql32_u32 >> 4) & 0x0F0F0F0F;
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uint32_t qh_u32 = uint32_t(data_a_packed16[ib0 + i].qh[qh_offset / 2]) | (uint32_t(data_a_packed16[ib0 + i].qh[qh_offset / 2 + 1]) << 16);
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uint32_t qh0_u32 = (qh_u32 & 0x03030303) << 4;
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uint32_t qh2_u32 = (qh_u32 & 0x0C0C0C0C) << 2;
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uint32_t qh4_u32 = (qh_u32 & 0x30303030) << 0;
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uint32_t qh6_u32 = (qh_u32 & 0xC0C0C0C0) >> 2;
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uint32_t q0_u32 = ql0_u32_lo4 | qh0_u32;
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uint32_t q1_u32 = ql32_u32_lo4 | qh2_u32;
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uint32_t q2_u32 = ql0_u32_hi4 | qh4_u32;
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uint32_t q3_u32 = ql32_u32_hi4 | qh6_u32;
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uvec4 q0 = uvec4(unpack8(q0_u32));
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uvec4 q1 = uvec4(unpack8(q1_u32));
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uvec4 q2 = uvec4(unpack8(q2_u32));
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uvec4 q3 = uvec4(unpack8(q3_u32));
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FLOAT_TYPE sum = FLOAT_TYPE(0.0);
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[[unroll]] for (int l = 0; l < 4; ++l) {
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sum = fma(FLOAT_TYPE(by0[l]) * scales[0], FLOAT_TYPE(int8_t(q0[l]) - 32),
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fma(FLOAT_TYPE(by32[l]) * scales[1], FLOAT_TYPE(int8_t(q1[l]) - 32),
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fma(FLOAT_TYPE(by64[l]) * scales[2], FLOAT_TYPE(int8_t(q2[l]) - 32),
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fma(FLOAT_TYPE(by96[l]) * scales[3], FLOAT_TYPE(int8_t(q3[l]) - 32), sum))));
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}
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temp[n] += sum * d;
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}
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temp += sum * d;
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}
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tmp[gl_LocalInvocationID.x] = temp;
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// sum up partial sums and write back result
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[[unroll]] for (uint n = 0; n < num_rows; ++n) {
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tmpsh[n][tid] = temp[n];
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}
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barrier();
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[[unroll]] for (uint s = gl_WorkGroupSize.x/2; s > 0; s >>= 1) {
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[[unroll]] for (uint s = BLOCK_SIZE/2; s > 0; s >>= 1) {
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if (tid < s) {
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tmp[tid] += tmp[tid + s];
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[[unroll]] for (uint n = 0; n < num_rows; ++n) {
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tmpsh[n][tid] += tmpsh[n][tid + s];
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}
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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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[[unroll]] for (uint n = 0; n < num_rows; ++n) {
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data_d[d_offset + first_row + n] = D_TYPE(tmpsh[n][0]);
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}
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}
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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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