diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp index 4cb292380c72f..fb73baa91d8f5 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp @@ -7,35 +7,86 @@ layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in; FLOAT_TYPE temp[NUM_COLS][NUM_ROWS]; -void calc_superblock(const uint a_offset, const uint b_offset, const uint ib32, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows) { +// ------------------ calc_superblock (final optimized version) ------------------ +void calc_superblock(const uint a_offset, const uint b_offset, const uint ib32, const uint i, + const uint num_blocks_per_row, const uint first_row, const uint num_rows) { + // Compute starting index in matrix B for this superblock const uint y_idx = i * QUANT_K + 32 * ib32; - uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i; + + // Precompute indices for quantization lookup tables + const uint qh_base = 2 * ib32; + const uint qs_base = 4 * ib32; + const uint sc_index = ib32 / 2; + const uint sc_shift = 6 * (ib32 & 1); + + // Loop over rows in the superblock [[unroll]] for (uint n = 0; n < num_rows; ++n) { + // Load per-block scales and shift for quantization const uint16_t[4] scales = data_a[ibi].scales; const u16vec4 s = u16vec4(scales[0], scales[1], scales[2], scales[3]) >> 12; const float d = float(unpackHalf2x16(s.x | (s.y << 4) | (s.z << 8) | (s.w << 12)).x); - - const uint sc = data_a[ibi].scales[ib32 / 2] >> (6 * (ib32 & 1)); + const uint sc = data_a[ibi].scales[sc_index] >> sc_shift; + + // Temporary caches for decoding + FLOAT_TYPE dl_cache[4]; + uint16_t gvf_cache[4]; + float delta_cache[4]; + + // Precompute the multiplier and lookup values for 4 sub-blocks [[unroll]] for (uint l = 0; l < 4; ++l) { - const uint qh = data_a[ibi].qh[2 * ib32 + l / 2] >> (4 * (l&1)); - const uint qs = data_a[ibi].qs[4 * ib32 + l]; - const float delta = ((qh & 8) != 0) ? -IQ1M_DELTA : IQ1M_DELTA; - const float dl = d * (2 * bitfieldExtract(sc, 3 * int(l / 2), 3) + 1); - - const int16_t grid = int16_t(iq1s_grid[qs | ((qh & 7) << 8)]); - - [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) { - vec4 b0 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 0]); - vec4 b4 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 1]); - - FLOAT_TYPE sum = FLOAT_TYPE(0.0); - [[unroll]] for (int k = 0; k < 4; ++k) { - sum = fma(FLOAT_TYPE(b0[k]), bitfieldExtract(grid, 2 * k, 2) + delta, - fma(FLOAT_TYPE(b4[k]), bitfieldExtract(grid, 8 + 2 * k, 2) + delta, sum)); - } - temp[j][n] = fma(dl, sum, temp[j][n]); + dl_cache[l] = FLOAT_TYPE(d * (2 * bitfieldExtract(sc, 3 * int(l / 2), 3) + 1)); + const uint qh = data_a[ibi].qh[qh_base + l / 2] >> (4 * (l & 1)); + const uint qs = data_a[ibi].qs[qs_base + l]; + gvf_cache[l] = iq1s_grid[qs | ((qh & 7) << 8)]; + delta_cache[l] = ((qh & 8) != 0) ? -IQ1M_DELTA : IQ1M_DELTA; + } + + // Loop over columns of the output + [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) { + // Compute base index for matrix B + const uint base_b_idx = (j * p.batch_stride_b + b_offset + y_idx) / 4; + vec4 b_vals[8]; + + // Load 8 vec4 values from matrix B + [[unroll]] for (int idx = 0; idx < 8; ++idx) { + b_vals[idx] = vec4(data_b_v4[base_b_idx + idx]); + } + + FLOAT_TYPE col_sum = FLOAT_TYPE(0.0); + + // Loop over sub-blocks + [[unroll]] for (uint l = 0; l < 4; ++l) { + const uint16_t grid = gvf_cache[l]; + const float dl = dl_cache[l]; + + // Decode 8 2-bit fbits from gvf_cache + float f0 = float(bitfieldExtract(grid, 0, 2)); + float f1 = float(bitfieldExtract(grid, 2, 2)); + float f2 = float(bitfieldExtract(grid, 4, 2)); + float f3 = float(bitfieldExtract(grid, 6, 2)); + float f4 = float(bitfieldExtract(grid, 8, 2)); + float f5 = float(bitfieldExtract(grid, 10, 2)); + float f6 = float(bitfieldExtract(grid, 12, 2)); + float f7 = float(bitfieldExtract(grid, 14, 2)); + + // Pack into vec4 for vectorized FMA + const vec4 fbits_v0 = vec4(f0, f1, f2, f3); + const vec4 fbits_v1 = vec4(f4, f5, f6, f7); + const vec4 delta_v = vec4(delta_cache[l]); + + // Vectorized fused multiply-add + vec4 sum_v = fma(b_vals[2*l + 0], fbits_v0 + delta_v, vec4(0.0)); + sum_v = fma(b_vals[2*l + 1], fbits_v1 + delta_v, sum_v); + + // Horizontal add to get scalar sum + FLOAT_TYPE sum = sum_v.x + sum_v.y + sum_v.z + sum_v.w; + + // Accumulate to column sum + col_sum = fma(dl, sum, col_sum); } + // Write result to temporary buffer + temp[j][n] += col_sum; } ibi += num_blocks_per_row; } @@ -44,39 +95,39 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint ib32, 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; - - // 8 threads are used to process each block - const uint blocks_per_wg = gl_WorkGroupSize.x/8; + const uint blocks_per_wg = gl_WorkGroupSize.x / 8; const uint tid = gl_LocalInvocationID.x; - const uint itid = tid % 8; // 0...7 + const uint itid = tid % 8; const uint ix = tid / 8; - [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) { - [[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) { + // Initialize temporary storage + [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) + [[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) temp[j][i] = FLOAT_TYPE(0); - } - } + // Loop over blocks assigned to this thread [[unroll]] for (uint i = ix; i < num_blocks_per_row; i += blocks_per_wg) calc_superblock(a_offset, b_offset, itid, i, num_blocks_per_row, first_row, num_rows); + // Reduce results from temporary buffer to output reduce_result(temp, d_offset, first_row, num_rows, tid); } void main() { + // Compute first row for this workgroup const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z); + // Initialize shared memory for quantization lookups init_iq_shmem(gl_WorkGroupSize); - // 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); - } + // Early exit if out-of-bounds + if (first_row >= p.stride_d) + return; + + // Number of rows to process for this workgroup + const uint rows_to_process = min(NUM_ROWS, p.stride_d - first_row); + + // Compute outputs for assigned rows + compute_outputs(first_row, rows_to_process); }