vbatts/llama.cpp
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data b cache example, slower than original

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Eve 2024-12-29 17:05:19 -05:00
parent 860159c10d
commit 64bb149d53
1 changed files with 14 additions and 11 deletions
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25
ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q6_k.comp
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@ -12,6 +12,7 @@ layout (constant_id = 1) const uint NUM_ROWS = 1;
shared FLOAT_TYPE tmpsh[NUM_ROWS][BLOCK_SIZE]; shared FLOAT_TYPE tmpsh[NUM_ROWS][BLOCK_SIZE];
shared FLOAT_TYPE sccache[BLOCK_SIZE/16][16]; shared FLOAT_TYPE sccache[BLOCK_SIZE/16][16];
shared block_q6_K_packed16 blkcache[BLOCK_SIZE/16]; shared block_q6_K_packed16 blkcache[BLOCK_SIZE/16];
shared B_TYPE bycache[BLOCK_SIZE/16][QUANT_K];
void compute_outputs(const uint32_t first_row, const uint32_t num_rows) { void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
uint a_offset, b_offset, d_offset; uint a_offset, b_offset, d_offset;
@ -34,7 +35,6 @@ void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
const uint ql_offset = 64*v_im + l0; const uint ql_offset = 64*v_im + l0;
const uint qh_offset = 32*v_im + l0; const uint qh_offset = 32*v_im + l0;
const uint s_offset = 8*v_im + is; const uint s_offset = 8*v_im + is;
const uint y_offset = 128*v_im + l0;
const uint bcs_offset = (itid%2 == 1) ? 8 : 0; const uint bcs_offset = (itid%2 == 1) ? 8 : 0;
FLOAT_TYPE temp[NUM_ROWS]; FLOAT_TYPE temp[NUM_ROWS];
@ -45,12 +45,16 @@ void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
[[unroll]] for (uint i0 = 0; i0 < num_blocks_per_row; i0 += it_size) { [[unroll]] for (uint i0 = 0; i0 < num_blocks_per_row; i0 += it_size) {
uint i = i0 + ix; // 16 thread group specific counter uint i = i0 + ix; // 16 thread group specific counter
const uint y_idx = i * QUANT_K + y_offset; const uint y_idx = i0 * QUANT_K;
const int blim = min(int(num_blocks_per_row) - int(i0), 4);
B_TYPE_VEC4 by0 = data_b_v4[(b_offset + y_idx) / 4]; // assume 64 threads
B_TYPE_VEC4 by32 = data_b_v4[(b_offset + y_idx) / 4 + 8]; [[unroll]] for (int n = 0; n < blim; ++n) {
B_TYPE_VEC4 by64 = data_b_v4[(b_offset + y_idx) / 4 + 16]; [[unroll]] for (int l = 0; l < 4; ++l) {
B_TYPE_VEC4 by96 = data_b_v4[(b_offset + y_idx) / 4 + 24]; bycache[n][tid + 64*l] = data_b[b_offset + y_idx + QUANT_K*n + tid + 64*l];
}
}
barrier();
uint ibi = first_row*num_blocks_per_row; uint ibi = first_row*num_blocks_per_row;
[[unroll]] for (uint n = 0; n < num_rows; ++n) { [[unroll]] for (uint n = 0; n < num_rows; ++n) {
@ -59,7 +63,6 @@ void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
// cache full superblock into shared memory with coalesced reads // cache full superblock into shared memory with coalesced reads
// we assume 64 threads here! // we assume 64 threads here!
const int blim = min(int(num_blocks_per_row) - int(i0), 4);
// this is required as this loop is super sensitive to unrolling with hardcoded 4 // this is required as this loop is super sensitive to unrolling with hardcoded 4
if (blim == 4) { if (blim == 4) {
if (tid < 52) { if (tid < 52) {
@ -109,10 +112,10 @@ void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
FLOAT_TYPE sum[4] = {0, 0, 0, 0}; FLOAT_TYPE sum[4] = {0, 0, 0, 0};
[[unroll]] for (uint l = 0; l < 4; ++l) { [[unroll]] for (uint l = 0; l < 4; ++l) {
sum[0] = fma(FLOAT_TYPE(by0[l]), FLOAT_TYPE(int8_t(q0[l]) - 32), sum[0]); sum[0] = fma(FLOAT_TYPE(bycache[ix][128*v_im + l0 + l]), FLOAT_TYPE(int8_t(q0[l]) - 32), sum[0]);
sum[1] = fma(FLOAT_TYPE(by32[l]), FLOAT_TYPE(int8_t(q1[l]) - 32), sum[1]); sum[1] = fma(FLOAT_TYPE(bycache[ix][128*v_im + l0 + 32 + l]), FLOAT_TYPE(int8_t(q1[l]) - 32), sum[1]);
sum[2] = fma(FLOAT_TYPE(by64[l]), FLOAT_TYPE(int8_t(q2[l]) - 32), sum[2]); sum[2] = fma(FLOAT_TYPE(bycache[ix][128*v_im + l0 + 64 + l]), FLOAT_TYPE(int8_t(q2[l]) - 32), sum[2]);
sum[3] = fma(FLOAT_TYPE(by96[l]), FLOAT_TYPE(int8_t(q3[l]) - 32), sum[3]); sum[3] = fma(FLOAT_TYPE(bycache[ix][128*v_im + l0 + 96 + l]), FLOAT_TYPE(int8_t(q3[l]) - 32), sum[3]);
} }
[[unroll]] for (uint l = 0; l < 4; ++l) [[unroll]] for (uint l = 0; l < 4; ++l)