ikawrakow/ik_llama.cpp
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Bitnet: 2.25 bpw version

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Just scaler and AVX2 for now.
PP-512 is even faster (325 t/s on the Ryzn-7950X, 404 t/s on
Ryzen-5975WX). We lose ~6-7% for TG due to being memory bound and
the model being 10% larger.
This commit is contained in:
Kawrakow
2024-06-18 12:00:16 +03:00
parent 68741281e5
commit 39982764d7
3 changed files with 25 additions and 81 deletions
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55
iqk-quantize.cpp
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@@ -159,25 +159,14 @@ void IQ1BNQuantizer::quantize_one_row_2bn(const float * src, block_iq2_bn * y, i
const int nblock = n_per_row/QK_IQ1BN;
const auto& iq1bn = get_iq1bn_data();
auto max_in_row = row_max(n_per_row, src);
ggml_half * d = (ggml_half *)y;
*d = GGML_FP32_TO_FP16(max_in_row);
auto ql = (uint8_t *)(d + 2);
auto qh = ql + QK_IQ1BN/8;
std::memset(ql, 0, QK_IQ1BN/8);
std::memset(qh, 0, QK_IQ1BN/16);
auto xb = src;
auto extra = quantize_one_block_1bn(iq1bn, xb, L, ql, qh);
*(uint16_t *)(d + 1) = extra;
ggml_half dh = GGML_FP32_TO_FP16(max_in_row);
constexpr int Nj = QK_IQ1BN/4;
for (int ib = 1; ib < nblock; ++ib) {
xb = src + QK_IQ1BN*ib;
for (int ib = 0; ib < nblock; ++ib) {
y[ib].d = dh;
auto xb = src + QK_IQ1BN*ib;
for (int j = 0; j < QK_IQ1BN; ++j) {
L[j] = fabsf(xb[j]) < 1e-6f ? 1 : xb[j] < 0 ? 0 : 2;
}
@@ -258,22 +247,11 @@ void dequantize_row_iq2_bn(const block_iq2_bn * x, float * y, int64_t k) {
assert(k%QK_IQ1BN == 0);
int nblock = k / QK_IQ1BN;
float d = GGML_FP16_TO_FP32(*(const ggml_half *)x);
auto * extra_ptr = (const uint16_t *)x;
auto extra = extra_ptr[1];
auto ql = (const uint8_t *)(extra_ptr + 2);
auto qh = ql + QK_IQ1BN/8;
for (int l = 0; l < QK_IQ1BN/8; ++l) {
uint16_t idx = ql[l] | ((qh[l/2] << (8 - 4*(l%2))) & 0x0f00);
uint16_t val = iq1bn_grid_u16[idx];
float dls = extra & (1 << l) ? -d : d;
for (int j = 0; j < 8; ++j) y[j] = dls * (((val >> 2*j) & 3) - 1);
y += 8;
}
float d = GGML_FP16_TO_FP32(x[0].d);
auto m = -d;
auto d1 = d, d2 = d*0.25f, d3 = d2*0.25f, d4 = d3*0.25f;
constexpr int Nj = QK_IQ1BN/4;
for (int i = 1; i < nblock; ++i) {
for (int i = 0; i < nblock; ++i) {
for (int j = 0; j < Nj; ++j) {
y[j+ 0] = d1*(x[i].qs[j] & 0x03) + m;
y[j+1*Nj] = d2*(x[i].qs[j] & 0x0c) + m;
@@ -396,25 +374,10 @@ void ggml_vec_dot_iq2_bn_q8_K64(int n, float * s, size_t bs, const void * vx, si
float sumf = 0;
float d = GGML_FP16_TO_FP32(*(const ggml_half *)x);
auto * extra_ptr = (const uint16_t *)x;
auto extra = extra_ptr[1];
auto ql = (const uint8_t *)(extra_ptr + 2);
auto qh = ql + QK_IQ1BN/8;
auto q8 = y[0].qs;
int sumi = 0;
for (int k = 0; k < QK_IQ1BN/8; ++k) {
uint16_t idx = ql[k] | ((qh[k/2] << (8 - 4*(k%2))) & 0x0f00);
uint16_t val = iq1bn_grid_u16[idx];
int s = 0;
for (int j = 0; j < 8; ++j) s += q8[j] * (((val >> 2*j) & 3) - 1);
sumi += extra & (1 << k) ? -s : s;
q8 += 8;
}
sumf += y[0].d * sumi;
float d = GGML_FP16_TO_FP32(x[0].d);
for (int i = 1; i < nblock; ++i) {
q8 = y[i].qs;
for (int i = 0; i < nblock; ++i) {
auto q8 = y[i].qs;
int s0 = 0, s1 = 0, s2 = 0, s3 = 0, s4 = 0;
for (int j = 0; j < Nj; ++j) {
s1 += q8[j+ 0] * (x[i].qs[j] & 0x03);