#![cfg(all(feature = "simd-avx512", target_arch = "x86_64"))]
use core::arch::x86_64::*;
use crate::error::{QuantError, QuantResult};
use crate::simd::avx512::util::{f16_to_f32, hsum_f32_avx512};
use crate::traits::QuantKernel;
use crate::types::QuantTensor;
pub const BLOCK_SIZE: usize = 32;
pub const BLOCK_BYTES: usize = 34;
pub struct Q8_0Avx512;
impl QuantKernel for Q8_0Avx512 {
fn dequant_block(&self, block: &[u8], output: &mut [f32]) -> QuantResult<()> {
if block.len() < BLOCK_BYTES {
return Err(QuantError::BufferTooSmall {
needed: BLOCK_BYTES,
available: block.len(),
});
}
if output.len() < BLOCK_SIZE {
return Err(QuantError::BufferTooSmall {
needed: BLOCK_SIZE,
available: output.len(),
});
}
unsafe { dequant_block_avx512(block, output) }
Ok(())
}
fn gemv(
&self,
quant_matrix: &QuantTensor,
input: &[f32],
output: &mut [f32],
) -> QuantResult<()> {
let n_rows = quant_matrix.shape[0];
let n_cols = if quant_matrix.shape.len() > 1 {
quant_matrix.shape[1]
} else {
quant_matrix.n_elements() / n_rows
};
if input.len() < n_cols {
return Err(QuantError::DimensionMismatch {
expected: n_cols,
got: input.len(),
});
}
if output.len() < n_rows {
return Err(QuantError::DimensionMismatch {
expected: n_rows,
got: output.len(),
});
}
let blocks_per_row = n_cols.div_ceil(BLOCK_SIZE);
let row_bytes = blocks_per_row * BLOCK_BYTES;
for (row, out) in output.iter_mut().enumerate().take(n_rows) {
let row_start = row * row_bytes;
*out = unsafe {
gemv_row_avx512(
&quant_matrix.data[row_start..row_start + row_bytes],
input,
blocks_per_row,
n_cols,
)
};
}
Ok(())
}
fn gemm(
&self,
quant_matrix: &QuantTensor,
input: &[f32],
output: &mut [f32],
m: usize,
n: usize,
k: usize,
) -> QuantResult<()> {
for row in 0..m {
let input_row = &input[row * k..(row + 1) * k];
let output_row = &mut output[row * n..(row + 1) * n];
self.gemv(quant_matrix, input_row, output_row)?;
}
Ok(())
}
fn block_size(&self) -> usize {
BLOCK_SIZE
}
fn block_bytes(&self) -> usize {
BLOCK_BYTES
}
fn name(&self) -> &'static str {
"Q8_0"
}
}
#[target_feature(enable = "avx512f")]
unsafe fn dequant_block_avx512(block: &[u8], output: &mut [f32]) {
let d = f16_to_f32(block);
let vd = _mm512_set1_ps(d);
let q1 = _mm_loadu_si128(block.as_ptr().add(2) as *const __m128i); let q1_i32 = _mm512_cvtepi8_epi32(q1); let q1_f32 = _mm512_cvtepi32_ps(q1_i32);
let w1 = _mm512_mul_ps(q1_f32, vd);
let q2 = _mm_loadu_si128(block.as_ptr().add(18) as *const __m128i); let q2_i32 = _mm512_cvtepi8_epi32(q2);
let q2_f32 = _mm512_cvtepi32_ps(q2_i32);
let w2 = _mm512_mul_ps(q2_f32, vd);
let ptr = output.as_mut_ptr();
_mm512_storeu_ps(ptr, w1);
_mm512_storeu_ps(ptr.add(16), w2);
}
#[target_feature(enable = "avx512f")]
unsafe fn gemv_row_avx512(
row_data: &[u8],
input: &[f32],
blocks_per_row: usize,
n_cols: usize,
) -> f32 {
let mut row_sum = 0.0f32;
for blk in 0..blocks_per_row {
let block_offset = blk * BLOCK_BYTES;
let block = &row_data[block_offset..block_offset + BLOCK_BYTES];
let input_offset = blk * BLOCK_SIZE;
let d = f16_to_f32(block);
let remaining = n_cols.saturating_sub(input_offset);
if remaining >= BLOCK_SIZE {
let q1 = _mm_loadu_si128(block.as_ptr().add(2) as *const __m128i);
let q2 = _mm_loadu_si128(block.as_ptr().add(18) as *const __m128i);
let vd = _mm512_set1_ps(d);
let inp_ptr = input.as_ptr().add(input_offset);
let w1 = _mm512_mul_ps(_mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(q1)), vd);
let i1 = _mm512_loadu_ps(inp_ptr);
let acc = _mm512_mul_ps(w1, i1);
let w2 = _mm512_mul_ps(_mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(q2)), vd);
let i2 = _mm512_loadu_ps(inp_ptr.add(16));
let acc = _mm512_fmadd_ps(w2, i2, acc);
row_sum += hsum_f32_avx512(acc);
} else if remaining > 0 {
let mut partial_sum = 0.0f32;
for i in 0..remaining {
let q = *block.get_unchecked(2 + i) as i8;
partial_sum += q as f32 * input[input_offset + i];
}
row_sum += partial_sum * d;
}
}
row_sum
}
#[cfg(all(test, target_arch = "x86_64", feature = "simd-avx512"))]
mod tests {
use super::*;
use crate::reference::q8_0::Q8_0Ref;
fn make_q8_0_block(scale: f32, values: &[i8; 32]) -> Vec<u8> {
let mut block = Vec::with_capacity(BLOCK_BYTES);
let d_bits = half::f16::from_f32(scale).to_bits();
block.extend_from_slice(&d_bits.to_le_bytes());
for &v in values {
block.push(v as u8);
}
block
}
fn make_tensor(block: Vec<u8>, n_cols: usize) -> QuantTensor {
QuantTensor::new(block, vec![1, n_cols], oxillama_gguf::GgufTensorType::Q8_0)
}
#[test]
#[cfg_attr(not(target_feature = "avx512f"), ignore)]
fn test_dequant_matches_reference() {
if !std::arch::is_x86_feature_detected!("avx512f") {
return;
}
let mut values = [0i8; 32];
for (i, v) in values.iter_mut().enumerate() {
*v = (i as i8).wrapping_sub(16);
}
let block = make_q8_0_block(0.5, &values);
let mut out_avx512 = vec![0.0f32; 32];
let mut out_ref = vec![0.0f32; 32];
Q8_0Avx512.dequant_block(&block, &mut out_avx512).unwrap();
Q8_0Ref.dequant_block(&block, &mut out_ref).unwrap();
for (i, (&a, &r)) in out_avx512.iter().zip(out_ref.iter()).enumerate() {
assert!(
(a - r).abs() < 1e-4,
"dequant mismatch at index {i}: avx512={a}, ref={r}"
);
}
}
#[test]
#[cfg_attr(not(target_feature = "avx512f"), ignore)]
fn test_gemv_matches_reference() {
if !std::arch::is_x86_feature_detected!("avx512f") {
return;
}
let mut values = [0i8; 32];
for (i, v) in values.iter_mut().enumerate() {
*v = ((i as i32) - 10) as i8;
}
let block = make_q8_0_block(0.25, &values);
let tensor_avx512 = make_tensor(block.clone(), 32);
let tensor_ref = make_tensor(block, 32);
let input: Vec<f32> = (0..32).map(|i| (i as f32) * 0.1 - 1.5).collect();
let mut out_avx512 = vec![0.0f32; 1];
let mut out_ref = vec![0.0f32; 1];
Q8_0Avx512
.gemv(&tensor_avx512, &input, &mut out_avx512)
.unwrap();
Q8_0Ref.gemv(&tensor_ref, &input, &mut out_ref).unwrap();
assert!(
(out_avx512[0] - out_ref[0]).abs() < 1e-4,
"gemv mismatch: avx512={}, ref={}",
out_avx512[0],
out_ref[0]
);
}
#[test]
#[cfg_attr(not(target_feature = "avx512f"), ignore)]
fn test_gemv_partial_block() {
if !std::arch::is_x86_feature_detected!("avx512f") {
return;
}
let values = [1i8; 32];
let block = make_q8_0_block(1.0, &values);
let tensor_avx512 = make_tensor(block.clone(), 20);
let tensor_ref = make_tensor(block, 20);
let input = vec![1.0f32; 20];
let mut out_avx512 = vec![0.0f32; 1];
let mut out_ref = vec![0.0f32; 1];
Q8_0Avx512
.gemv(&tensor_avx512, &input, &mut out_avx512)
.unwrap();
Q8_0Ref.gemv(&tensor_ref, &input, &mut out_ref).unwrap();
assert!(
(out_avx512[0] - out_ref[0]).abs() < 1e-4,
"partial gemv mismatch: avx512={}, ref={}",
out_avx512[0],
out_ref[0]
);
}
#[test]
#[cfg_attr(not(target_feature = "avx512f"), ignore)]
fn test_gemv_negative_weights() {
if !std::arch::is_x86_feature_detected!("avx512f") {
return;
}
let mut values = [0i8; 32];
values[0] = -128;
values[31] = 127;
let block = make_q8_0_block(2.0, &values);
let tensor_avx512 = make_tensor(block.clone(), 32);
let tensor_ref = make_tensor(block, 32);
let mut input = vec![0.0f32; 32];
input[0] = 1.0;
input[31] = 1.0;
let mut out_avx512 = vec![0.0f32; 1];
let mut out_ref = vec![0.0f32; 1];
Q8_0Avx512
.gemv(&tensor_avx512, &input, &mut out_avx512)
.unwrap();
Q8_0Ref.gemv(&tensor_ref, &input, &mut out_ref).unwrap();
assert!(
(out_avx512[0] - out_ref[0]).abs() < 1e-2,
"negative weight gemv mismatch: avx512={}, ref={}",
out_avx512[0],
out_ref[0]
);
}
}