oxillama-quant 0.1.3

Quantization kernels for all GGUF quantization types
Documentation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
//! AVX-512 accelerated Q1_0_G128 quantization kernel.
//!
//! Q1_0_G128 block layout (18 bytes per 128 weights):
//! - bytes[0..2]  — FP16 scale `d` (little-endian)
//! - bytes[2..18] — 16 bytes = 128 sign bits (bit=1 → +d, bit=0 → −d)
//!
//! Bit ordering: LSB-first per byte.  Byte 0, bit 0 → weight 0;
//! byte 0, bit 7 → weight 7; byte 1, bit 0 → weight 8; etc.
//!
//! ## GEMV strategy
//!
//! Same XOR-sign approach as the AVX2 kernel, but we process **2 sign bytes
//! (16 weights) per `__m512` pass** instead of 1 sign byte (8 weights) per
//! `__m256` pass.  This halves the loop trip count.
//!
//! For each pair of consecutive sign bytes (8 weights each):
//! - Expand 16 bits into 16 × u32 XOR masks (0 → 0x80000000, 1 → 0x00000000).
//! - XOR 16 input floats with the mask to apply sign.
//! - Accumulate with `_mm512_add_ps`.
//!
//! At the end, multiply the horizontal sum by `d`.

#![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;

/// Block size for Q1_0_G128: 128 weights per block.
pub const BLOCK_SIZE: usize = 128;
/// Bytes per Q1_0_G128 block: 2 (FP16 scale) + 16 (128 sign bits).
pub const BLOCK_BYTES: usize = 18;

/// AVX-512 accelerated Q1_0_G128 kernel.
///
/// Requires the `avx512f` CPU feature.  The [`crate::dispatch::KernelDispatcher`]
/// checks for this at runtime before constructing this kernel.
pub struct Q1_0G128Avx512;

impl QuantKernel for Q1_0G128Avx512 {
    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(),
            });
        }

        // SAFETY: block.len() >= 18 and output.len() >= 128 verified above.
        // CPU avx512f support guaranteed by KernelDispatcher.
        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;
            // SAFETY: row/block bounds verified above.
            // CPU avx512f support guaranteed by KernelDispatcher.
            *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 {
        "Q1_0_G128"
    }
}

// ---------------------------------------------------------------------------
// Internal helpers
// ---------------------------------------------------------------------------

/// Build a 16-element XOR mask array from two consecutive sign bytes.
///
/// For each of the 16 bit positions (byte0 bits 0..7 then byte1 bits 0..7):
///   - bit==1 → mask = 0x00000000 (leave sign unchanged, weight = +d)
///   - bit==0 → mask = 0x80000000 (flip IEEE-754 sign, weight = −d)
///
/// Stored in natural order: element 0 ← byte0 bit 0 (LSB).
#[inline(always)]
fn two_sign_bytes_to_xor_masks(byte0: u8, byte1: u8) -> [u32; 16] {
    core::array::from_fn(|i| {
        let bit = if i < 8 {
            (byte0 >> i) & 1
        } else {
            (byte1 >> (i - 8)) & 1
        };
        // bit XOR 1 == 1 when the weight is negative; shift to sign-bit position.
        (bit as u32 ^ 1) << 31
    })
}

// ---------------------------------------------------------------------------
// Internal AVX-512 kernels
// ---------------------------------------------------------------------------

/// Dequantize one 18-byte Q1_0_G128 block into 128 FP32 values using AVX-512.
///
/// Processes 16 weights (2 sign bytes) per `__m512` pass — 8 passes total.
///
/// # Safety
/// - `block.len() >= 18`
/// - `output.len() >= 128`
/// - CPU must support `avx512f`
#[target_feature(enable = "avx512f")]
unsafe fn dequant_block_avx512(block: &[u8], output: &mut [f32]) {
    // Read FP16 scale.
    // SAFETY: block.len() >= 18 >= 2.
    let d = f16_to_f32(block);

    // Broadcast +d: XOR-ing with 0x80000000 mask will flip to −d as needed.
    let vd = _mm512_set1_ps(d);

    // Process pairs of sign bytes: each pair covers 16 weights (one AVX-512 lane).
    // 16 sign bytes / 2 = 8 AVX-512 passes.
    for pair_idx in 0..8 {
        // SAFETY: 2 + pair_idx*2 + 1 <= 17 < 18; block.len() >= 18.
        let byte0 = *block.get_unchecked(2 + pair_idx * 2);
        let byte1 = *block.get_unchecked(2 + pair_idx * 2 + 1);
        let masks = two_sign_bytes_to_xor_masks(byte0, byte1);

        // Load the 16 × u32 mask as a 512-bit int register.
        // SAFETY: masks is [u32; 16] = 64 bytes on stack.
        let vmask = _mm512_loadu_si512(masks.as_ptr() as *const __m512i);

        // XOR vd (as integer) with the mask to flip sign bits where bit 31 == 1.
        // _mm512_xor_ps requires avx512dq; use _mm512_xor_si512 (avx512f) + casts instead.
        // mask lanes: 0x00000000 (XOR no-op, keeps +d) or 0x80000000 (flips sign → −d).
        let result = _mm512_castsi512_ps(_mm512_xor_si512(_mm512_castps_si512(vd), vmask));

        // Store 16 dequantized weights.
        // SAFETY: pair_idx * 16 + 15 < 128; output.len() >= 128.
        _mm512_storeu_ps(output.as_mut_ptr().add(pair_idx * 16), result);
    }
}

/// Compute the dot product of one row of a Q1_0_G128 matrix with an FP32 vector.
///
/// Returns the scalar result for this row.
///
/// # Safety
/// - `row_data.len() == blocks_per_row * BLOCK_BYTES`
/// - `input.len() >= n_cols`
/// - CPU must support `avx512f`
#[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;
        // SAFETY: row_data.len() == blocks_per_row * BLOCK_BYTES; blk < blocks_per_row.
        let block = &row_data[block_offset..block_offset + BLOCK_BYTES];
        let input_offset = blk * BLOCK_SIZE;
        let remaining = n_cols.saturating_sub(input_offset);

        // Read FP16 scale.
        // SAFETY: block.len() == 18 >= 2.
        let d = f16_to_f32(block);

        if remaining >= BLOCK_SIZE {
            // Fast path: all 128 weights are valid — 8 AVX-512 passes of 16.
            let mut acc = _mm512_setzero_ps();

            for pair_idx in 0..8 {
                // SAFETY: 2 + pair_idx*2 + 1 < 18; block.len() == 18.
                let byte0 = *block.get_unchecked(2 + pair_idx * 2);
                let byte1 = *block.get_unchecked(2 + pair_idx * 2 + 1);
                let masks = two_sign_bytes_to_xor_masks(byte0, byte1);

                // Expand the sign bytes into per-lane XOR masks.
                // SAFETY: masks is [u32; 16] = 64 bytes on stack.
                let vmask = _mm512_loadu_si512(masks.as_ptr() as *const __m512i);

                // Load 16 input floats.
                // SAFETY: input_offset + pair_idx*16 + 15 < input_offset + 128 <= n_cols <= input.len().
                let inp = _mm512_loadu_ps(input.as_ptr().add(input_offset + pair_idx * 16));

                // XOR input sign bits with the mask, then accumulate.
                // bit==0 → flip input sign (weight=−d), bit==1 → keep sign (weight=+d).
                // Use _mm512_xor_si512 (avx512f) instead of _mm512_xor_ps (avx512dq).
                let signed_inp =
                    _mm512_castsi512_ps(_mm512_xor_si512(_mm512_castps_si512(inp), vmask));
                acc = _mm512_add_ps(acc, signed_inp);
            }

            row_sum += d * hsum_f32_avx512(acc);
        } else if remaining > 0 {
            // Tail path: partial block — scalar fallback to avoid out-of-bounds reads.
            let mut diff = 0.0f32;

            for byte_idx in 0..16 {
                // SAFETY: 2 + byte_idx < 18; block.len() == 18.
                let sign_byte = *block.get_unchecked(2 + byte_idx);
                for bit_idx in 0..8 {
                    let weight_idx = input_offset + byte_idx * 8 + bit_idx;
                    if weight_idx < n_cols {
                        let bit = (sign_byte >> bit_idx) & 1;
                        if bit == 1 {
                            diff += input[weight_idx];
                        } else {
                            diff -= input[weight_idx];
                        }
                    }
                }
            }

            row_sum += d * diff;
        }
        // remaining == 0: block fully out of bounds, skip.
    }

    row_sum
}

// ---------------------------------------------------------------------------
// Tests (CI only — not executed on aarch64 Darwin build machines)
// ---------------------------------------------------------------------------

#[cfg(all(test, target_arch = "x86_64", feature = "simd-avx512"))]
mod tests {
    use super::*;
    use crate::reference::q1_0_g128::Q1_0G128Ref;

    fn make_q1_block(scale: f32, bits: &[u8; 16]) -> 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());
        block.extend_from_slice(bits);
        block
    }

    fn make_tensor(block: Vec<u8>, n_cols: usize) -> QuantTensor {
        QuantTensor::new(
            block,
            vec![1, n_cols],
            oxillama_gguf::GgufTensorType::Q1_0G128,
        )
    }

    #[test]
    #[cfg_attr(not(target_feature = "avx512f"), ignore)]
    fn test_dequant_all_positive() {
        if !std::arch::is_x86_feature_detected!("avx512f") {
            return;
        }
        let block = make_q1_block(2.0, &[0xFF; 16]);
        let mut out_avx512 = vec![0.0f32; 128];
        let mut out_ref = vec![0.0f32; 128];

        Q1_0G128Avx512
            .dequant_block(&block, &mut out_avx512)
            .unwrap();
        Q1_0G128Ref.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_dequant_all_negative() {
        if !std::arch::is_x86_feature_detected!("avx512f") {
            return;
        }
        let block = make_q1_block(3.0, &[0x00; 16]);
        let mut out_avx512 = vec![0.0f32; 128];
        let mut out_ref = vec![0.0f32; 128];

        Q1_0G128Avx512
            .dequant_block(&block, &mut out_avx512)
            .unwrap();
        Q1_0G128Ref.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_dequant_alternating() {
        if !std::arch::is_x86_feature_detected!("avx512f") {
            return;
        }
        // 0xAA = 10101010: bits 1,3,5,7 are +d; bits 0,2,4,6 are -d.
        let block = make_q1_block(1.5, &[0xAA; 16]);
        let mut out_avx512 = vec![0.0f32; 128];
        let mut out_ref = vec![0.0f32; 128];

        Q1_0G128Avx512
            .dequant_block(&block, &mut out_avx512)
            .unwrap();
        Q1_0G128Ref.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_all_positive() {
        if !std::arch::is_x86_feature_detected!("avx512f") {
            return;
        }
        // All bits = 1 → all weights = +d = +1.0, all inputs = 1.0 → dot = 128.
        let block = make_q1_block(1.0, &[0xFF; 16]);
        let tensor_avx512 = make_tensor(block.clone(), 128);
        let tensor_ref = make_tensor(block, 128);

        let input = vec![1.0f32; 128];
        let mut out_avx512 = vec![0.0f32; 1];
        let mut out_ref = vec![0.0f32; 1];

        Q1_0G128Avx512
            .gemv(&tensor_avx512, &input, &mut out_avx512)
            .unwrap();
        Q1_0G128Ref.gemv(&tensor_ref, &input, &mut out_ref).unwrap();

        assert!(
            (out_avx512[0] - out_ref[0]).abs() < 0.5,
            "gemv mismatch: avx512={}, ref={}",
            out_avx512[0],
            out_ref[0]
        );
    }

    #[test]
    #[cfg_attr(not(target_feature = "avx512f"), ignore)]
    fn test_gemv_alternating() {
        if !std::arch::is_x86_feature_detected!("avx512f") {
            return;
        }
        // Alternating sign bits: should cancel with uniform input.
        let block = make_q1_block(1.0, &[0xAA; 16]);
        let tensor_avx512 = make_tensor(block.clone(), 128);
        let tensor_ref = make_tensor(block, 128);

        let input = vec![1.0f32; 128];
        let mut out_avx512 = vec![0.0f32; 1];
        let mut out_ref = vec![0.0f32; 1];

        Q1_0G128Avx512
            .gemv(&tensor_avx512, &input, &mut out_avx512)
            .unwrap();
        Q1_0G128Ref.gemv(&tensor_ref, &input, &mut out_ref).unwrap();

        assert!(
            (out_avx512[0] - out_ref[0]).abs() < 0.5,
            "gemv mismatch: avx512={}, ref={}",
            out_avx512[0],
            out_ref[0]
        );
    }

    #[test]
    #[cfg_attr(not(target_feature = "avx512f"), ignore)]
    fn test_gemv_matches_reference_random() {
        if !std::arch::is_x86_feature_detected!("avx512f") {
            return;
        }
        let bits: [u8; 16] = [
            0b10110101, 0b01001110, 0b11100010, 0b00011111, 0b10101010, 0b01010101, 0b11001100,
            0b00110011, 0b11110000, 0b00001111, 0b10011001, 0b01100110, 0b11111110, 0b00000001,
            0b10000001, 0b01111110,
        ];
        let block = make_q1_block(0.5, &bits);
        let tensor_avx512 = make_tensor(block.clone(), 128);
        let tensor_ref = make_tensor(block, 128);

        let input: Vec<f32> = (0..128).map(|i| (i as f32) * 0.03 - 1.9).collect();
        let mut out_avx512 = vec![0.0f32; 1];
        let mut out_ref = vec![0.0f32; 1];

        Q1_0G128Avx512
            .gemv(&tensor_avx512, &input, &mut out_avx512)
            .unwrap();
        Q1_0G128Ref.gemv(&tensor_ref, &input, &mut out_ref).unwrap();

        assert!(
            (out_avx512[0] - out_ref[0]).abs() < 1e-3,
            "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;
        }
        // 80 columns — one partial block (80 < 128).
        let block = make_q1_block(1.0, &[0xFF; 16]);
        let tensor_avx512 = make_tensor(block.clone(), 80);
        let tensor_ref = make_tensor(block, 80);

        let input = vec![1.0f32; 80];
        let mut out_avx512 = vec![0.0f32; 1];
        let mut out_ref = vec![0.0f32; 1];

        Q1_0G128Avx512
            .gemv(&tensor_avx512, &input, &mut out_avx512)
            .unwrap();
        Q1_0G128Ref.gemv(&tensor_ref, &input, &mut out_ref).unwrap();

        assert!(
            (out_avx512[0] - out_ref[0]).abs() < 0.5,
            "partial gemv mismatch: avx512={}, ref={}",
            out_avx512[0],
            out_ref[0]
        );
    }
}