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perf: SIMD l1() + l1_weighted() via I32x16 — 719M lookups/sec (+18%)
Base17::l1(): 16 of 17 dims via I32x16 (sub, abs, reduce_sum), 17th scalar. Base17::l1_weighted(): same + I32x16 multiply for PCDVQ weights [20,3,3,3,3,3,1,1,1,1,1,1,1,1,1,1]. Non-x86 fallback preserved (scalar loop). Before: 611M lookups/sec, 1.8 ns/lookup, 17K tokens/sec After: 719M lookups/sec, 1.4 ns/lookup, 22K tokens/sec https://claude.ai/code/session_01M3at4EuHVvQ8S95mSnKgtK
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Lines changed: 60 additions & 10 deletions

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src/hpc/bgz17_bridge.rs

Lines changed: 60 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -90,13 +90,44 @@ impl Base17 {
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}
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/// L1 (Manhattan) distance.
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///
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/// AVX-512: load 16 of 17 i16 dims as i32, subtract, abs, horizontal sum.
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/// Last dim scalar. Total: ~3 instructions vs 17 scalar iterations.
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#[inline]
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pub fn l1(&self, other: &Base17) -> u32 {
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let mut d = 0u32;
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for i in 0..BASE_DIM {
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d += (self.dims[i] as i32 - other.dims[i] as i32).unsigned_abs();
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#[cfg(target_arch = "x86_64")]
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{
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use crate::simd::I32x16;
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// Load 16 dims as i32 (sign-extend i16 → i32)
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let a: [i32; 16] = [
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self.dims[0] as i32, self.dims[1] as i32, self.dims[2] as i32, self.dims[3] as i32,
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self.dims[4] as i32, self.dims[5] as i32, self.dims[6] as i32, self.dims[7] as i32,
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self.dims[8] as i32, self.dims[9] as i32, self.dims[10] as i32, self.dims[11] as i32,
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self.dims[12] as i32, self.dims[13] as i32, self.dims[14] as i32, self.dims[15] as i32,
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];
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let b: [i32; 16] = [
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other.dims[0] as i32, other.dims[1] as i32, other.dims[2] as i32, other.dims[3] as i32,
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other.dims[4] as i32, other.dims[5] as i32, other.dims[6] as i32, other.dims[7] as i32,
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other.dims[8] as i32, other.dims[9] as i32, other.dims[10] as i32, other.dims[11] as i32,
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other.dims[12] as i32, other.dims[13] as i32, other.dims[14] as i32, other.dims[15] as i32,
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];
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let va = I32x16::from_array(a);
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let vb = I32x16::from_array(b);
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let diff = va - vb;
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let abs_diff = diff.abs();
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let sum16 = abs_diff.reduce_sum();
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// 17th dim scalar
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let d16 = (self.dims[16] as i32 - other.dims[16] as i32).unsigned_abs();
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sum16 as u32 + d16
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}
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#[cfg(not(target_arch = "x86_64"))]
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{
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let mut d = 0u32;
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for i in 0..BASE_DIM {
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d += (self.dims[i] as i32 - other.dims[i] as i32).unsigned_abs();
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}
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d
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}
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d
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}
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/// PCDVQ-informed L1: weight sign dimension 20x over mantissa.
@@ -105,15 +136,34 @@ impl Base17 {
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/// quantization than magnitude. BF16 decomposition maps to polar:
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/// dim 0 = sign (direction), dims 1-6 = exponent (magnitude scale),
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/// dims 7-16 = mantissa (fine detail).
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/// PCDVQ-weighted L1 via SIMD: sign=20×, magnitude=3×, detail=1×.
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#[inline]
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pub fn l1_weighted(&self, other: &Base17) -> u32 {
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let mut d = 0u32;
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for i in 0..BASE_DIM {
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let diff = (self.dims[i] as i32 - other.dims[i] as i32).unsigned_abs();
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let weight = if i == 0 { 20 } else if i < 7 { 3 } else { 1 };
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d += diff * weight;
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#[cfg(target_arch = "x86_64")]
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{
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use crate::simd::I32x16;
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let a: [i32; 16] = core::array::from_fn(|i| self.dims[i] as i32);
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let b: [i32; 16] = core::array::from_fn(|i| other.dims[i] as i32);
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let weights: [i32; 16] = [20, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1];
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let va = I32x16::from_array(a);
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let vb = I32x16::from_array(b);
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let vw = I32x16::from_array(weights);
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let diff = (va - vb).abs();
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let weighted = diff * vw;
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let sum16 = weighted.reduce_sum() as u32;
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let d16 = (self.dims[16] as i32 - other.dims[16] as i32).unsigned_abs();
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sum16 + d16
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}
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#[cfg(not(target_arch = "x86_64"))]
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{
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let mut d = 0u32;
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for i in 0..BASE_DIM {
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let diff = (self.dims[i] as i32 - other.dims[i] as i32).unsigned_abs();
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let weight = if i == 0 { 20 } else if i < 7 { 3 } else { 1 };
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d += diff * weight;
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}
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d
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}
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d
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}
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/// Sign-bit agreement (out of 17).

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