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Fix distance computations in Native provider #389

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merged 3 commits into from
Jan 23, 2025
Merged

Fix distance computations in Native provider #389

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b5b1fa4
Replace multiplication and addition by FMA in tail computation
marianotepper Jan 22, 2025
14bd2c5
Fix computation of tail elements in nvqCosine8bit, nvqDotProduct8bit,…
marianotepper Jan 22, 2025
b25fb98
When using FloatVector.fromMemorySegment, use MemorySegmentVectorFloa…
marianotepper Jan 22, 2025
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37 changes: 19 additions & 18 deletions jvector-native/src/main/java/io/github/jbellis/jvector/vector/VectorSimdOps.java
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Original file line number Diff line number Diff line change
Expand Up @@ -653,6 +653,7 @@ public static void quantizePartials(float delta, MemorySegmentVectorFloat partia
//---------------------------------------------
// NVQ quantization instructions start here
//---------------------------------------------

static final FloatVector const1f = FloatVector.broadcast(FloatVector.SPECIES_PREFERRED, 1.f);
static final FloatVector const05f = FloatVector.broadcast(FloatVector.SPECIES_PREFERRED, 0.5f);

Expand Down Expand Up @@ -742,7 +743,7 @@ static void nvqQuantize8bit(MemorySegmentVectorFloat vector, float alpha, float
var invLogisticScale = 255 / (logisticNQT(maxValue, scaledAlpha, scaledX0) - logisticBias);

for (int i = 0; i < vectorizedLength; i += FloatVector.SPECIES_PREFERRED.length()) {
var arr = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), i, ByteOrder.LITTLE_ENDIAN);
var arr = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), vector.offset(i), ByteOrder.LITTLE_ENDIAN);
arr = logisticNQT(arr, scaledAlpha, scaledX0);
arr = arr.sub(logisticBias).mul(invLogisticScale);
var bytes = arr.add(const05f)
Expand Down Expand Up @@ -777,7 +778,7 @@ static float nvqLoss(MemorySegmentVectorFloat vector, float alpha, float x0, flo
var invLogisticScale = 1 / logisticScale;

for (int i = 0; i < vectorizedLength; i += FloatVector.SPECIES_PREFERRED.length()) {
var arr = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), i, ByteOrder.LITTLE_ENDIAN);
var arr = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), vector.offset(i), ByteOrder.LITTLE_ENDIAN);
var recArr = logisticNQT(arr, scaledAlpha, scaledX0);
recArr = recArr.sub(logisticBias).mul(invLogisticScale);
recArr = recArr.add(const05f)
Expand All @@ -803,7 +804,7 @@ static float nvqLoss(MemorySegmentVectorFloat vector, float alpha, float x0, flo
recValue = (recValue - logisticBias) * invLogisticScale;
recValue = Math.round(recValue);
recValue = Math.fma(logisticScale, recValue, logisticBias);
recValue = logitNQT(recValue, scaledAlpha, scaledX0);
recValue = logitNQT(recValue, invScaledAlpha, scaledX0);

squaredSum += MathUtil.square(value - recValue);
}
Expand All @@ -813,19 +814,21 @@ static float nvqLoss(MemorySegmentVectorFloat vector, float alpha, float x0, flo

static float nvqUniformLoss(MemorySegmentVectorFloat vector, float minValue, float maxValue, int nBits) {
float constant = (1 << nBits) - 1;
float delta = maxValue - minValue;

int vectorizedLength = FloatVector.SPECIES_PREFERRED.loopBound(vector.length());

FloatVector squaredSumVec = FloatVector.zero(FloatVector.SPECIES_PREFERRED);

for (int i = 0; i < vectorizedLength; i += FloatVector.SPECIES_PREFERRED.length()) {
var arr = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), i, ByteOrder.LITTLE_ENDIAN);
var recArr = arr.sub(minValue).mul(constant / (maxValue - minValue));
var arr = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), vector.offset(i), ByteOrder.LITTLE_ENDIAN);
var recArr = arr.sub(minValue).mul(constant / delta);
recArr = recArr.add(const05f)
.convert(VectorOperators.F2I, 0)
.reinterpretAsInts()
.convert(VectorOperators.I2F, 0)
.reinterpretAsFloats();
recArr = recArr.fma((maxValue - minValue) / constant, minValue);
recArr = recArr.fma(delta / constant, minValue);

var diff = arr.sub(recArr);
squaredSumVec = diff.fma(diff, squaredSumVec);
Expand All @@ -838,9 +841,9 @@ static float nvqUniformLoss(MemorySegmentVectorFloat vector, float minValue, flo
for (int i = vectorizedLength; i < vector.length(); i++) {
value = vector.get(i);

recValue = (value - minValue) / (maxValue - minValue);
recValue = (value - minValue) / delta;
recValue = Math.round(constant * recValue) / constant;
recValue = recValue / (maxValue - minValue) + minValue;
recValue = recValue * delta + minValue;

squaredSum += MathUtil.square(value - recValue);
}
Expand All @@ -866,7 +869,7 @@ static float nvqSquareDistance8bit(MemorySegmentVectorFloat vector, MemorySegmen
var byteArr = ByteVector.fromMemorySegment(ByteVector.SPECIES_PREFERRED, quantizedVector.get(), i, ByteOrder.LITTLE_ENDIAN);

for (int j = 0; j < 4; j++) {
var v1 = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), i + floatStep * j, ByteOrder.LITTLE_ENDIAN);
var v1 = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), vector.offset(i + floatStep * j), ByteOrder.LITTLE_ENDIAN);
var v2 = nvqDequantize8bit(byteArr, invScaledAlpha, scaledX0, logisticScale, logisticBias, j);

var diff = v1.sub(v2);
Expand All @@ -881,15 +884,14 @@ static float nvqSquareDistance8bit(MemorySegmentVectorFloat vector, MemorySegmen
for (int i = vectorizedLength; i < quantizedVector.length(); i++) {
value2 = Byte.toUnsignedInt(quantizedVector.get(i));
value2 = Math.fma(logisticScale, value2, logisticBias);
value2 = logitNQT(value2, scaledAlpha, scaledX0);
value2 = logitNQT(value2, invScaledAlpha, scaledX0);
diff = vector.get(i) - value2;
squaredSum += MathUtil.square(diff);
}

return squaredSum;
}


static float nvqDotProduct8bit(MemorySegmentVectorFloat vector, MemorySegmentByteSequence quantizedVector,
float alpha, float x0, float minValue, float maxValue) {
FloatVector dotProdVec = FloatVector.zero(FloatVector.SPECIES_PREFERRED);
Expand All @@ -904,12 +906,11 @@ static float nvqDotProduct8bit(MemorySegmentVectorFloat vector, MemorySegmentByt
var logisticBias = logisticNQT(minValue, scaledAlpha, scaledX0);
var logisticScale = (logisticNQT(maxValue, scaledAlpha, scaledX0) - logisticBias) / 255;


for (int i = 0; i < vectorizedLength; i += ByteVector.SPECIES_PREFERRED.length()) {
var byteArr = ByteVector.fromMemorySegment(ByteVector.SPECIES_PREFERRED, quantizedVector.get(), i, ByteOrder.LITTLE_ENDIAN);

for (int j = 0; j < 4; j++) {
var v1 = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), i + floatStep * j, ByteOrder.LITTLE_ENDIAN);
var v1 = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), vector.offset(i + floatStep * j), ByteOrder.LITTLE_ENDIAN);
var v2 = nvqDequantize8bit(byteArr, invScaledAlpha, scaledX0, logisticScale, logisticBias, j);
dotProdVec = v1.fma(v2, dotProdVec);
}
Expand All @@ -922,7 +923,7 @@ static float nvqDotProduct8bit(MemorySegmentVectorFloat vector, MemorySegmentByt
for (int i = vectorizedLength; i < quantizedVector.length(); i++) {
value2 = Byte.toUnsignedInt(quantizedVector.get(i));
value2 = Math.fma(logisticScale, value2, logisticBias);
value2 = logitNQT(value2, scaledAlpha, scaledX0);
value2 = logitNQT(value2, invScaledAlpha, scaledX0);
dotProd = Math.fma(vector.get(i), value2, dotProd);
}

Expand Down Expand Up @@ -953,10 +954,10 @@ static float[] nvqCosine8bit(MemorySegmentVectorFloat vector, MemorySegmentByteS
var byteArr = ByteVector.fromMemorySegment(ByteVector.SPECIES_PREFERRED, quantizedVector.get(), i, ByteOrder.LITTLE_ENDIAN);

for (int j = 0; j < 4; j++) {
var va = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), i + floatStep * j, ByteOrder.LITTLE_ENDIAN);
var va = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, vector.get(), vector.offset(i + floatStep * j), ByteOrder.LITTLE_ENDIAN);
var vb = nvqDequantize8bit(byteArr, invScaledAlpha, scaledX0, logisticScale, logisticBias, j);

var vCentroid = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, centroid.get(), i + floatStep * j, ByteOrder.LITTLE_ENDIAN);
var vCentroid = FloatVector.fromMemorySegment(FloatVector.SPECIES_PREFERRED, centroid.get(), centroid.offset(i + floatStep * j), ByteOrder.LITTLE_ENDIAN);
vb = vb.add(vCentroid);

vsum = va.fma(vb, vsum);
Expand All @@ -972,7 +973,7 @@ static float[] nvqCosine8bit(MemorySegmentVectorFloat vector, MemorySegmentByteS
for (int i = vectorizedLength; i < vector.length(); i++) {
value2 = Byte.toUnsignedInt(quantizedVector.get(i));
value2 = Math.fma(logisticScale, value2, logisticBias);
value2 = logitNQT(value2, scaledAlpha, scaledX0) + centroid.get(i);
value2 = logitNQT(value2, invScaledAlpha, scaledX0) + centroid.get(i);
sum = Math.fma(vector.get(i), value2, sum);
bMagnitude = Math.fma(value2, value2, bMagnitude);
}
Expand Down Expand Up @@ -1012,6 +1013,6 @@ static void nvqShuffleQueryInPlace8bit(MemorySegmentVectorFloat vector) {
}

//---------------------------------------------
// NVQ quantization instructions end here
// NVQ instructions end here
//---------------------------------------------
}
2 changes: 1 addition & 1 deletion jvector-twenty/src/main/java/io/github/jbellis/jvector/vector/SimdOps.java
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Original file line number Diff line number Diff line change
Expand Up @@ -1104,7 +1104,7 @@ static float nvqSquareDistance8bit(ArrayVectorFloat vector, ArrayByteSequence qu
float value2, diff;
for (int i = vectorizedLength; i < quantizedVector.length(); i++) {
value2 = Byte.toUnsignedInt(quantizedVector.get(i));
value2 = logisticScale * value2 + logisticBias;
value2 = Math.fma(logisticScale, value2, logisticBias);
value2 = logitNQT(value2, invScaledAlpha, scaledX0);
diff = vector.get(i) - value2;
squaredSum += MathUtil.square(diff);
Expand Down
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