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Merged
5000user5000 merged 1 commit into from
Nov 9, 2025
Merged

Add build variants with conditional compilation #11

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107 changes: 94 additions & 13 deletions Makefile
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
CXX := g++
CXXFLAGS := -std=c++17 -O3 -fPIC -march=native -fopenmp
BASE_CXXFLAGS := -std=c++17 -O3 -fPIC

# Python / pybind11 include flags
PYBIND11_INCLUDES := $(shell python3 -m pybind11 --includes)
Expand Down Expand Up @@ -28,35 +28,116 @@ SOURCES := \

# Extension suffix (.so or .cpython-XYm-x86_64-linux-gnu.so, etc.)
EXT_SUFFIX := $(shell python3-config --extension-suffix)
TARGET := build/zenann$(EXT_SUFFIX)

# Platform‐specific linker flags
UNAME_S := $(shell uname -s)
ifeq ($(UNAME_S),Darwin)
# on macOS use dynamic_lookup
LDFLAGS := -undefined dynamic_lookup
BASE_LDFLAGS := -undefined dynamic_lookup
else
# on Linux embed rpath to pick up our extern/faiss libfaiss.so
LDFLAGS := -Wl,-rpath,$$ORIGIN/../extern/faiss/build/install/lib
BASE_LDFLAGS := -Wl,-rpath,$$ORIGIN/../extern/faiss/build/install/lib
endif

# Add OpenMP linking
LDFLAGS += -fopenmp
# ============================================================================
# Version-specific build configurations
# ============================================================================

# Output target (all versions output to the same file)
TARGET := build/zenann$(EXT_SUFFIX)

# NAIVE: No parallelization (baseline)
NAIVE_CXXFLAGS := $(BASE_CXXFLAGS)
NAIVE_LDFLAGS := $(BASE_LDFLAGS)

# OPENMP: Only OpenMP parallelization
OPENMP_CXXFLAGS := $(BASE_CXXFLAGS) -fopenmp -DENABLE_OPENMP
OPENMP_LDFLAGS := $(BASE_LDFLAGS) -fopenmp

# SIMD: Only SIMD vectorization (AVX2)
SIMD_CXXFLAGS := $(BASE_CXXFLAGS) -march=native -DENABLE_SIMD
SIMD_LDFLAGS := $(BASE_LDFLAGS)

.PHONY: all clean prepare
# FULL: OpenMP + SIMD (fully optimized)
FULL_CXXFLAGS := $(BASE_CXXFLAGS) -march=native -fopenmp -DENABLE_OPENMP -DENABLE_SIMD
FULL_LDFLAGS := $(BASE_LDFLAGS) -fopenmp

all: prepare $(TARGET)
# CUDA: CUDA acceleration (placeholder for future)
CUDA_CXXFLAGS := $(BASE_CXXFLAGS) -DENABLE_CUDA
CUDA_LDFLAGS := $(BASE_LDFLAGS) -lcuda -lcudart

# ============================================================================
# Targets
# ============================================================================

.PHONY: all clean prepare naive openmp simd full cuda help

# Default target: build full version
all: full

prepare:
mkdir -p build
@mkdir -p build

# Build the Python extension, linking against our Faiss
$(TARGET): $(SOURCES)
$(CXX) $(CXXFLAGS) $(ALL_INCLUDES) -shared -o $@ \
# Build naive version (no parallelization)
naive: prepare
$(CXX) $(NAIVE_CXXFLAGS) $(ALL_INCLUDES) -shared -o $(TARGET) \
$(SOURCES) \
-L$(FAISS_ROOT)/lib -lfaiss \
$(ALL_LIBS) \
$(LDFLAGS)
$(NAIVE_LDFLAGS)
@echo "✓ Built NAIVE version: $(TARGET)"

# Build OpenMP-only version
openmp: prepare
$(CXX) $(OPENMP_CXXFLAGS) $(ALL_INCLUDES) -shared -o $(TARGET) \
$(SOURCES) \
-L$(FAISS_ROOT)/lib -lfaiss \
$(ALL_LIBS) \
$(OPENMP_LDFLAGS)
@echo "✓ Built OPENMP version: $(TARGET)"

# Build SIMD-only version
simd: prepare
$(CXX) $(SIMD_CXXFLAGS) $(ALL_INCLUDES) -shared -o $(TARGET) \
$(SOURCES) \
-L$(FAISS_ROOT)/lib -lfaiss \
$(ALL_LIBS) \
$(SIMD_LDFLAGS)
@echo "✓ Built SIMD version: $(TARGET)"

# Build full version (OpenMP + SIMD)
full: prepare
$(CXX) $(FULL_CXXFLAGS) $(ALL_INCLUDES) -shared -o $(TARGET) \
$(SOURCES) \
-L$(FAISS_ROOT)/lib -lfaiss \
$(ALL_LIBS) \
$(FULL_LDFLAGS)
@echo "✓ Built FULL version: $(TARGET)"

# Build CUDA version (placeholder)
cuda: prepare
@echo "CUDA version not yet implemented"
@echo "Will output to: $(TARGET)"

# Clean all builds
clean:
rm -rf build

# Help message
help:
@echo "ZenANN Build System - Multiple Optimization Versions"
@echo ""
@echo "Available targets:"
@echo " make naive - Build naive version (no parallelization)"
@echo " make openmp - Build OpenMP-only version"
@echo " make simd - Build SIMD-only version (AVX2)"
@echo " make full - Build fully optimized version (OpenMP + SIMD)"
@echo " make cuda - Build CUDA version (not yet implemented)"
@echo " make all - Build full version (default)"
@echo " make clean - Remove all built files"
@echo ""
@echo "Note: All versions output to build/zenann.so"
@echo "Each build will overwrite the previous one."
@echo ""
@echo "Usage:"
@echo " import build.zenann as zenann # Always works regardless of version"
Comment on lines +127 to +143
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@5000user5000 5000user5000 Nov 9, 2025

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make help
說明 make 選項

13 changes: 9 additions & 4 deletions include/zenann/SimdUtils.h
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Original file line number Diff line number Diff line change
@@ -1,12 +1,16 @@
#pragma once
#include <cstddef>

#if defined(ENABLE_SIMD)
#include <immintrin.h>
#endif

namespace zenann {
inline float l2_simd(const float* __restrict a,
const float* __restrict b,
size_t dim) {
#if defined(__AVX2__)

// L2 distance calculation with optional SIMD optimization
inline float l2_distance(const float* a, const float* b, size_t dim) {
#if defined(ENABLE_SIMD) && defined(__AVX2__)
// SIMD version using AVX2
const size_t step = 8; // 8 × 32-bit floats
__m256 acc = _mm256_setzero_ps();
size_t i = 0;
Expand All @@ -27,6 +31,7 @@ inline float l2_simd(const float* __restrict a,
}
return d;
#else
// Naive version (no SIMD or AVX2 not available)
float d = 0.f;
for (size_t i = 0; i < dim; ++i) {
float diff = a[i] - b[i];
Expand Down
36 changes: 30 additions & 6 deletions src/IVFFlatIndex.cpp
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Original file line number Diff line number Diff line change
@@ -1,6 +1,8 @@
#include "IVFFlatIndex.h"
#include "SimdUtils.h"
#ifdef ENABLE_OPENMP
#include <omp.h>
#endif
#include <limits>
#include <random>
#include <algorithm>
Expand Down Expand Up @@ -48,10 +50,12 @@ SearchResult IVFFlatIndex::search(const Vector& query, size_t k) const {
std::vector<Pair> cdist(nlist_);
std::vector<Pair> heap;

// Calculate distance from query to all centroids (parallelized)
// Calculate distance from query to all centroids
#ifdef ENABLE_OPENMP
#pragma omp parallel for schedule(static)
#endif
for (size_t c = 0; c < nlist_; ++c) {
float d = l2_simd(query.data(), centroids_[c].data(), dimension_);
float d = l2_distance(query.data(), centroids_[c].data(), dimension_);
cdist[c] = {d, c};
}

Expand All @@ -62,23 +66,27 @@ SearchResult IVFFlatIndex::search(const Vector& query, size_t k) const {
}
);

// Probe nprobe nearest lists in parallel
// Each thread maintains a local heap, then merges into global heap
// Probe nprobe nearest lists
heap.reserve(k);
const auto& data = datastore_->getAll();

#ifdef ENABLE_OPENMP
#pragma omp parallel for schedule(dynamic)
#endif
for (size_t pi = 0; pi < nprobe_; ++pi) {
size_t c = cdist[pi].second;

#ifdef ENABLE_OPENMP
// Thread-local heap for this cluster
std::vector<Pair> local;
local.reserve(k);
#endif

// Search within this cluster's inverted list
for (size_t id : lists_[c]) {
float dist = l2_simd(query.data(), data[id].data(), dimension_);
float dist = l2_distance(query.data(), data[id].data(), dimension_);

#ifdef ENABLE_OPENMP
if (local.size() < k) {
local.emplace_back(dist, id);
if (local.size() == k) {
Expand All @@ -89,8 +97,21 @@ SearchResult IVFFlatIndex::search(const Vector& query, size_t k) const {
local.back() = {dist, id};
std::push_heap(local.begin(), local.end());
}
#else
if (heap.size() < k) {
heap.emplace_back(dist, id);
if (heap.size() == k) {
std::make_heap(heap.begin(), heap.end());
}
} else if (dist < heap.front().first) {
std::pop_heap(heap.begin(), heap.end());
heap.back() = {dist, id};
std::push_heap(heap.begin(), heap.end());
}
#endif
}

#ifdef ENABLE_OPENMP
// Merge local results into global heap (thread-safe)
#pragma omp critical
{
Expand All @@ -107,6 +128,7 @@ SearchResult IVFFlatIndex::search(const Vector& query, size_t k) const {
}
}
}
#endif
}

std::sort(heap.begin(), heap.end(),
Expand Down Expand Up @@ -134,8 +156,10 @@ std::vector<SearchResult> IVFFlatIndex::search_batch(const Dataset& queries, siz
const size_t nq = queries.size();
std::vector<SearchResult> results(nq);

// Parallel batch search with dynamic scheduling
// Batch search with optional parallelization
#ifdef ENABLE_OPENMP
#pragma omp parallel for schedule(dynamic)
#endif
for (size_t i = 0; i < nq; ++i) {
results[i] = search(queries[i], k);
}
Expand Down