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use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
use pklib::{explode_bytes, implode_bytes, CompressionMode, DictionarySize};
use std::hint::black_box;
use std::sync::{Arc, Mutex};
use std::thread;
use std::time::Duration;
fn generate_test_files(count: usize, size_per_file: usize) -> Vec<Vec<u8>> {
(0..count)
.map(|i| {
// Generate slightly different data for each file
let base = format!("File {i} content: Lorem ipsum dolor sit amet. ");
let mut data = Vec::with_capacity(size_per_file);
while data.len() < size_per_file {
data.extend_from_slice(base.as_bytes());
}
data.truncate(size_per_file);
data
})
.collect()
}
fn generate_large_file(size: usize) -> Vec<u8> {
let pattern = b"The quick brown fox jumps over the lazy dog. ";
let mut data = Vec::with_capacity(size);
while data.len() < size {
data.extend_from_slice(pattern);
}
data.truncate(size);
data
}
/// Benchmark multiple files processed in parallel
fn parallel_file_compression(c: &mut Criterion) {
let mut group = c.benchmark_group("parallel_compression");
group.measurement_time(Duration::from_secs(20));
group.sample_size(20);
// Test different file counts and sizes
let test_cases = vec![
(10, 102400), // 10 files × 100KB each
(100, 10240), // 100 files × 10KB each
(1000, 1024), // 1000 files × 1KB each
];
for (file_count, file_size) in test_cases {
let files = generate_test_files(file_count, file_size);
let total_size = file_count * file_size;
// Test with different thread counts
for thread_count in [1, 2, 4, 8].iter() {
let benchmark_id = BenchmarkId::from_parameter(format!(
"{}files_{}KB_{}threads",
file_count,
file_size / 1024,
thread_count
));
group.throughput(Throughput::Bytes(total_size as u64));
group.bench_with_input(benchmark_id, &files, |b, files: &Vec<Vec<u8>>| {
b.iter(|| {
let files = files.clone();
let thread_count = *thread_count;
// Create work queue
let work_queue = Arc::new(Mutex::new(
files.into_iter().enumerate().collect::<Vec<_>>(),
));
let results = Arc::new(Mutex::new(Vec::with_capacity(file_count)));
// Spawn worker threads
let mut handles = vec![];
for _ in 0..thread_count {
let queue = Arc::clone(&work_queue);
let results = Arc::clone(&results);
let handle = thread::spawn(move || {
loop {
// Get next file to process
let work_item = {
let mut queue = queue.lock().unwrap();
queue.pop()
};
let (idx, data) = match work_item {
Some(item) => item,
None => break,
};
// Compress the file
let compressed = implode_bytes(
&data,
CompressionMode::Binary,
DictionarySize::Size4K,
)
.expect("Compression failed");
// Store result
let mut results = results.lock().unwrap();
results.push((idx, compressed));
}
});
handles.push(handle);
}
// Wait for all threads to complete
for handle in handles {
handle.join().unwrap();
}
// Return sorted results
let mut results = Arc::try_unwrap(results).unwrap().into_inner().unwrap();
results.sort_by_key(|(idx, _)| *idx);
results
});
});
}
}
group.finish();
}
/// Benchmark single file split into chunks for parallel processing
fn parallel_chunk_compression(c: &mut Criterion) {
let mut group = c.benchmark_group("parallel_chunk_compression");
group.measurement_time(Duration::from_secs(15));
group.sample_size(20);
// Test different file sizes
for file_size in [1048576, 10485760, 104857600].iter() {
// 1MB, 10MB, 100MB
let size_label = match *file_size {
1048576 => "1MB",
10485760 => "10MB",
104857600 => "100MB",
_ => "unknown",
};
let data = generate_large_file(*file_size);
// Test with different chunk sizes and thread counts
for chunk_size in [65536, 262144, 1048576].iter() {
// 64KB, 256KB, 1MB chunks
let chunk_label = match *chunk_size {
65536 => "64KB",
262144 => "256KB",
1048576 => "1MB",
_ => "unknown",
};
for thread_count in [1, 2, 4, 8].iter() {
let benchmark_id = BenchmarkId::from_parameter(format!(
"{size_label}_{chunk_label}chunks_{thread_count}threads"
));
group.throughput(Throughput::Bytes(*file_size as u64));
group.bench_with_input(benchmark_id, &data, |b, data| {
b.iter(|| {
let chunks: Vec<Vec<u8>> = data
.chunks(*chunk_size)
.map(|chunk| chunk.to_vec())
.collect();
let thread_count = *thread_count;
let work_queue = Arc::new(Mutex::new(
chunks.into_iter().enumerate().collect::<Vec<_>>(),
));
let results = Arc::new(Mutex::new(Vec::new()));
// Spawn worker threads
let mut handles = vec![];
for _ in 0..thread_count {
let queue = Arc::clone(&work_queue);
let results = Arc::clone(&results);
let handle = thread::spawn(move || loop {
let work_item = {
let mut queue = queue.lock().unwrap();
queue.pop()
};
let (idx, chunk) = match work_item {
Some(item) => item,
None => break,
};
let compressed = implode_bytes(
&chunk,
CompressionMode::Binary,
DictionarySize::Size4K,
)
.expect("Compression failed");
let mut results = results.lock().unwrap();
results.push((idx, compressed));
});
handles.push(handle);
}
for handle in handles {
handle.join().unwrap();
}
// Return sorted compressed chunks
let mut results = Arc::try_unwrap(results).unwrap().into_inner().unwrap();
results.sort_by_key(|(idx, _)| *idx);
results
});
});
}
}
}
group.finish();
}
/// Benchmark parallel decompression
fn parallel_decompression(c: &mut Criterion) {
let mut group = c.benchmark_group("parallel_decompression");
group.measurement_time(Duration::from_secs(15));
group.sample_size(20);
// Generate compressed files for decompression
let test_cases = vec![
(10, 102400), // 10 files × 100KB each
(100, 10240), // 100 files × 10KB each
];
for (file_count, original_size) in test_cases {
// Generate and compress files
let compressed_files: Vec<Vec<u8>> = generate_test_files(file_count, original_size)
.into_iter()
.map(|data| {
implode_bytes(&data, CompressionMode::Binary, DictionarySize::Size4K)
.expect("Compression failed")
})
.collect();
let total_original_size = file_count * original_size;
for thread_count in [1, 2, 4, 8].iter() {
let benchmark_id = BenchmarkId::from_parameter(format!(
"{}files_{}KB_{}threads",
file_count,
original_size / 1024,
thread_count
));
group.throughput(Throughput::Bytes(total_original_size as u64));
group.bench_with_input(
benchmark_id,
&compressed_files,
|b, files: &Vec<Vec<u8>>| {
b.iter(|| {
let files = files.clone();
let thread_count = *thread_count;
let work_queue = Arc::new(Mutex::new(
files.into_iter().enumerate().collect::<Vec<_>>(),
));
let results = Arc::new(Mutex::new(Vec::new()));
let mut handles = vec![];
for _ in 0..thread_count {
let queue = Arc::clone(&work_queue);
let results = Arc::clone(&results);
let handle = thread::spawn(move || loop {
let work_item = {
let mut queue = queue.lock().unwrap();
queue.pop()
};
let (idx, data) = match work_item {
Some(item) => item,
None => break,
};
let decompressed =
explode_bytes(&data).expect("Decompression failed");
let mut results = results.lock().unwrap();
results.push((idx, decompressed));
});
handles.push(handle);
}
for handle in handles {
handle.join().unwrap();
}
let mut results = Arc::try_unwrap(results).unwrap().into_inner().unwrap();
results.sort_by_key(|(idx, _)| *idx);
results
});
},
);
}
}
group.finish();
}
/// Benchmark thread scaling efficiency
fn thread_scaling_efficiency(c: &mut Criterion) {
let mut group = c.benchmark_group("thread_scaling");
group.measurement_time(Duration::from_secs(10));
// Fixed workload: 100 files of 10KB each
let files = generate_test_files(100, 10240);
let total_size = 100 * 10240;
// Test scaling from 1 to 16 threads
for thread_count in [1, 2, 3, 4, 6, 8, 12, 16].iter() {
let benchmark_id = BenchmarkId::from_parameter(format!("{thread_count}threads"));
group.throughput(Throughput::Bytes(total_size as u64));
group.bench_with_input(benchmark_id, &files, |b, files: &Vec<Vec<u8>>| {
b.iter(|| {
let files = files.clone();
let thread_count = *thread_count;
let work_queue = Arc::new(Mutex::new(files.into_iter().collect::<Vec<_>>()));
let results = Arc::new(Mutex::new(0usize));
let mut handles = vec![];
for _ in 0..thread_count {
let queue = Arc::clone(&work_queue);
let results = Arc::clone(&results);
let handle = thread::spawn(move || {
let mut local_processed = 0;
loop {
let work_item = {
let mut queue = queue.lock().unwrap();
queue.pop()
};
let data = match work_item {
Some(item) => item,
None => break,
};
let compressed = implode_bytes(
&data,
CompressionMode::Binary,
DictionarySize::Size4K,
)
.expect("Compression failed");
black_box(compressed);
local_processed += 1;
}
let mut results = results.lock().unwrap();
*results += local_processed;
});
handles.push(handle);
}
for handle in handles {
handle.join().unwrap();
}
let processed = *results.lock().unwrap();
assert_eq!(processed, 100);
});
});
}
group.finish();
}
criterion_group!(
benches,
parallel_file_compression,
parallel_chunk_compression,
parallel_decompression,
thread_scaling_efficiency
);
criterion_main!(benches);