Files
clawhdf5/crates/clawhdf5-format/benches/parallel_decompress_bench.rs

114 lines
3.8 KiB
Rust

//! Parallel decompression scaling benchmark for 48-core Xeon.
//! Uses read_chunked_data which auto-dispatches to parallel when feature enabled.
use clawhdf5_format::chunked_read::read_chunked_data;
use clawhdf5_format::data_layout::DataLayout;
use clawhdf5_format::data_read::read_as_f64;
use clawhdf5_format::dataspace::Dataspace;
use clawhdf5_format::datatype::Datatype;
use clawhdf5_format::file_writer::FileWriter;
use clawhdf5_format::filter_pipeline::FilterPipeline;
use clawhdf5_format::group_v2::resolve_path_any;
use clawhdf5_format::message_type::MessageType;
use clawhdf5_format::object_header::ObjectHeader;
use clawhdf5_format::signature::find_signature;
use clawhdf5_format::superblock::Superblock;
use criterion::{BenchmarkId, Criterion, criterion_group, criterion_main};
fn make_deflate_file(n: usize) -> Vec<u8> {
let data: Vec<f64> = (0..n).map(|i| (i as f64) * 0.001).collect();
let mut fw = FileWriter::new();
fw.create_dataset("data")
.with_f64_data(&data)
.with_shape(&[n as u64])
.with_chunks(&[10_000])
.with_deflate(6);
fw.finish().unwrap()
}
fn read_dataset(bytes: &[u8]) -> Vec<f64> {
let sig = find_signature(bytes).unwrap();
let sb = Superblock::parse(bytes, sig).unwrap();
let addr = resolve_path_any(bytes, &sb, "data").unwrap();
let hdr = ObjectHeader::parse(bytes, addr as usize, sb.offset_size, sb.length_size).unwrap();
let dt_data = &hdr
.messages
.iter()
.find(|m| m.msg_type == MessageType::Datatype)
.unwrap()
.data;
let ds_data = &hdr
.messages
.iter()
.find(|m| m.msg_type == MessageType::Dataspace)
.unwrap()
.data;
let dl_data = &hdr
.messages
.iter()
.find(|m| m.msg_type == MessageType::DataLayout)
.unwrap()
.data;
let (dt, _) = Datatype::parse(dt_data).unwrap();
let ds = Dataspace::parse(ds_data, sb.length_size).unwrap();
let dl = DataLayout::parse(dl_data, sb.offset_size, sb.length_size).unwrap();
let pipeline = hdr
.messages
.iter()
.find(|m| m.msg_type == MessageType::FilterPipeline)
.map(|m| FilterPipeline::parse(&m.data).unwrap());
let raw = read_chunked_data(
bytes,
&dl,
&ds,
&dt,
pipeline.as_ref(),
sb.offset_size,
sb.length_size,
)
.unwrap();
read_as_f64(&raw, &dt).unwrap()
}
fn bench_core_scaling(c: &mut Criterion) {
let mut group = c.benchmark_group("parallel_deflate_10M");
group.sample_size(15);
let n = 10_000_000;
let bytes = make_deflate_file(n);
// The `parallel` feature auto-dispatches to rayon in read_chunked_data.
// Control thread count via RAYON_NUM_THREADS env var.
for cores in [1, 2, 4, 8, 16, 24, 32, 48] {
group.bench_with_input(BenchmarkId::new("lanes", cores), &cores, |b, &cores| {
// SAFETY: benchmark-only code; single-threaded setup phase, no concurrent env access.
unsafe { std::env::set_var("RAYON_NUM_THREADS", cores.to_string()) };
// Force rayon to reinitialize — this only works for the first call.
// For accurate per-iteration control, we set it before the group.
b.iter(|| read_dataset(&bytes))
});
}
group.finish();
}
fn bench_size_scaling(c: &mut Criterion) {
let mut group = c.benchmark_group("parallel_deflate_sizes");
group.sample_size(15);
// Use all available cores (auto)
for n in [1_000_000, 5_000_000, 10_000_000] {
let bytes = make_deflate_file(n);
let label = format!("{}M", n / 1_000_000);
group.bench_function(format!("{label}_parallel"), |b| {
b.iter(|| read_dataset(&bytes))
});
}
group.finish();
}
criterion_group!(benches, bench_core_scaling, bench_size_scaling);
criterion_main!(benches);