/rust_convolution

Primary LanguageRust

rust_convolution

A simple 2d convolution in Rust, as fast as possible!

This is a collection of suggested Rust functions that were proposed as solutions to matching the performance of C. The suggestions come from respondents to a question on the Rust user forum: "Rust performance help (convolution)" : https://users.rust-lang.org/t/rust-performance-help-convolution/44075

The problem is a simple 500-element convolution kernel run over a 20-million-element data set. See convolution.c in the top-level directory.

The Rust solutions are each held in modules named after their contributor on the above forum thread.

Build and Run

Build and run is a program that times the various solutions for the 20-million-element convolution and prints the results:

    $ git clone https://github.com/ZiCog/rust_convolution/edit/master/README.md
    $ cd rust_convolution
    $ cargo run --release

Or run the benchmarks, which use a much smaller kernel and data set:

    $ cargo bench

Results

The full convolution produces times like these on my Intel PC:

zso::convolution:            Duration 24365 ms
119.04489  127.622635
zso::convolution_ffi:        Duration 1396 ms
119.04485  127.62263
bjorn3::convolution:         Duration 7074 ms
119.04483  127.62263
dodomorandi::convolution:    Duration 8175 ms
119.04489  127.622635
pcpthm::convolution:         Duration 1328 ms
119.04485  127.62263
zicog::convolution:          Duration 1310 ms
119.04485  127.62263
zicog::convolution_fast:     Duration 1358 ms
119.04485  127.62263
zicog::convolution_safe:     Duration 8070 ms
119.04489  127.622635
alice::convolution_serial:   Duration 1341 ms
119.04485  127.62263
alice::convolution_parallel: Duration 348 ms
119.04485  127.62263

and the benchmark output:

test tests::bench_alice_convolution_parallel ... bench:      22,066 ns/iter (+/- 1,441)
test tests::bench_alice_convolution_serial   ... bench:       5,500 ns/iter (+/- 176)
test tests::bench_bjorn3_convolution         ... bench:      12,900 ns/iter (+/- 434)
test tests::bench_dodomorandi_convolution    ... bench:       8,695 ns/iter (+/- 296)
test tests::bench_pcpthm_convolution         ... bench:       5,470 ns/iter (+/- 283)
test tests::bench_zicog_convolution          ... bench:       4,445 ns/iter (+/- 88)
test tests::bench_zicog_convolution_fast     ... bench:       4,723 ns/iter (+/- 109)
test tests::bench_zicog_convolution_safe     ... bench:       8,302 ns/iter (+/- 287)
test tests::bench_zso_convolution            ... bench:      25,268 ns/iter (+/- 852)
test tests::bench_zso_convolution_ffi        ... bench:       4,667 ns/iter (+/- 149)

Commentary:

  1. Many people suggested different Rust "functional" style approaches to this problem, some of them involving use of "unsafe". It turns out that for single-thread performance the normal procedural style I wrote naïvely from the C example is the fastest by a wide margin. Beware of those who suggest functional style and/or "unsafe" to get performance in Rust; it is not always true!

  2. The fastest "functional" style solution, by @alice, matches my procedural effort. It is also pure poetry. So short, sweet and to the point compared to all the others.

  3. For multi-core parallelism @alice's functional style wins hands down. Also, it only required a 4-character change to the source to parallelize it!

  4. The parallel solution is painfully slow on small data sets, as shown in the benchmark figures.