parasailors is a set of Rust bindings to the parasail vectorized pairwise sequence alignment library. parasail provides vectorized/SIMD versions of the Smith-Waterman, Needleman-Wunsch, semi-global alignment algorithms for pairwise DNA/protein sequence alignment.
The original C library provides hundreds of functions to use for alignment. Even though they only implement 3 algorithms, they vary based on which SIMD ISA is used, the integer width for the underlying calculations, whether statistics of the alignment are calculated, whether rows or columns from the dynamic programming matrix are returned, etc. However, the library also provides automatic SIMD feature detection (to dynamically dispatch functions based on CPU architecture), and an overflow-detecting method for picking the correct integer width for calculations. In order to simplify use in the absence of more mature SIMD feature detection in Rust, these dispatching functions are what are currently called in parasailors.
WARNING: The bindings are currently in an immature state. If you find something worrying, please open an issue :).
Using the same 5kb random sequences on the same machine (CPU supports AVX2).
$ rustc --version
rustc 1.8.0-nightly (3c9442fc5 2016-02-04)
$ cat /proc/cpuinfo | grep "model name"
model name : Intel(R) Xeon(R) CPU E5-2603 v3 @ 1.60GHz
# ... other cores omittedA very rough estimate suggests that on my machine, parasailors achieves a 98.7% - 98.9% speedup vs rust-bio's sequential alignment, with the obvious tradeoff of needing to call out to native C code to achieve the speedup.
The excellent rust-bio crate's (sequential) pairwise alignment.
$ git clone https://github.com/rust-bio/rust-bio
# ...
$ git checkout v0.4.0
# ...
$ multirust run nightly cargo bench
# ... other benchmarks omitted
test bench_aligner_wc_global ... bench: 992,524,365 ns/iter (+/- 12,619,674)
test bench_aligner_wc_local ... bench: 1,041,005,609 ns/iter (+/- 14,608,932)
test bench_aligner_wc_semiglobal ... bench: 990,937,047 ns/iter (+/- 7,047,941)$ multirust run nightly cargo bench
# ...
test bench_global_fresh_profile ... bench: 14,096,259 ns/iter (+/- 50,964)
test bench_global_reuse_profile ... bench: 12,647,865 ns/iter (+/- 55,200)
test bench_local_fresh_profile ... bench: 11,006,416 ns/iter (+/- 35,788)
test bench_local_reuse_profile ... bench: 9,543,404 ns/iter (+/- 49,748)
test bench_semiglobal_fresh_profile ... bench: 13,909,503 ns/iter (+/- 30,403)
test bench_semiglobal_reuse_profile ... bench: 12,465,250 ns/iter (+/- 52,930)[dependencies]
parasailors = "0.3"A brief usage example with an identity substitution matrix (although PAM and BLOSUM are available as well):
use parasailors::*;
// everything operates on &[u8] to avoid copying and reparsing
// this is the format that rust-bio provides when parsing FASTA/FASTQ
let query_sequence = b"AAAAAAAAAA";
let reference = b"AAAAAAAAAACCCCCCCCCCGGGGGGGGGGTTTTTTTTTTTNNNNNNNNN";
// the MatrixType enum allows us to type-safely select which matrix to use
let identity_matrix = Matrix::new(MatrixType::Identity);
// profiles can be reused across many alignments, saving overhead
let profile = Profile::new(query_sequence, &identity_matrix);
// parasail provides us with fast implementations for multiple alignment types
assert_eq!(10, local_alignment_score(&profile, reference, 1, 1));
assert_eq!(10, semi_global_alignment_score(&profile, reference, 1, 1));
assert_eq!(-30, global_alignment_score(&profile, reference, 1, 1));See the documentation for more usage examples.
- Profile-reusing alignment scores
- Type-safe usage of many different substitution matrices
- Quick one-off alignment functions that automatically create profiles
- Gap statistics calculations
- CIGAR strings
- Returning rows and columns of dynamic-programming matrices for further calculations
- Manually selecting which SIMD features to use
- Manually selecting algorithm implementations (striped, scan, diagonal, blocked)
- Manually selecting integer bit-width
- Compile-time creation of non-included substitution matrices
The sub-crate with the FFI bindings (parasail_sys) uses an autotools build for the C library (there aren't any distro packages for parasail, AFAIK), so you'll need a compatible toolchain. It's recommended to build on a system with a comparable SIMD instruction set to the target machine (ideally the target machine itself). The parasail C library generally does a good job of feature detection, but your compiler may balk at producing vector instructions for an architecture on which it's not running, potentially robbing some performance.
Contributions are more than welcome, especially if you're more familiar than I am with C (which is likely) or bioinformatics (which is also likely). I encourage any bug reports or requests on GitHub Issues, and I'm happy to review any pull requests.
If you have questions that aren't related to a bug or requested feature, please email me or find me in the Rust IRC channels (usually #rust and #rust-beginners, nick is the same as GitHub username).
All of the Rust code here is licensed under the MIT license. However, the code under parasail_sys/parasail_c is not mine to license and adheres to the Batelle BSD-style license.
If needed, please cite the original paper for parasail:
Daily, Jeff. (2016). Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments. BMC Bioinformatics, 17(1), 1-11. doi:10.1186/s12859-016-0930-z
http://dx.doi.org/10.1186/s12859-016-0930-z
I take no responsibility for the nice implementations of these algorithms, and I do think that the original author should be rewarded if this crate is used in an academic context.