From ac144c7bf9c43351f726147653fc777ad5f310df Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kalle=20Ahlstr=C3=B6m?= Date: Tue, 30 Apr 2024 00:36:43 +0300 Subject: [PATCH] improvement(final?): use multithreading to utilize all threads --- README.md | 52 ++++++++++++++++++ multithreaded-main-thread.png | Bin 0 -> 923446 bytes src/main.rs | 100 +++++++++++++++++++++++++++++++--- 3 files changed, 143 insertions(+), 9 deletions(-) create mode 100644 multithreaded-main-thread.png diff --git a/README.md b/README.md index 98a8c67..625218b 100644 --- a/README.md +++ b/README.md @@ -105,6 +105,7 @@ Benchmarks and profiling results shown below are run against a `measurements.txt | [a custom hash function](#using-a-custom-hash-function) | 30.427 s ± 0.455 | -8,043 s (-21%) | Use a custom hash function for the hashmap that is used by the Rust Compiler | | [Custom chunked reader](#chunked-reader-to-reduce-memory-footprint--prepare-for-parallellism) | 29.310 s ± 0.276 | -1,117 s (-4%) | Write a custom chunked file reader to prepare for parallellism and reduce memory allocation | | [Tweak chunk size](#tweaking-the-chunk_size) | 28.663 s ± 0.546 | -0,647 s (-2%) | Small tweak for the fixed buffer-size created in previous improvement | +| [Multithreading](#multithreading) | 3.747 s ± 0.093 | -24,916 s (-87%) | Multithread the program to utilize all cores on the system | ### Initial Version @@ -433,3 +434,54 @@ Benchmark 1: ./target/release/brc-rs Time (mean ± σ): 28.663 s ± 0.546 s [User: 26.501 s, System: 1.259 s] Range (min … max): 28.304 s … 29.631 s 5 runs ``` + +### Multithreading + +We have now prepared our program to be able to handle multiple threads at once, and we can start utilizing them to speed up the program. + +One might wonder why this wasn't done earlier, but profiling and optimizing a single-threaded program is much more straightforward than a multithreaded one. +As long as we keep the fact that we are going to use multiple threads in mind, we can optimize the single-threaded program to be as fast as possible, and then just spawn more threads to do the same work. + +We need to somehow divide the work we have done sequentially into multiple threads. +This can be achieved by dividing the file into chunks and then processing each chunk in a separate thread. + +However, we need to be careful when creating the chunks, as we need to make sure that we don't split the lines in the middle. +To do this, we can "peek into" the file at `chunk_size`, and then read forwards until we find a newline character. +Then set the next chunk to start after that newline character. + +After creating the chunks, we can then spawn a thread for each chunk, and have them process the chunk in parallel. + +After a thread is finished, it will insert its results into the shared hashmap, locked by a [`Mutex`](https://doc.rust-lang.org/std/sync/struct.Mutex.html). +As we are using a `Mutex`, only one thread can access the hashmap at a time, blocking other threads from accessing it until the lock is released. +This time isn't a problem, as the amount of time spend holding the lock is minimal compared to the time spent processing the data. + +```sh +~/src/github/brc-rs (main*) » ./bench.sh +Benchmark 1: ./target/release/brc-rs + Time (mean ± σ): 3.747 s ± 0.093 s [User: 29.739 s, System: 2.102 s] + Range (min … max): 3.679 s … 3.910 s 5 runs +``` + +![Flamegraph of the multithread program, showing the main thread](multithreaded-main-thread.png) +As we can see from the flamegraph, the main thread is mostly waiting for the other threads to finish their work. +Other threads are then doing the actual work of reading the file and processing the data. + +Looking at the threads doing the processing, we can see that there are sections where some of the threads have 0% CPU usage. +This is due to I/O blocking, as the thread is waiting for the file to be read into memory. + +A slight trick to improve the I/O blocking nature was to create more chunks than there are threads available. +This allows the OS scheduler to switch between threads, potentially enabling I/O blocked threads to be swapped to threads where I/O is not blocked. + +## Conclusion + +The final(?) result is a program that can process 1 billion rows in 3.7 seconds on a 10-core M1 Macbook Pro. +This is a 97% improvement over the initial version. + +A big chunk of the improvement came from multithreading in the end, but without the single-core optimizations done first, we couldn't have been able to parallelize the program as effectively. +Keeping the program single-threaded first allowed us to iterate on the program more easily. + +The program is now utilizing all cores on the system, and the I/O blocking is distributed more evenly throughout the program. +The memory footprint is kept low, and the program is quite optimized. + +More optimizations could be done, for instance making line parsing branchless, using memory-mapped files, but the latter would require use of `unsafe`-code or external crates, which were not in scope for this project. +For now, I'm quite happy with the results, and I'll leave it at that (for now?) diff --git a/multithreaded-main-thread.png b/multithreaded-main-thread.png new file mode 100644 index 0000000000000000000000000000000000000000..e2e073f82a3f6153c9c3ffde4a895c383a6a5864 GIT binary patch literal 923446 zcmc$G1zS{Y+wKt3B_K!*Lw8H3bR(d2r*y~A2ndMMok~hecXvy7cX!ubyzl<@FWArX zdCWKiEO8wx?(576{h%m?jzWk60)fzFq{UT0AY9-r3NsP{@Y3jbq6)mgIH^d9f=Y&o zcY!agO*Lf96cj-8zH2)w@h zi3FZ6|K`81us>n{XA4}=Pq_bikHY-2>3C@=9`J%}FRkeW0^w1;JYi&1C{I8j5s-}d z`;YE02WiNOij$;0z7-l~-OVxNa?<45{Znf!HuSMvvA-FaXye4Q%jGob<&;BYm6fB( zwW+chXUmCd_#0go)O_!vw4TLOjIpqjq|6kY#Klt)M5hJ5a_|EQbt*aK0jI?xbwBigc zawO>Ae(3bWfBEty_M9d1tVIq=c(Ne#ub-0gWD!x(#yxUY2n14iZ*)&70{d@2?EA3) zF154<2Erqwp*5PkKk5AU4}&y>0hyBe8>N=7##W2CKYZl-fBi532R`x^e&qob1?3Cq z110MR8}=6bYU%%l{Yc>P|M^oyMqWNvWZxVa1jp<^EZ~g|f%&%|y@aqQPp>rQS`0Km 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zl1bxFfxi>zfAaRZbC)^E)Z!lM2Q+x)-wS?XyQ>h$0lcmi1RB4>A*t{=r2PImpVrj8 z7PnMK3H&P`#Om7GJ7}s*>T1$OKH++GqREXJg$Do>`=P^R(221t<^82mDb}oj@|MvMhc0OtL=8N8O zI68AyUz(K<4L?zl59W zRa&krwrjm)M8r?wMxopi-sJzR#dhUN|No`_Up%W!uorix$anEX71Ads@Y_UFiGS-h zdO^U7%Oc6wwW|ZtIR6^aG|?0@V8%}6gQq~G3vD!Fb<(Px;X for WeatherStationStats { + type Output = Self; + + fn add(self, rhs: &mut Self) -> Self::Output { + WeatherStationStats { + min: self.min.min(rhs.min), + max: self.max.max(rhs.max), + sum: self.sum + rhs.sum, + count: self.count + rhs.count, + } + } +} fn parse_line(line: &[u8]) -> (&[u8], i64) { // we know that the measurement is pure ASCII and is at max 5 characters long // based on this we can find the semicolon faster by doing at most 6 byte comparisons by iterating the reversed bytes @@ -46,7 +61,11 @@ fn parse_line(line: &[u8]) -> (&[u8], i64) { // reversed index 2, is the first whole number, "shift" it twice to the left with * 100 (b, 3) => measurement += (b - b'0') as i64 * 100, // Data is of incorrect format, as in indices 1, 4 or 5 always must be one of the other characters - _ => unreachable!(), + (b, _) => panic!( + "{} , {:#?}", + String::from_utf8(vec![*b]).unwrap(), + String::from_utf8(line.to_vec()) + ), } } ( @@ -58,13 +77,76 @@ fn parse_line(line: &[u8]) -> (&[u8], i64) { }, ) } - +struct Chunk { + start_point: u64, + len: usize, + outer_map: Arc, WeatherStationStats>>>, +} +fn chunk_le_file( + mut f: T, + file_len: usize, + arccimuuteksi: Arc, WeatherStationStats>>>, +) -> Vec { + let chunk_count = std::thread::available_parallelism() + .map(NonZeroUsize::get) + .unwrap_or(1) + // do a sneaky 4x chunks vs available threads to allow OS scheduler to switch between threads, + // potentially enabling I/O blocked threads being swapped to threads where I/O is not blocked. + // 4 was tested to provide best perf with both M1 Macbook Max and Ryzen 5950x + * 4; + let chunk_size = file_len / chunk_count + 1; + // max length of line is 100 bytes station name, ';', '-99.9', '\n' + let mut tmp_arr = Vec::with_capacity(107); + let mut res = vec![]; + let mut cur_start = 0; + for _ in 0..chunk_count { + f.seek(std::io::SeekFrom::Current(chunk_size as i64)) + .unwrap(); + f.read_until(b'\n', &mut tmp_arr).unwrap(); + let end_pos = f.stream_position().unwrap(); + res.push(Chunk { + start_point: cur_start, + len: (end_pos - cur_start) as usize, + outer_map: arccimuuteksi.clone(), + }); + tmp_arr.clear(); + cur_start = end_pos + } + res +} fn calc(file_name: Option) -> String { - let f = File::open(file_name.as_deref().unwrap_or("measurements.txt")).unwrap(); - - let stations = aggregate_measurements(f); + let file_name: Arc = file_name.unwrap_or("measurements.txt".into()).into(); + let f = File::open(file_name.to_string()).unwrap(); + let file_len = f.metadata().unwrap().len() as usize; + let stations = Arc::new(Mutex::new(HashMap::, WeatherStationStats>::new())); + let chunks = chunk_le_file(BufReader::new(f), file_len, stations.clone()); + let handles = chunks + .into_iter() + .map(|c| { + let file_name = file_name.clone(); + thread::spawn(move || { + let mut f = File::open(file_name.to_string()).unwrap(); + f.seek(std::io::SeekFrom::Start(c.start_point)).unwrap(); + let f = f.take(c.len as u64); + let stations_välipala = aggregate_measurements(f); + let mut stations = c.outer_map.lock().unwrap(); + for (k, v) in stations_välipala { + match stations.get_mut(&k) { + Some(jutska) => *jutska = v + jutska, + None => { + stations.insert(k, v); + } + } + } + }) + }) + .collect::>(); + for h in handles { + h.join().unwrap() + } + let lock = stations.lock().unwrap(); + let mut res = lock.iter().collect::>(); - let mut res = stations.into_iter().collect::>(); res.sort_unstable_by(|a, b| a.0.cmp(&b.0)); String::from("{") + &res @@ -72,7 +154,7 @@ fn calc(file_name: Option) -> String { .map(|(station, stats)| { format!( "{}={:.1}/{:.1}/{:.1}", - String::from_utf8(station).unwrap(), + String::from_utf8_lossy(station), stats.min as f64 / 10.0, stats.mean(), stats.max as f64 / 10.0

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