- May 29, 2024
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STEVAN Antoine authoredin `./bins/inbreeding/`, this MR does - refactor the "list item drawing" from `environment.rs` and `strategy.rs` into the `draw_unique_elements` function of new `random.rs` module - use a `HashSet` to draw unique indices in the slice of "things" to draw from and then extracts the items corresponding to these indices ## results ```bash use ./bins/inbreeding use std bench const PRNG_SEED = 0 const OPTS = { nb_bytes: (10 * 1_024), k: 10, n: 20, nb_measurements: 100, nb_scenarii: 10, measurement_schedule: 1, measurement_schedule_start: 2_000, max_t: 2_000, strategies: [ "single:5" ], environment: null, } def run [rev: string] { git co $rev inbreeding build let a = bench --rounds 5 { inbreeding run --options ($OPTS | update environment "fixed:0") --prng-seed $PRNG_SEED } let b = bench --rounds 5 { inbreeding run --options ($OPTS | update environment "fixed:1") --prng-seed $PRNG_SEED } { 0: $a, 1: $b, } } let main = run a29b511d let mr = run fix-shuffle ``` ```bash let table = [ [env, main, mr, improvement]; ["fixed:0", $main."0".mean, $mr."0".mean, (($main."0".mean - $mr."0".mean) / $main."0".mean * 100)], ["fixed:1", $main."1".mean, $mr."1".mean, (($main."1".mean - $mr."1".mean) / $main."1".mean * 100)], ] $table | to md --pretty ``` | env | main | mr | improvement | | ------- | ----------------------- | ----------------------- | ------------------ | | fixed:0 | 8sec 504ms 794µs 784ns | 6sec 353ms 206µs 645ns | 25.298530930431912 | | fixed:1 | 727ms 648µs 292ns | 639ms 443µs 782ns | 12.12186037811795 | the improvement is quite nice, even though not huge, but the code is cleaner anyways🙏
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- May 28, 2024
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STEVAN Antoine authored
## new structure for the repository - benchmarks are in `./benchmarks/` and can be run with either `cargo run --package benchmarks --bin <bench>` or the commands in `./benchmarks/README.md` ``` ├── Cargo.toml ├── README.md └── src └── bin ├── commit.rs ├── fec.rs ├── linalg.rs ├── operations │ ├── curve_group.rs │ └── field.rs ├── recoding.rs ├── setup.rs └── setup_size.rs ``` - examples are now in `./bins/` as standalone binaries and can be run either with `cargo run --package <pkg>` or with the help of the `cargo bin` command from `.nushell/cargo.nu` ``` ├── curves │ ├── Cargo.toml │ ├── README.md │ └── src │ └── main.rs ├── inbreeding │ ├── build.nu │ ├── Cargo.toml │ ├── consts.nu │ ├── mod.nu │ ├── plot.nu │ ├── README.md │ ├── run.nu │ └── src │ ├── environment.rs │ ├── main.rs │ └── strategy.rs ├── rank │ ├── Cargo.toml │ └── src │ └── main.rs └── rng ├── Cargo.toml └── src └── main.rs ``` - Nushell modules are now located in `./.nushell/` ## changelog apart from the changes to the general structure of the repo: - `binary.nu` -> `.nushell/binary.nu` - new `cargo bin` command from `.nushell/cargo.nu` - `error throw` is now defined in `.nushell/error.nu` - main TOML has been greatly simplified because the dependencies of "examples" have been moved to the associated crates - the rest is basically the same but in the new structure
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- May 27, 2024
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STEVAN Antoine authored
- add `--prng-seed: u8` to fix the random number generator seed ## example by running the following snippet, we get - `first.123.png` and `second.123.png` with `--prng-seed 123` which are the same - `first.111.png` and `second.111.png` with `--prng-seed 111` which are the same - `first.111.png` and `first.123.png` are different ```bash use ./scripts/inbreeding const OPTS = { nb_bytes: (10 * 1_024), k: 10, n: 20, nb_scenarii: 10, nb_measurements: 10, measurement_schedule: 1, measurement_schedule_start: 0, max_t: 50, strategies: [ "single:1", "double:0.5:1:2", "single:2" "double:0.5:2:3", "single:3" "single:5" "single:10", ], environment: "random-fixed:0.5:1", } inbreeding build inbreeding run --options $OPTS --prng-seed 123 --output /tmp/first.123.nuon inbreeding plot /tmp/first.123.nuon --options { k: $OPTS.k } --save /tmp/first.123.png inbreeding run --options $OPTS --prng-seed 123 --output /tmp/second.123.nuon inbreeding plot /tmp/second.123.nuon --options { k: $OPTS.k } --save /tmp/second.123.png inbreeding run --options $OPTS --prng-seed 111 --output /tmp/first.111.nuon inbreeding plot /tmp/first.111.nuon --options { k: $OPTS.k } --save /tmp/first.111.png inbreeding run --options $OPTS --prng-seed 111 --output /tmp/second.111.nuon inbreeding plot /tmp/second.111.nuon --options { k: $OPTS.k } --save /tmp/second.111.png ``` | seed | first | second | | ---- | ----- | ------ | | 123 |  |  | | 111 |  |  | -
STEVAN Antoine authored
- add a timestamp to all the measurements of the _diversity_ from `inbreeding/mod.rs` - allow to delay the measurement starts with `--measurement-schedule-start`, to help completing already existing measurements >
❗ **Important** > existing measurement files will have to change shape from > ``` > table<strategy: string, diversity: list<float>> > ``` > to > ``` > table<strategy: string, diversity: table<t: int, diversity: float>> > ``` -
STEVAN Antoine authored
makes sure - "inbreeding" experiment quits when there are less than $k$ shards - `fec::decode` returns `KomodoError::TooFewShards` when no shards are provided
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- May 24, 2024
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STEVAN Antoine authored
just a small QoL improvement
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STEVAN Antoine authored
this MR is two-fold - refactor `run.nu` and `plot.nu` from `scripts/inbreeding/` into Nushell modules with `--options` as argument instead of `options.nu` (a7cebb95, 6b72191f and 5f1c4963) - introduce another level of depth to the measurements (a0e52e95) >
💡 **Note** > in the table below > - $s$ is the number of recoding scenarii averages together > - $m$ is the number of measurements per point > - two iterations of the same experiment are shown side by side for comparison s | m | . | . :--:|:----:|:-------------------------:|:-------------------------: 1 | 10 |  |  1 | 100 |  |  1 | 1000 |  |  10 | 100 |  |  100 | 10 |  |  100 | 100 |  |  we can see that - the smaller the $s$, the more different the two figures are on each line -> this is likely due to the fact that, if only one recoding scenario is used, then repeating the same experiment will result in very different results and measurements. Running the same experiment $s$ times and averaging helps reducing the variance along this axis - the smaller the $m$, the more noisy the measures of each points -> this is simply because, when $m$ is small, the variance of the empirical means measured for each point is higher ## final results  
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- May 23, 2024
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STEVAN Antoine authored
this MR moves run and plot commands from `examples/benches/README.md` to - `scripts/setup/`: `run.nu` and `plot.nu` - `scripts/commit/`: `run.nu` and `plot.nu` - `scripts/recoding/`: `run.nu` and `plot.nu` - `scripts/fec/`: `run.nu` and `plot.nu` - `scripts/inbreeding/`: `build.nu`, `run.nu` and `plot.nu` to generate all the figures at once ```bash use scripts/setup/run.nu; seq 0 13 | each { 2 ** $in } | run --output data/setup.ndjson use ./scripts/setup/plot.nu; plot data/setup.ndjson --save ~/setup.pdf use scripts/commit/run.nu; seq 0 13 | each { 2 ** $in } | run --output data/commit.ndjson use ./scripts/commit/plot.nu; plot data/commit.ndjson --save ~/commit.pdf use scripts/recoding/run.nu; seq 0 18 | each { 512 * 2 ** $in } | run --ks [2, 4, 8, 16] --output data/recoding.ndjson use ./scripts/recoding/plot.nu; plot data/recoding.ndjson --save ~/recoding.pdf use scripts/fec/run.nu; seq 0 18 | each { 512 * 2 ** $in } | run --ks [2, 4, 8, 16] --output data/fec.ndjson use ./scripts/fec/plot.nu; plot encoding data/fec.ndjson --save ~/encoding.pdf use ./scripts/fec/plot.nu; plot decoding data/fec.ndjson --save ~/decoding.pdf use ./scripts/fec/plot.nu; plot e2e data/fec.ndjson --save ~/e2e.pdf use ./scripts/fec/plot.nu; plot combined data/fec.ndjson --recoding data/recoding.ndjson --save ~/comparison.pdf use ./scripts/fec/plot.nu; plot ratio data/fec.ndjson --recoding data/recoding.ndjson --save ~/ratio.pdf ./scripts/inbreeding/build.nu ./scripts/inbreeding/run.nu --output data/inbreeding.nuon ./scripts/inbreeding/plot.nu data/inbreeding.nuon --save ~/inbreeding.pdf ``` >💡 **Note** > this took around 27min 18sec in total on my machine with 14min 45sec for the inbreeding section only and 12min 33sec for the rest -
STEVAN Antoine authored
this MR: - refactors the "inbreeding" example into `examples/inbreeding/` - adds `--strategy` and `--environment` - `Strategy::draw` will draw the number of shards to keep for recoding - `Environment::update` will update the pool of shards by losing some of them
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- May 21, 2024
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STEVAN Antoine authored
- update `benches/README.md` to use `cargo run --release --example ...` - add `build-examples` to `Makefile` to build all examples in release ### minor change add two `eprintln!` in `inbreeding.rs` to show the experiment parameters
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STEVAN Antoine authored
- new `scripts/plot.nu` with common tools and options - better sets of parameters - better commands in `benches/README.md`
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- May 13, 2024
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STEVAN Antoine authored
this MR makes the plot a bit nicer. ## new figures       
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- May 02, 2024
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STEVAN Antoine authored
this MR adds `examples/inbreeding.rs` which allows to do two things - _naive recoding_: in order to generate a new random shard, we first $k$-decode the whole data and then $1$-encode a single shard - _true recoding_: to achieve the same goal, we directly $k$-recode shards into a new one ## the scenario regardless of the _recoding strategy_, the scenario is the same 1. data is split into $k$ shards and $n$ original shards are generated 2. for a given number of steps $s$, $k$ shards are drawn randomly with replacement and we count the number of successful decoding, given a measure of the _diversity_, $$\delta = \frac{\#success}{\#attempts}$$ 3. create a new _recoded shard_ and add it to the $n$ previous ones, i.e. $n$ increases by one 4. repeat steps 2. and 3. as long as you want ## results 
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