- Nov 21, 2024
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This MR adds an option to perform erasure coding using FFT rather than using a matrix. It also adds the field FP128 in the list of curves Note that there is a redundant function `random_loss` into benchmarks/bin/fec.rs and examples/fec.rs
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- Aug 06, 2024
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STEVAN Antoine authored`algebra`, `field` and `linalg` were doing extremely similar things before... this MR merges them into a single module `algebra` - old `algebra` and `field` are at the root of the new `algebra` - old `linalg` is now `algebra::linalg` all references to these have been fixed in the rest of the codebase and the features have been tuned to work fine.
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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 │ ├──...
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- May 23, 2024
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STEVAN Antoine authored
up until now, elliptic curves have been hardcoded in the benchmarks, forcing to run them on all supported curves... this MR makes it possible to use only a subset of curves. >
💡 **Note** > when running the same commands from !104, minus the "inbreeding" ones which are not affected by this MR, the time goes from 12min 33sec to 4min 28sec🎉 ## TODO - [x] setup - [x] commit - [x] recoding - [x] fec - [ ] linalg - [ ] setup size - [ ] field operations - [ ] group operations >💡 **Note** > because all the unticked bullet points above are far from critical to the paper and do require to measure all curves, i won't change these for now
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- Apr 29, 2024
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we want to compare - _naive recoding_: k-decoding followed by 1-encoding - _komodo recoding_: k-recoding with $k = \#\text{shards}$ # results >💡 **Note** > we see that the _naive recoding_ is around 100 times slower compared to the _komodo recoding_🎉 >💡 **Note** > the format of the labels is always `{curve} / {k}`  
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- Apr 26, 2024
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STEVAN Antoine authored
this MR adds - `examples/benches/bench_fec.rs` to the list of example benches - instructions on how to run the new benchmark and plot the results ## results   
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