A repository to test different performance optimizations in a sparse matrix computation. Read the post explaining the benchmark: https://willcrichton.net/notes/k-corrset/

To run the benchmark, first generate the synthetic data:

mkdir data
cargo run --release --bin gen-data -- 60000 200 0.2 > data/data-large.json

Then run the benchmark:

cargo bench

To run a single configuration, you can use the top binary. It takes at least two arguments: the name of the outer loop (like 2_batched) and the name of the inner loop (like 6_alloc). Check out the outer_names and inner_names functions to see a list of all the names. You can also optionally provide a value of k (default 5) and a name for the dataset (default "large").

To get a quick-and-dirty ETA for the full computation, you can run with a progress bar enabled:

cargo run --release --bin top --features progress -- 2_batched 6_alloc

To get a profile for the configuration, install the samply tool. Then run:

cargo build --release --bin top
samply record ./target/release/top 2_batched 6_alloc

Let it run for ~30s, then hit Ctrl C and the profile should open up in your browser.