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Add fast filtering step to tig-benchmarker.

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This commit is contained in:
FiveMovesAhead 2024-07-04 12:32:16 +08:00
parent 8b6794c0fb
commit e7dda7e80d
4 changed files with 15062 additions and 4 deletions
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5997
tig-benchmarker/Cargo.toml
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4
tig-benchmarker/Dockerfile
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@ -1,8 +1,10 @@
FROM rust:1.77
ARG features=""
WORKDIR /app
COPY . .
RUN cargo build -p tig-benchmarker --bins --release --no-default-features --features standalone
RUN cargo build -p tig-benchmarker --bins --release --no-default-features --features "standalone ${features}"
RUN cp target/release/tig-benchmarker /usr/local/bin/tig-benchmarker
RUN chmod +x /usr/local/bin/tig-benchmarker

18
tig-benchmarker/README.md
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@ -26,7 +26,8 @@ There are two ways to start the master benchmarker:
1. Compile into exectuable and then run the executable:
```
cargo build -p tig-benchmarker --release --no-default-features --features standalone
ALGOS_TO_COMPILE="" # See notes
cargo build -p tig-benchmarker --release --no-default-features --features "standalone ${ALGOS_TO_COMPILE}"
# edit below line for your own algorithm selection
echo '{"satisfiability":"schnoing","vehicle_routing":"clarke_wright","knapsack":"dynamic"}' > algo_selection.json
./target/release/tig-benchmarker <address> <api_key> algo_selection.json
@ -34,13 +35,24 @@ There are two ways to start the master benchmarker:
2. Compile executable in a docker, and run the docker:
```
docker build -f tig-benchmarker/Dockerfile -t tig-benchmarker .
ALGOS_TO_COMPILE="" # See notes
docker build -f tig-benchmarker/Dockerfile --build-arg features="${ALGOS_TO_COMPILE}" -t tig-benchmarker .
# edit below line for your own algorithm selection
echo '{"satisfiability":"schnoing","vehicle_routing":"clarke_wright","knapsack":"dynamic"}' > algo_selection.json
docker run -it -v $(pwd):/app tig-benchmarker <address> <api_key> algo_selection.json
```
**Note:**
**Notes:**
* Setting `ALGOS_TO_COMPILE` will run the selected algorithms directly in your execution environment to filter for nonces that results in solutions. Nonces that are filtered will then be re-run in the WASM virtual machine to compute the necessary solution data for submission.
* **WARNING** before setting `ALGOS_TO_COMPILE`, be sure to thoroughly review the algorithm code for malicious routines as it will be ran directly in your execution environment (not within a sandboxed WASM virtual machine)!
* `ALGOS_TO_COMPILE` is a space separated string of algorithms with format `<challenge_name>_<algorithm_name>`. Example:
```
ALGOS_TO_COMPILE="satisfiability_schnoing vehicle_routing_clarke_wright knapsack_dynamic"
```
* Every 10 seconds, the benchmarker reads your json file path and uses the contents to update its algorithm selection.
* You can see available algorithms in the dropdowns of the [Benchmarker UI](https://play.tig.foundation/benchmarker)

9047
tig-benchmarker/src/benchmarker/run_benchmark.rs
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