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Update artifact and add configs and plots
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‎.gitignore‎

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# Ignore config files
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**/*.json
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# Figs
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*.pdf
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*.png

‎README.md‎

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# ...
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```
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#### Plain Metrics with Prios: Aggregators
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#### Plain Metrics with Prio: Aggregators
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Run the aggregators in two separate shells. They will wait and be ready to
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process client requests.
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```bash
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more efficient implementation uses the `Count` circuit and is in the [`Count`
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branch](https://github.com/TrustworthyComputing/mastic/tree/Count).
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## Troubleshooting
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Mastic relies on the [tarpc](https://github.com/google/tarpc) library which has
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a limit on the size of the RPC messages. As such, you might see an error similar
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to the following:
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```shell
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thread 'main' panicked at src/bin/driver.rs:335:
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called `Result::unwrap()` on an `Err` value: Disconnected
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```
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which is caused by the RPC batch sizes.
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To fix this reduce the batch sizes of either the reports or the FLPs (or both).
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Note that this does not affect the online running time, but it affects the
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upload time from the `driver` to the Mastic servers.
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```toml
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add_report_share_batch_size = 1000
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query_flp_batch_size = 100000
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```
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## Disclaimer
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ARTIFACT-EVALUATION.md renamed to artifact/README.md

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```
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etc. These parameters are sufficient to reproduce all our results -- all our
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experiments in the paper specify the parameters used.
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To reproduce our experiments, use the configs from the [configs](./configs/)
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directory and the scripts from the [plots](../plots/) directory.

‎artifact/configs/figure-3/Mastic-m=1,n=128.toml‎

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# For more efficiency, use the "count" branch in case m = 1.
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mode.weighted_heavy_hitters.threshold = 0.01
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data_bits = 128
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hist_buckets = 1
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server_0 = "0.0.0.0:8000"
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server_1 = "0.0.0.0:8001"
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add_report_share_batch_size = 100
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query_flp_batch_size = 100000
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zipf_unique_buckets = 1000
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zipf_exponent = 1.03

‎artifact/configs/figure-3/Mastic-m=1,n=256.toml‎

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# For more efficiency, use the "count" branch in case m = 1.
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mode.weighted_heavy_hitters.threshold = 0.01
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data_bits = 256
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hist_buckets = 1
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server_0 = "0.0.0.0:8000"
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server_1 = "0.0.0.0:8001"
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add_report_share_batch_size = 100
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query_flp_batch_size = 100000
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zipf_unique_buckets = 1000
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zipf_exponent = 1.03

‎artifact/configs/figure-3/Mastic-m=1,n=64.toml‎

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# For more efficiency, use the "count" branch in case m = 1.
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mode.weighted_heavy_hitters.threshold = 0.01
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data_bits = 64
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hist_buckets = 1
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server_0 = "0.0.0.0:8000"
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server_1 = "0.0.0.0:8001"
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add_report_share_batch_size = 100
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query_flp_batch_size = 100000
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zipf_unique_buckets = 1000
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zipf_exponent = 1.03

‎artifact/configs/figure-3/Mastic-m=10,n=128.toml‎

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mode.weighted_heavy_hitters.threshold = 0.01
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data_bits = 128
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hist_buckets = 9
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server_0 = "0.0.0.0:8000"
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server_1 = "0.0.0.0:8001"
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add_report_share_batch_size = 100
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query_flp_batch_size = 100000
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zipf_unique_buckets = 1000
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zipf_exponent = 1.03

‎artifact/configs/figure-3/Mastic-m=10,n=256.toml‎

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mode.weighted_heavy_hitters.threshold = 0.01
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data_bits = 256
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hist_buckets = 9
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server_0 = "0.0.0.0:8000"
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server_1 = "0.0.0.0:8001"
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add_report_share_batch_size = 100
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query_flp_batch_size = 100000
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zipf_unique_buckets = 1000
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zipf_exponent = 1.03

‎artifact/configs/figure-3/Mastic-m=10,n=64.toml‎

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mode.weighted_heavy_hitters.threshold = 0.01
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data_bits = 64
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hist_buckets = 9
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server_0 = "0.0.0.0:8000"
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server_1 = "0.0.0.0:8001"
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add_report_share_batch_size = 100
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query_flp_batch_size = 100000
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zipf_unique_buckets = 1000
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zipf_exponent = 1.03

‎artifact/configs/figure-3/Mastic-m=30,n=128.toml‎

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mode.weighted_heavy_hitters.threshold = 0.01
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data_bits = 128
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hist_buckets = 29
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server_0 = "0.0.0.0:8000"
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server_1 = "0.0.0.0:8001"
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add_report_share_batch_size = 100
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query_flp_batch_size = 100000
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zipf_unique_buckets = 1000
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zipf_exponent = 1.03

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