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add grumpkin msm (#965)
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Co-authored-by: Hanting Zhang <winston@lurk-lab.com>
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winston-h-zhang and Hanting Zhang authored Dec 22, 2023
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Expand Up @@ -134,6 +134,7 @@ once_cell = "1.18.0"
pairing = { version = "0.23" }
pasta_curves = { git = "https://github.com/lurk-lab/pasta_curves", branch = "dev" }
pasta-msm = { git = "https://github.com/lurk-lab/pasta-msm", branch = "dev" }
grumpkin-msm = { git = "https://github.com/lurk-lab/grumpkin-msm", branch = "dev", features = ["dont-implement-sort"] }
proptest = "1.2.0"
proptest-derive = "0.3.0"
rand = "0.8"
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Benchmarks

Table of Contents

Overview

This benchmark report shows the Fibonacci GPU benchmark.
NVIDIA L4
Intel(R) Xeon(R) CPU @ 2.20GHz
125.78 GB RAM
Workflow run: https://github.com/lurk-lab/lurk-rs/actions/runs/7301245761

Benchmark Results

LEM Fibonacci Prove - rc = 100

fib-ref=510d7042990844760d97d65c7e6c7ab75f934630 fib-ref=0a4960a846be8d5a6fbaa762eb5353a13fae1374
num-100 2.36 s (✅ 1.00x) 2.36 s (✅ 1.00x slower)
num-200 4.62 s (✅ 1.00x) 4.63 s (✅ 1.00x slower)

LEM Fibonacci Prove - rc = 600

fib-ref=510d7042990844760d97d65c7e6c7ab75f934630 fib-ref=0a4960a846be8d5a6fbaa762eb5353a13fae1374
num-100 1.98 s (✅ 1.00x) 1.99 s (✅ 1.00x slower)
num-200 4.49 s (✅ 1.00x) 4.50 s (✅ 1.00x slower)

Made with criterion-table

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