SHARP is a human-AI collaboration pipeline for reproducing scientific analyses, demonstrated by recreating a jet classification task from a particle physics paper.
Canonical reference
Giordano et al., HEPScore: A new CPU benchmark for the WLCG , EPJ Web of Conf
Canonical reference. 75% of citing Pith papers cite this work as background.
5
Pith papers citing it
Background
75% of classified citations
citation-role summary
background 7
method 1
citation-polarity summary
years
2026 5verdicts
UNVERDICTED 5representative citing papers
FPGA implementations for full matrix-element workflow on e+e- to mu+mu- and color-algebra kernels on gg to ttbar+X achieve speedups and energy gains over CPU/GPU while preserving numerical accuracy.
A cascade pipeline on 400 AIE tiles evaluates gg→ttg leading-order matrix elements at 1 million per second with parts-per-million accuracy to MadGraph, delivering 34× CPU speedup and 7.7× better energy efficiency at 54.8 W.
A review of initiatives to make LHC Monte Carlo event generations available as open data to minimize redundant simulations and resource use.
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.
citing papers explorer
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A Scientific Human-Agent Reproduction Pipeline
SHARP is a human-AI collaboration pipeline for reproducing scientific analyses, demonstrated by recreating a jet classification task from a particle physics paper.
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FPGA Acceleration of Matrix-Element Calculations for Monte Carlo Event Generation
FPGA implementations for full matrix-element workflow on e+e- to mu+mu- and color-algebra kernels on gg to ttbar+X achieve speedups and energy gains over CPU/GPU while preserving numerical accuracy.
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Cascade Pipeline for Leading-Order Matrix Element Evaluation on AMD Versal AI Engine Arrays
A cascade pipeline on 400 AIE tiles evaluates gg→ttg leading-order matrix elements at 1 million per second with parts-per-million accuracy to MadGraph, delivering 34× CPU speedup and 7.7× better energy efficiency at 54.8 W.
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Open LHC Monte Carlo Event Generation
A review of initiatives to make LHC Monte Carlo event generations available as open data to minimize redundant simulations and resource use.
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The Monte Carlo Ecosystem in High-Energy Physics: A Primer
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.