- author = "Matthew Andres Moreno and Santiago {Rodriguez Papa} and Charles Ofria and Luis Zaman and Emily Dolson",
- title = "Trust, but Verify: Rigorously Profiling Best-Effort High-Performance Computing for Digital Evolution",
- booktitle = "Genetic Programming Theory and Practice XXIII",
- year = "2025",
- editor = "Wolfgang Banzhaf and Bogdan Burlacu and Stephen Kelly and Fabricio {Olivetti de Franca}",
- address = "University of Michigan, USA",
- month = jun # " 4-6",
- keywords = "genetic algorithms, genetic programming, HPC",
-
URL = "
https://arxiv.org/abs/2608.23955",
- abstract = "Developments in high-performance computing (HPC) technology continue to drastically increase quantities of available processing power. In the context of digital evolution, this explosive growth offers opportunities to advance both hypothesis-driven explorations of multi-scale biological phenomena and application-driven evolutionary optimization targeting hard problem domains. A particular opportunity arises from emerging next-generation AI/ML hardware accelerator platforms, such as the 880000-processor Cerebras Wafer-Scale Engine (WSE). Such hardware, however, constrains on-device data storage and movement; a challenge compounded by vulnerability to failures arising over numerous device components. Best-effort relaxations that depart from a traditional deterministic computing paradigm can help accommodate such constraints, but complicate reproducibility and risk introducing artifactual biases. We explore these concerns, developing a framework to measure runtime behavior of best-effort...",
-
notes = "lightning talk. Also known as
\cite{moreno2026trustverifyrigorouslyprofiling}
To be published after the workshop",
