English

RAPTOR: Ravenous Throughput Computing

Distributed, Parallel, and Cluster Computing 2022-09-02 v1

Abstract

We describe the design, implementation and performance of the RADICAL-Pilot task overlay (RAPTOR). RAPTOR enables the execution of heterogeneous tasks -- i.e., functions and executables with arbitrary duration -- on HPC platforms, providing high throughput and high resource utilization. RAPTOR supports the high throughput virtual screening requirements of DOE's National Virtual Biotechnology Laboratory effort to find therapeutic solutions for COVID-19. RAPTOR has been used on >8000>8000 compute nodes to sustain 144M/hour docking hits, and to screen \sim1011^{11} ligands. To the best of our knowledge, both the throughput rate and aggregated number of executed tasks are a factor of two greater than previously reported in literature. RAPTOR represents important progress towards improvement of computational drug discovery, in terms of size of libraries screened, and for the possibility of generating training data fast enough to serve the last generation of docking surrogate models.

Keywords

Cite

@article{arxiv.2209.00114,
  title  = {RAPTOR: Ravenous Throughput Computing},
  author = {Andre Merzky and Matteo Turilli and Shantenu Jha},
  journal= {arXiv preprint arXiv:2209.00114},
  year   = {2022}
}

Comments

10 pages, 9 figures. 22nd International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022)

R2 v1 2026-06-28T00:31:24.550Z