HiCOPS: Computational framework for accelerating database peptide search workloads on supercomputing systems.
GiCOPS: The GPU-accelerated HiCOPS framework.
This is the maintained HiCOPS/GiCOPS repository.
Visit the HiCOPS/GiCOPS homepage here and the ACCESS SGCI Gateway here.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. All contributions are welcome including new features, documentation and bug fixes through standard GitHub pull request method.
Complete documentation on HiCOPS/GiCOPS installation and usage can be found here.
Tutorials and automated scripts for installing and setting up HiCOPS on a desktop or cluster computer can be found here.
Read more about HiCOPS and GiCOPS in the following research works. Please CITE our work if you use it. Thank you.
Muhammad Haseeb, and Fahad Saeed. "High performance computing framework for tera-scale database search of mass spectrometry data." Nature Computational Science, Volume no. 1, Issue no. 8 (2021): pp no. 550-561. https://doi.org/10.1038/s43588-021-00113-z (Read at SharedIt)
Muhammad Haseeb, and Fahad Saeed. "GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data." Nature Scientific Report, Volume no. 13, Issue no. 1 (2023). [https://www.nature.com/articles/s41598-023-43033-w)
Muhammad Haseeb, and Fahad Saeed. "GPU-Acceleration of the Distributed-Memory Database Peptide Search on Supercomputers." In 2022 ASMS Conference on Mass Spectrometry and Allied Topics, ASMS 2022.
Open an issue here. Please include any logs, screenshots and/or helpful observations. Also, do not forget to describe the dataset(s), database, steps performed etc. so that the issue can be reproduced.
HiCOPS and GiCOPS are under active development at the Parallel Computing and Data Science Laboratory at the Florida International University in Miami, Florida, USA.
Primary researchers: