# High Performance Simulation Libraries for Systems Biology

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2020 · $433,392

## Abstract

Abstract
Quantitative analysis and simulation of cellular processes is becoming an important and indispensible tool for
predictive biomedical research. Not only that, but models are becoming larger, more sophisticated and
encompassing areas such as multicellular and multiscale modeling of tissues and whole organs. Performance
can be improved by using compute clusters or the cloud, however interactive computing is severely restricted
using this kind of infrastructure. Moreover supercomputing or cloud access is not available to everyone. In this
proposal we wish to focus on developing high performance simulators, notably libRoadRunner and specific
hardware based on analog computing. libRoadRunner is unique in that it is the only cellular simulator that
compiles standard SBML using LLVM. LLVM is a backend machine code generation technology that is starting
to be widely used by performance conscious software developers. Using this technology we have achieved
significant, in some cases orders of magnitude speed ups in simulation times compared to existing simulators.
Our letters of support highlight some of the major improvements that have been realized by this new
technology. We have shown that the performance of libRoadRunner is on par (within 95%) with natively
compiled solutions. In other words we have reached the limit to computing on ordinary desktop computers.
In this proposal we will continue to improve libRoadRunner and implement a completely novel way to carry out
cellular simulations which will lead to additional orders of magnitude improvements in simulation performance.
Our proposal is to work with Rahul Sarpeshkar at Dartmouth who has pioneered hardware based simulation
technologies called cytomorphic computing. As part of this proposal, the Dartmouth group will develop a new
generation of ultra-high-speed hardware-based biochemical simulators. We will develop SBML and MATLAB
translators that can translate a model directly into programmable high-performance cytomorphic silicon chips.
In addition to this highly innovative approach we will also exploit this hardware to implement novel approaches
to interactive real-time modeling of cellular processes that includes the complete control of time and temporal
incursion. A small part of the proposed effort will include general maintenance of our existing infrastructure as
well as organizing an annual workshop on modeling and training.

## Key facts

- **NIH application ID:** 10020192
- **Project number:** 5R01GM123032-04
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** HERBERT M. SAURO
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $433,392
- **Award type:** 5
- **Project period:** 2017-09-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10020192

## Citation

> US National Institutes of Health, RePORTER application 10020192, High Performance Simulation Libraries for Systems Biology (5R01GM123032-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10020192. Licensed CC0.

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