Related Experiment Video
Updated: Oct 21, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
QSPcc reduces bottlenecks in computational model simulations
Danilo Tomasoni1, Alessio Paris1, Stefano Giampiccolo1
1Fondazione the Microsoft Research, University of Trento Centre for Computational and Systems Biology, Rovereto, Italy.
Abstract:
Mathematical models have grown in size and complexity becoming often computationally intractable. In sensitivity analysis and optimization phases, critical for tuning, validation and qualification, these models may be run thousands of times. Scientific programming languages popular for prototyping, such as MATLAB and R, can be a bottleneck in terms of performance. Here we show a compiler-based approach, designed to be universal at handling engineering and life sciences modeling styles, that automatically translates models into fast C code. At first QSPcc is demonstrated to be crucial in enabling the research on otherwise intractable Quantitative Systems Pharmacology models, such as in rare Lysosomal Storage Disorders. To demonstrate the full value in seamlessly accelerating, or enabling, the R&D efforts in natural sciences, we then benchmark QSPcc against 8 solutions on 24 real-world projects from different scientific fields. With speed-ups of 22000x peak, and 1605x arithmetic mean, our results show consistent superior performances.
Related Concept Videos
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Typical Model Studies
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models
Mechanistic Models: Overview of Compartment Models
Design Example: Creating a Hydraulic Model of a Dam Spillway
Compartment Models: Single-Compartment Model

