@inbook {Simula.simula.76,
	title = {A Computational Framework for Patient-Specific Multi-Scale Cardiac Modeling},
	booktitle = {Patient-Specific Modeling of the Cardiovascular System; Technology-Driven Personalized Medicine},
	year = {2010},
	pages = {202-223},
	publisher = {Springer},
	organization = {Springer},
	chapter = {12},
	abstract = {Systems biology has introduced new paradigms in science by switching from a reductionist point of view to a more integrative approach toward the study of \-systems. As researchers over the past years have produced an extraordinary wealth of knowledge on human physiology, we now aim at integrating this knowledge to decipher the intimate relationships between the different components and scales that form the delicate balance in physiological systems. Our aim is to study the heart.},
	isbn = {978-1-4419-6690-2},
	author = {Aguado-Sierra, Jazmin and Fred V. {Lionetti} and Hunt, Darlene and Christopher T. {Villongco} and Gonzales, Matt and Stuart G. {Campbell} and Andrew D. {McCulloch}}
}
@article {Simula.simula.68,
	title = {Coupling of Adjacent Tropomyosins Enhances Cross-Bridge-Mediated Cooperative Activation in a Markov Model of the Cardiac Thin Filament},
	journal = {Biophysical Journal},
	volume = {98},
	number = {10},
	year = {2010},
	month = {May},
	pages = {2254-2264},
	abstract = {We developed a Markov model of cardiac thin filament activation that accounts for interactions among nearest-neighbor regulatory units (RUs) in a spatially explicit manner. Interactions were assumed to arise from structural coupling of adjacent tropomyosins (Tms), such that Tm shifting within each RU was influenced by the Tm status of its neighbors. Simulations using the model demonstrate that this coupling is sufficient to produce observed cooperativity in both steady-state and dynamic force-Ca(2+) relationships. The model was further validated by comparison with reported responses under various conditions including inhibition of myosin binding and the addition of strong-binding, non-force-producing myosin fragments. The model also reproduced the effects of 2.5 mM added P(i) on Ca(2+)-activated force and the rate of force redevelopment measured in skinned rat myocardial preparations. Model analysis suggests that Tm-Tm coupling potentiates the activating effects of strongly-bound cross-bridges and contributes to force-Ca(2+) dynamics of intact cardiac muscle. The model further predicts that activation at low Ca(2+) concentrations is cooperatively inhibited by nearest neighbors, requiring Ca(2+) binding to >25\% of RUs to produce appreciable levels of force. Without excluding other putative cooperative mechanisms, these findings suggest that structural coupling of adjacent Tm molecules contributes to several properties of cardiac myofilament activation.},
	doi = {10.1016/j.bpj.2010.02.010},
	author = {S. G. {Campbell} and Fred V. {Lionetti} and K. S. {Campbell} and Andrew D. {McCulloch}}
}
@inproceedings {Simula.acdc.74,
	title = {GPU Accelerated Cardiac Electrophysiology},
	journal = {Proceedings of the International Conference on Applied Parallel Computing},
	year = {2010},
	type = {1},
	abstract = {Computational models of cardiac electrophysiology require the integration of large and complex systems of ordinary differential equations. This poses special challenges on a GPU architecture owing to the large numbers of state variables required to describe the detailed biophysics of the ion channels in the cardiac muscle cells. We describe a system for generating efficient CUDA C from high level mathematical expressions and their solution within large three-dimensional, anatomically realistic multi-scale models of whole heart electrical activation. Significant performance improvements over CPU clusters are presented.},
	author = {Fred V. {Lionetti} and Andrew D. {McCulloch} and Baden, Scott}
}
@inproceedings {Simula.acdc.60,
	title = {Source-to-Source Optimization of CUDA C for GPU Accelerated Cardiac Cell Modeling},
	journal = {Proceedings of Euro-Par 2010},
	year = {2010},
	type = {Conference},
	abstract = {Large and complex systems of ordinary differential equations (ODEs) arise in diverse areas of science and engineering, and pose special challenges on a streaming processor owing to the large amount of state they manipulate. We describe a set of domain-specific source transformations on CUDA C that improved performance by \&times;6.7 on a system of ODEs arising in cardiac electrophysiology running on the nVidia GTX-295, without requiring expert knowledge of the GPU. Our transformations should apply to a wide range of reaction-diffusion systems.},
	author = {Fred V. {Lionetti} and Andrew D. {McCulloch} and Baden, Scott}
}
@inproceedings {Simula.sc.1134,
	title = {GPU Accelerated Electrophysiology Simulations},
	journal = {Proceedings of the 2009 ACM/IEEE Conference on supercomputing (SC 2009)},
	year = {2009},
	type = {Conference},
	abstract = {Numerical simulations of cellular membranes are useful for basic science and increasingly for clinical diagnostic and therapeutic applications. A common bottleneck arises from solving large stiff systems of ODEs at thousands of integration points in a three-dimensional whole organ model. When performing a modern electrophysiogy simulation on a single conventional core, the ODE bottleneck consumed 99.4\% of the running time. Using an nVidia GTX 295 GPU, we reduced the time to 2\%, eliminating the bottleneck. This speedup comes at a small loss in accuracy, due to the use of single precision. By comparison, a multithreaded implementation running on the CPU yielded a speedup of 3.3 only. We are currently investigating the new bottleneck-a PDE solver. We plan to present results at the conference demonstrating the benefits of hybrid execution, whereby the PDE solver runs as multiple threads on the front end CPU. This choice balances development costs against performance.},
	author = {Fred V. {Lionetti} and Andrew D. {McCulloch} and Baden, Scott}
}
@misc {Simula.sc.1136,
	title = {GPU Accelerated Electrophysiology Simulations.},
	howpublished = {Talk, Poster at GPU Technology conference, San Jose, California},
	year = {2009},
	month = {October},
	author = {Fred V. {Lionetti} and Andrew D. {McCulloch} and Baden, Scott}
}
@misc {Simula.sc.1138,
	title = {GPU Accelerated Electrophysiology Simulations},
	howpublished = {Talk, poster at the 2009 ACM/IEEE Conference on Supercomputing (SC 2009)},
	year = {2009},
	month = {November},
	author = {Fred V. {Lionetti} and Andrew D. {McCulloch} and Baden, Scott}
}
@inproceedings {Simula.sc.1132,
	title = {GPU Accelerated Solvers for ODEs Describing Cardiac Membrane Equations},
	journal = {Proceeding of the GPU technology Conference},
	year = {2009},
	type = {Conference},
	abstract = {Mathematical models describing cellular membranes form the basis of whole tissue models to describe the electrical activity of entire organs, such as the heart. Numerical simulations based on these models are useful for both basic science and increasingly for clinical diagnostic and therapeutic applications such as targeting ablation therapy for atrial arrhythmias, defibrillator design and cardiac resynchronization therapy. A common bottleneck in such simulations arises from solving large stiff systems of ordinary differential equations (ODEs) thousands of times for numerous integration points (representing cells) throughout a three-dimensional tissue or organ model. For some electrophysiology simulations, over 80\% of the time is spent solving these systems of ODEs. While a cluster provides the required interactive response time to solve the ODEs, a desktop sized platform would enhance usability of the software in a laboratory setting. The audience will benefit by learning how a real-world, complex, HPC application can directly benefit by the use of CUDA technology. Participants will learn which optimization techniques yielded the best performance results on an actual application. We will also explore the benefits and limits of the use of single precision in certain scientific applications.},
	author = {Fred V. {Lionetti} and Andrew D. {McCulloch} and Baden, Scott}
}
