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— | myocyte [2018/10/03 17:53] (current) – created - external edit 127.0.0.1 | ||
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+ | ====== Myocyte ====== | ||
+ | Myocyte application models cardiac myocyte (heart muscle cell) and simulates its behavior according to the work by Saucerman and Bers [1]. The model integrates cardiac myocyte electrical activity with the calcineurin pathway, which is a key aspect of the development of heart failure. The model spans large number of temporal scales to reflect how changes in heart rate as observed during exercise or stress contribute to calcineurin pathway activation, which ultimately leads to the expression of numerous genes that remodel the heart’s structure. It can be used to identify potential therapeutic targets that may be useful for the treatment of heart failure. Biochemical reactions, ion transport and electrical activity in the cell are modeled with 91 ordinary differential equations (ODEs) that are determined by more than 200 experimentally validated parameters. The model is simulated by solving this group of ODEs for a specified time interval. The process of ODE solving is based on the causal relationship between values of ODEs at different time steps, thus it is mostly sequential. At every dynamically determined time step, the solver evaluates the model consisting of a set of 91 ODEs and 480 supporting equations to determine behavior of the system at that particular time instance. If evaluation results are not within the expected tolerance at a given time step (usually as a result of incorrect determination of the time step), another calculation attempt is made at a modified (usually reduced) time step. Since the ODEs are stiff (exhibit fast rate of change within short time intervals), they need to be simulated at small time scales with an adaptive step size solver. | ||
+ | The original code used MATLAB ode45 ODE solver. In the process of accelerating this code, we arrived with the intermediate versions that used single-threaded Sundials CVODE solver which evaluated parallelized model (either OpenMP or CUDA) at each time step. In order to convert entire solver to OpenMP and CUDA codes (to remove some of the operational overheads such as thread/ | ||
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+ | ==== Papers ==== | ||
+ | [1] L. G. Szafaryn, K. Skadron, and J. J. Saucerman. " | ||
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+ | ==== Presentation Slides ==== | ||
+ | [2] L. G. Szafaryn, K. Skadron, and J. J. Saucerman. " | ||
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+ | Retrieved from " |