Projects: Faculty Collaboration
Computational Fluid Dynamics
Performed parallelization opportunities preliminary research for Dr. Aleksander Kartusinski for a single and multi-phase fluid simulation code. Computational fluid dynamics has important applications in a variety of critical areas such as fluid simulation for biomedical applications and oil exploration.
Computational Chemistry Parallel Software Testing
Collaborating with Dr. Walter Ermler (UTSA Deapertment of Chemistry) to provide access to the CBI allocation at TACC for testing parallel computational chemistry code. The CBI compute time allocation allows the researchers to test out their codes on TACC systems such as Ranger and Lonestar. Over 2 million SUs have been allocated for this project on Lonestar.
Fractional Integration Toolbox
Collaborating with Dr. Fidel Santamaria and Dr. Toma Marinov on a high performance C++ software toolbox for MATLAB for high speed fractional integration and fractional diffusion simulation applications. The FIT toolbox was developed in C++ with OpenMP parallelism to make use of as many cores as are available on a system. It can be compiled for both the Linux and Windows operating system environments. Fractional integration has a wide array of applications in areas such as neural simulation.
Website: FIT Download
Publication: Marinov, T. M., Ramirez, N., and Santamaria, F., 2013, "Fractional Integration Toolbox," Fractional Calc. Appl. Anal., 16, pp. 670–681
- Modeling the effects of anomalous diffusion on synaptic plasticity
- Estimation of the Order and Parameters of a Fractional Order Model From a Noisy Step Response Data." Journal of Dynamic Systems, Measurement, and Control 136 (2014): 031020-1
- Toma M. Marinov, Fidel Santamaria, Chapter Eight - Computational Modeling of Diffusion in the Cerebellum, In: Kim T. Blackwell, Editor(s), Progress in Molecular Biology and Translational Science, Academic Press, 2014, Volume 123, Pages 169-189
- Teka W, Marinov TM, Santamaria F (2014) Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model. PLoS Comput Biol 10(3): e1003526. doi:10.1371/journal.pcbi.1003526
High Throughput Biochemical Systems Simulation Enablement
Performed preliminary research for Dr. Clyde Phelix (UTSA Department of Biology) on providing an infrastructure to enable the streamlining and automating of large scale SimBiology based simulations on the Matlab Distributed Server environment and the Copasi simulation environment.
Large Scale Distributed Neural Diffusion Simulation Enablement
Collaborating with Dr. Fidel Santamaria (UTSA Department of Biology) and Dr. Toma Marinov to enable large scale distributed neural diffusion simulation workflows at the CBI as well as at the Texas Advanced Computing Center. Utilizing the ClusterCheckpointer™ system developed to allow automating the management of the checkpointing of long running jobs.
Website: Cluster Checkpointer
Collaborating with Dr. Michelle Zhang (UTSA Department of Electrical & Computer Engineering) on the creation of a software infrastructure platform for high performance proteomics in C++. High quality peptide identification is critical to all subsequent proteomics data analysis stages, such as protein identification as well as application areas such as biomarker and drug discovery.
Nanotechnology and Human Health Core Collaboration
Collaborating with Dr. Arturo Ponce-Pedraza (UTSA Department of Physics), Dr. Cesar Santiago Cortes (Research Fellow), Hector Barron-Escobar (Ph.D. Candidate), Dr. Pedro L. Galindo (Universidad de Cádiz Department of Computer Science and Engineering) to enable custom distributed software using the MATLAB Distributed Computing Server Cluster.
Proteomics Pipeline Automation
Collaborating with Dr. William Haskins (UTSA Department of Biology) and proteomics lab team on providing custom software to automate the proteomics workflow. Starting with acquisition data management to integrating with tools such as Mascot Daemon, Mascot Server, R, and the Ingenuity Systems Pathway Analysis web service. Automation in the proteomics workflow is critical to enable the efficient utilization of next generation proteomics hardware.
R Software Parallelization Enablement on the Cheetah Cluster
Collaborating with Dr. Long Liu (UTSA Department of Economics) to enable parallelization of software in the R programming language within the Cheetah HPC Cluster. Computational Econometrics: Nonparametric estimation techniques in the statistical software environment R with parallel enablement.