Statewide Users Group Conference Minutes - April 6, 2017

Wednesday, April 5th

Thursday, April 6th 

Keynote Address: NVIDIA, Jonathan Bentz, Solutions Architect

Jonathan Bentz is a Senior Solutions Architect with NVIDIA, focusing on Higher Education and Research customers. In this role he works as a technical resource to support and enable the use of GPU computing.  Jonathan has a background in computational chemistry and software engineering and frequently conducts hands-on programming sessions for CUDA, OpenACC and GPU-accelerated deep learning.  With OSC’s recent GPU adoption, Jonathan will discuss current advances in GPU hardware and software which directly impact accelerated applications in HPC and have been a catalyst in the rapid advancement of deep learning technologies. 

Flash Talk and Poster Session Information

Please see our detailed agenda. 

Flash Talk Session Winner:

Sandip Mazumder, Associate Professor at The Ohio State University
"Phonon Boltzmann Transport Equation Based Modeling of Time Domain Thermo-Reflectance Experiments"
Time Domain Thermo-Reflectance (TDTR) experiments have been recently identified as a viable pathway toward extracting the phonon mean free path spectrum of semiconductor materials. However, this requires an intervening model. It is now widely believed that the frequency and polarization dependent phonon Boltzmann Transport Equation (BTE) is the most suitable model for this purpose. In this study, TDTR experiments are simulated using large-scale parallel computations of the phonon BTE in a two-dimensional computational domain. Silicon is used as the candidate substrate material. Simulations are performed for multiple pulse and modulation cycles of the TDTR pump laser. This requires resolution of a picosecond laser pulse within a computational timeframe that spans several hundreds of nanoseconds. The metallic transducer layer on top of the substrate is modeled using the Fourier law and coupled to the BTE within the silicon substrate. Studies are conducted for four different laser spot sizes and two different modulation frequencies. The BTE results are fitted to the Fourier law, and effective thermal conductivities are extracted. It is demonstrated that the time delay of the probe laser could have a significant effect on the fitted (extracted) thermal conductivity value. The modulation frequency is found to have negligible effect on the thermal conductivity, while the spot size variation exhibits significant impact. Both trends are found to be in agreement with experimental observations. The thermal conductivity accumulation function is also computed, and the effect of the mean free path spectrum on the thermal conductivity suppression is delineated.

Flash Talk Session Runner-Up:

Gregory Wheeler, Graduate Student at The Ohio State University
"Identification of Carnivory in Plants via Genomic Functional Annotation"
The purpose of this project was to identify evidence of carnivory in plants using functional gene annotation. Illumina sequence reads of a carnivorous pitcher plant Sarracenia alata were processed and assembled with Velvet, with contigs assigned function via Blast2GO. These data, along with annotations from other carnivorous and non-carnivorous plants, were scored by representation of functions previously identified as related to carnivory. Carnivorous plants were found to have an overabundance of certain enzymes relative to most non-carnivorous plants; however, the non-carnivorous close relatives of these plants also showed overrepresentation, indicating that phylogenetic effects may play a role as well.

Poster Session Winner:

Ryan Lundgreen, Postodctorate at The Ohio State University
"Heat Transfer and Deposition in Gas Turbine Engines"
This poster highlighted some of the major research efforts of the Turbine Aerothermodynamics Laboratory.  These research efforts include novel cooling technologies such as reverse cooling holes, sweeping jet film cooling and impingement heat transfer, and particle deposition modeling with mesh morphing.

Poster Session Runner-Up:

Melanie Aprahamian, Graduate Student at The Ohio State University
"Incorporation of Mass Spectrometry Covalent Labeling Data into Rosetta Protein Structure Prediction"
The Rosetta Commons software suite is used for modeling and prediction of protein structures. Prediction of protein structure is done in an ab initio fashion and is based upon the primary amino acid sequence of a protein where a score is given to each predicted structure. Currently, Rosetta is only accurate for proteins with fewer than 150 amino acids. In order to improve the accuracy of protein structures predicted using Rosetta, a new score term is being incorporated that takes into account specific amino acid solvent exposure based upon covalent labeling mass spectrometry data.

SUG Press Release

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