Are we there yet? The road to Artificial General Intelligence

Rajat Monga, CEO Inference.io, ex-Head TensorFlow

 

Harnessing High Performance Computing to Advance Clinical Neuroscience at OSU

W. Kyle Simmons, Biomedical Imaging Center, Oklahoma State University

 

Teaming up for CI and Achieving High Throughput in the Great Plains

Dan Andresen, Department of Computer Science, Kansas State University

 Universities across the Great Plains region have worked together for decades to support one another in gaining access to and leveraging research cyberinfrastructure (CI). In the past few years, several universities have come together to develop an NSF-funded Cyber Team, engaging with under-resourced universities to improve aspects of data movement and scientific workflows and further the advancement of a professional development mentorship framework. This rapidly led to an “expansion-pack”, of a CC* Compute project led by Kansas State University that built upon the community aspects of the well-connected institutions to simplify the process of leveraging the Open Science Grid, providing compute resources to smaller institutions, and most importantly, helping onboard existing high-performance computing resources to the Open Science Grid.

 

Accelerated Enzyme Reaction Free Energy Simulations

Yihan Shao, Department of Chemistry and Biochemistry, University of Oklahoma

In this talk, we present two approaches to accelerate free energy simulations of enzyme reactions: multiple timestep integration and machine-learning potentials.  The power of these approaches are demonstrated with CRISPR-Cas9 HNH-domain catalyzed double-strand DNA cleavage. 

 

Big Data in Genomic Research for Big Questions with Examples from COVID-19 and Other Zoonoses

Dave Ussery, Department of Biomedical Informatics, University of Arkansas for Medical Services

BioMedical Data is becoming Big Data, with about 100 Zettabytes (10^23 bytes) of BioMedical data produced in 2022. This massive amount of data requires expertise in high throughput computational strategies, including rethinking how to make methods more scalable and how to automate data curation. The Covid-19 pandemic is the first pandemic where massive amounts of viral genomes have been sequenced and analyzed in near real-time, as the outbreak was unfolding.  Currently there are more than 16 million SARS-CoV-2 genome sequences publicly available for analysis.  Similarly, the rapidly plummeting costs of genomic sequencing has resulted in millions of bacterial genome sequences deposited in public databases.

 

Reinventing Compute for Next Gen Infrastructure

Sumit Gupta, Infra Lead, Google

Scalable warehouse computing using commodity clusters has served us well for over the last 25 years. We are now at an inflection point, where we are simultaneously facing the headwinds of slowing semiconductor and memory technologies, and a dramatic increase in compute needs driven by machine learning. In this talk, we will discuss what we are doing at Google to address these growth opportunities by rearchitecting the next generation of infrastructure.

 

Methods for Onboarding New HPC Users: Encouraging the HPC Experience in Curriculum Design at Wichita State University

Terrance Figy , Department of Mathematics, Statistics, and Physics, Wichita State University

This talk will discuss the methods for onboarding new HPC users on an academic research computing cluster at Wichita State University. As the first computing cluster available to all faculty and students since 2012, it is crucial to provide efficient and effective onboarding processes to ensure users can utilize the resources to their fullest potential. Additionally, the integration of HPC into course designs is encouraged to prepare students for research, and to develop valuable skills that will benefit them in their future careers. By implementing these practices, Wichita State University is promoting the growth of research computing and empowering the next generation of researchers.

 

Noncoding and Nonsensical Genome Elements:  How the Non-protein Coding Regions of the Genome Regulate Expression and Take Power from the One Percent

Darren Hagen , Department of Animal and Food Sciences, Oklahoma State University

Many studies of our genome focus on genes that make proteins but constitute about one percent of our genome. What about the other 99% of the genome that is considered noncoding (and once called junk DNA)? Scientists have figured out that as much as 80% of the genome has some biochemical function but we remain puzzled by the role of much of genome. To further complicate matters of the genome, our DNA itself has modifications and 3D structure that control the behavior of our genes. Our lab is utilizing a number of species from bees to cattle to interspecies hybrids to identify genome features and decipher the role of the unknown 99% of our genome.

 

The Future of HPC

Wynell Jenkins, Dell Technologies