HELPING NON-TRADITIONAL HPC USERS USING XSEDE RESOURCES EFFICIENTLY

Presenter(s): Shiquan Su (NICS)

Principal Investigator(s): Robert Sean Norman (University of South Carolina) Atsuko Tanaka (University of Wisconsin-Madison) Chao Fu (University of Wisconsin-Madison)

Presentation Slides

In the first project, the PI from University of South Carolina developed a bioinformatic pipeline for analyzing millions of DNA and cDNA sequences. The major computational workload comes from querying a large database by the BLAST tools. Shiquan will present how he helped the PI to reorganize the database file into multiple sub-databases (more than 50) and implemented the advanced host selection feature on Stampede batch system in the PI's job script. The improved workflow shortens the turn around time of the PI's job up to 80%.

In the second project, the researcher Dr. Atsuko Tanaka, from the University of Wisconsin-Madison, studies the lifetime utility: she simulates the clients' behavior and match the simulated outcomes and the observed data with respect to wage profile and asset accumulation over life cycle. This is an ongoing project. Dr. Atsuko Tanaka is actively developing the home-grown codes, which has the potential to be the starting point of a community code. Shiquan works closely with Dr. Tanaka to optimize her serial version of codes to efficiently utilize the powerful resources on Stampede. In this talk, Shiquan discusses the multiple parallelization treatments implemented in Dr. Tanaka's code. Shiquan provided a module to unfold the deep nested loop structure (more than 15 layers) in the main program with MPI. Also per the specific request from Dr. Tanaka, Shiquan applied the new feature in OpenMP 3.0+ to collapse multiple loop spaces in the core subroutine to explore the parallelism within the Stampede node.

Large-shared-memory supercomputing for game-theoretic analysis with fine-grained abstractions, and novel tree search algorithms.

Presenter(s): John Urbanic (PSC)

Principal Investigator(s): Tuomas Sandholdm (Carnegie Mellon)

Presentation Slides

John Urbanic (PSC) will discuss the optimization of the poker bot that recently competed in the first "Brain vs. AI" no-limit Texas Hold'em tournament, the first time that a poker program has competed against the top pros. John's work was in optimizing the Tuomas Sandholm group's algorithm for Blacklight, the world's largest shared memory platform, at PSC. John will discuss the project in general, the specifics optimizations that were used to make the poker bot competitive, and of course the results – which will shortly be televised.