GPU Callable Libraries; Vector Video Instructions for Smith-Waterman Algorithms
Details
Come for Table discussions, Member Self-Intro, What's New, Application Showcase, and Advanced Application Development Techniques! Exchange ideas, meet experts, share code... all HPC & GPU, all practical, all cutting-edge.
Agenda:
General Discussions:
6:15-6:35pm What’s new
6:35-6:50pm Member self-intros: 30 seconds for each member
Main Program:
6:50-7:15pm GPU Callable Libraries in CUDA 5.0 (Mike Murphy, NVIDIA)
7:15-8:00pm Vector Video Instructions to Accelerate the Smith-Waterman Algorithm (Erich Elsen and Vishal Vaidyanathan, Royal Caliber)
Abstract: The Smith-Waterman (SW) Algorithm is a key algorithm in bioinformatics. Briefly, it allows the comparison and alignment of sequences of DNA and proteins, which is the essence of genomic research today and will form the basis for medical science tomorrow. With rapid advances in gene sequencing technology, there is acute pressure on the computational front to keep pace with the growing size of genomic databases. In this talk we discuss how GPUs can be used in a real-world application of the SW algorithm. In particular we outline some exciting performance enhancements from new instructions in the Kepler architecture that make the GPU extremely attractive as a hardware solution for SW calculations.
Bio for Mike Murphy, NVIDIA: Mike is the lead compiler engineer for the separate compilation support in CUDA. He was one of the initial designers of the CUDA compiler, and was also responsible for the nvopencc component and the fatbinary implementation.
Bio for Erich Elsen, Royal Caliber: Erich received his Ph.D. in Mechanical Engineering from Stanford in 2009. His thesis developed novel parallel algorithms for running fluid dynamics and molecular dynamics computations on two types of then newly released parallel processors: Sony's Cell and GPUs. After graduating he joined an EDA startup where he developed GPU-accelerated computational lithography solutions. He was invited back to Stanford as a consulting associate professor to teach a course on parallel algorithms, OpenMP, MPI and CUDA in the Spring of 2012.
Bio for Vishal Vaidyanathan, Royal Caliber: Vishal graduated from Stanford in 2007 with a Ph.D. in Computational Chemistry and an M.S. in Financial Mathematics. He developed the first Folding@Home client that used GPUs to accelerate biomolecular simulations by 50 times over what was previously possible. From 2007-2009 Vishal worked at Goldman Sachs developing the first fully automated high frequency trading solution for the US Treasury desk in New York. Subsequently as co-founder of a startup in Silicon Valley, he developed low-latency trading systems and HFT strategies for futures contracts. Vishal joined Royal Caliber as a partner in 2012.
Location:
Open Space;
Carnegie Mellon Silicon Valley;
NASA Research Park Bldg 23;
Mountain View, CA 94043;
Directions (http://www.cmu.edu/silicon-valley/about-us/directions.html) to Carnegie Mellon Silicon Valley;
Google Map (http://maps.google.com/maps/ms?gl=us&hl=en&ie=UTF8&msa=0&ll=37.410941,-122.063169&spn=0.019191,0.048923&t=h&z=15&msid=215438781255871976989.00049cacf6f0e5596e5cc) showing parking, check point, and building entrance;
NOTE: You will need a government issued ID (e.g. Driver's License) to enter NASA Research Park
http://photos1.meetupstatic.com/photos/event/4/b/6/e/event_21799310.jpeg