Two Nominees, One Winner for Best Paper at Field Programmable Logic Conference

San Diego, September 5, 2014 — At the 24th International Conference on Field Programmable Logic (FPL), two papers from the Computer Science and Engineering (CSE) group of professor Ryan Kastner, an academic participant in the Qualcomm Institute, were nominated for the top award, and one of the CSE contributions won for Best Paper. The honor went to the authors of a paper on "Hardware Accelerated Novel Optical De Novo Assembly for Large-Scale Genomes." In addition to Kastner and first author Pingfan Meng, whose research focuses on high-throughput, real-time computing systems using heterogeneous hardware accelerators, other co-authors were CSE Ph.D. student Matthew Jacobsen, former visiting scholar Motoki Kimura, and collaborators from BioNano Genomics (Vladimir Dergachev, Thomas Anantharaman and Michael Requa).

The winning paper looked at the potential use of a novel optical label-based technology to make reliable, large-scale de novo assembly of human genomes possible. However, the new technology requires a more computationally intensive alignment algorithm if it is going to be used reliably for reconstructing the large-scale structures of human genomes. The run-time of reconstructing a human genome is approximately 10,000 hours on a sequential CPU, so the authors looked at three rival approaches to acceleration: multi-core CPU; a graphics processing unit (GPU); and field-programmable gate array (FPGA), which is an integrated circuit that can be customized to a specific use case. The new approaches had the desired effect of speeding up the reconstruction of human genomes. The multi-core CPU design was 8.4 times faster; the speedup with GPU was 13.6 times; and by far the greatest acceleration was produced using the FPGA approach, which was 115 times faster that today's sequential CPU approach.

FPGA acceleration was also a topic in the second paper from the Kastner group to receive a best-paper nomination at FPL. The paper explored "Improving FPGA Accelerated Tracking with Multiple Online Trained Classifiers." It was co-authored by Ph.D. student Matt Jacobsen, former Kastner group undergraduate Siddarth Sampangi (now a grad student at the University of Massachusetts-Amherst), and CSE professors Yoav Freund and Ryan Kastner. In their paper, Jacobsen and his co-authors proposed an FPGA accelerated design of an online boosting algorithm that used multiple classifiers to track and recover objects in real time -- even as their appearance might be changing (e.g., a car and its shadow will look different depending on the time of day and amount of sunlight). The algorithm used a novel method for training and comparing pose-specific classifiers along with adaptive tracking classifiers. The FPGA accelerated design was able to track at 60 frames per second while concurrently evaluating 11 classifiers. This represents a 30-times speed-up over a CPU-based software implementation. It also demonstrated state-of-the-art tracking accuracy on a standard set of videos. 

A third paper from the Kastner group was accepted to FPL 2014. Kastner and his Ph.D. students Dajung Lee (ECE) and Janarbek Matai (CSE) as well as Brad Weals of Toyon Research, reported on "High Throughput Channel Tracking for JTRS Wireless Channel Emulation." FPL is the first and largest conference covering the rapidly growing area of field-programmable logic, and FPL 2014 took place September 2-4 in Munich, Germany.

 

Related Links

Best Paper at FPL 2014 
Improving FPGA Accelerated Tracking with Multiple Online Trained Classifiers 
High Throughput Channel Tracking for JTRS Wireless Channel Emulation
FPL 2014 

Media Contacts

Doug Ramsey, (858) 822-5825, dramsey@ucsd.edu