Redwood forest

Publications

Google Scholar Profile

Academic Publications

  • Bryan Catanzaro, Alexander Keller, Michael Garland, “A Decomposition for In-place Matrix Transposition&8221;. Principles and Practices of Parallel Programming 2014, pages 193-206, Orlando, Florida. pdf
  • Adam Coates, Brody Huval, Tao Wang, David Wu, Andrew Ng, Bryan Catanzaro, “Deep learning with COTS HPC systems”. International Conference on Machine Learning 2013, pages 1337-1345, Atlanta, Georgia. pdf
  • Michael Anderson, Bryan Catanzaro, Jike Chong, Ekaterina Gonina, Kurt Keutzer, Chao-Yue Lai, Mark Murphy, David Sheffield, Bor-Yiing Su, Narayanan Sundaram, “Considerations When Evaluating Microprocessor Platforms”. USENIX Workshop on Hot Topics in Parallelism, May 2011.
  • Bryan Catanzaro, Michael Garland, Kurt Keutzer, “Copperhead: Compiling an Embedded Data Parallel Language”. Principles and Practices of Parallel Programming (PPoPP) 2011, pages 47-56. pdf
  • Bryan Catanzaro, Armando Fox, Kurt Keutzer, David Patterson, Bor-Yiing Su, Marc Snir, Kunle Olukotun, Pat Hanrahan, Hassan Chafi, “Ubiquitous Parallel Computing from Berkeley, Illinois and Stanford”. IEEE Micro, Volume 30, Number 2, pages 41-55, March 2010. pdf
  • Bryan Catanzaro, Bor-Yiing Su, Narayanan Sundaram, Yunsup Lee, Mark Murphy, Kurt Keutzer, “Efficient, High-Quality Image Contour Detection”. International Conference on Computer Vision, pages 2381-2388, Kyoto, Japan, 2009. pdf
  • Andreas Klöckner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih. “PyCUDA: GPU Run-Time Code Generation for High-Performance Computing.” Computing Research Repository, 2009. pdf
  • Bryan Catanzaro, Shoaib Kamil, Yunsup Lee, Krste Asanovic, James Demmel, Kurt Keutzer, John Shalf, Kathy Yelick, Armando Fox. “SEJITS: Getting Productivity and Performance with Selective Embedded JIT Specialization”. Programming Models for Emerging Architectures, Raleigh, NC, 2009. pdf
  • Bryan Catanzaro, Narayanan Sundaram and Kurt Keutzer, “Fast Support Vector Machine Training and Classification on Graphics Processors”. International Conference on Machine Learning 2008, pages 104-111, Helsinki, Finland. pdf
  • Bryan Catanzaro, Kurt Keutzer and Bor-Yiing Su, “Parallelizing CAD: A Timely Research Agenda for EDA”, In proceedings of Design Automation Conference 2008, pages 12-17, ACM. pdf
  • Bryan Catanzaro, Narayanan Sundaram and Kurt Keutzer, “A Map Reduce Framework for Programming Graphics Processors”, Workshop on Software Tools for Multi-Core Systems 2008. pdf
  • Jike Chong, Nadathur Satish, Bryan Catanzaro, Kaushik Ravindran, Kurt Keutzer, “Efficient Parallelization of H.264 Decoding with Macro Block Level Scheduling”, IEEE International Conference on Multimedia & Expo 2007. pdf
  • Krste Asanovic, Rastislav Bodik, Bryan Catanzaro, Joseph Gebis, Parry Husbands, Kurt Keutzer, Dave Patterson, William Plishker, John Shalf, Sam Williams and Kathy Yelick, “The Landscape of Parallel Computing Research: A View from Berkeley”, Technical Report UCB/EECS-2006-183, EECS Department, University of California, Berkeley, December 18, 2006. pdf
  • Bryan Catanzaro and Brent Nelson, “Higher Radix Floating-Point Representations for FPGA-Based Arithmetic”, IEEE Symposium on Field-Programmable Custom Computing Machines, pages 161-170, 2005. pdf

Theses

  • Bryan Catanzaro, “Compilation Techniques for Embedded Data Parallel Languages”. PhD thesis, University of California, Berkeley, 2011. pdf
  • Bryan Catanzaro, “Higher Radix Floating-Point Representations for FPGA-Based Arithmetic”. MS thesis, Brigham Young University, 2005. pdf

Book Chapters

  • Andreas Klöckner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih. “GPU Scripting and Code Generation with PyCUDA,” In GPU Computing Gems, Volume 2. Morgan Kaufmann, 2011.

Magazine Articles

  • Bryan Catanzaro and Kurt Keutzer, “Parallel computing with patterns and frameworks”, XRDS: Crossroads, the ACM Magazine for Students. Volume 17, Issue 1, Pages 22-27, Fall 2010. pdf