| The tao of parallelism in algorithms K Pingali, D Nguyen, M Kulkarni, M Burtscher, MA Hassaan, R Kaleem, ... Proceedings of the 32nd ACM SIGPLAN conference on Programming language …, 2011 | 537 | 2011 |
| A quantitative study of irregular programs on GPUs M Burtscher, R Nasre, K Pingali 2012 IEEE International Symposium on Workload Characterization (IISWC), 141-151, 2012 | 516 | 2012 |
| Bridging the processor-memory performance gap with 3D IC technology CC Liu, I Ganusov, M Burtscher, S Tiwari IEEE Design & Test of Computers 22 (6), 556-564, 2005 | 365 | 2005 |
| FPC: A high-speed compressor for double-precision floating-point data M Burtscher, P Ratanaworabhan IEEE transactions on computers 58 (1), 18-31, 2008 | 346 | 2008 |
| The VPC trace-compression algorithms M Burtscher, I Ganusov, SJ Jackson, J Ke, P Ratanaworabhan, NB Sam IEEE Transactions on Computers 54 (11), 1329-1344, 2005 | 341 | 2005 |
| Lonestar: A suite of parallel irregular programs M Kulkarni, M Burtscher, C Casçaval, K Pingali 2009 IEEE International Symposium on Performance Analysis of Systems and …, 2009 | 248 | 2009 |
| Fast lossless compression of scientific floating-point data P Ratanaworabhan, J Ke, M Burtscher Data Compression Conference (DCC'06), 133-142, 2006 | 247 | 2006 |
| An efficient CUDA implementation of the tree-based barnes hut n-body algorithm M Burtscher, K Pingali GPU computing Gems Emerald edition, 75-92, 2011 | 236 | 2011 |
| How much parallelism is there in irregular applications? M Kulkarni, M Burtscher, R Inkulu, K Pingali, C Casçaval ACM sigplan notices 44 (4), 3-14, 2009 | 224 | 2009 |
| A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries B Li, Y Lu, C Li, A Godil, T Schreck, M Aono, M Burtscher, Q Chen, ... Computer Vision and Image Understanding 131, 1-27, 2015 | 164 | 2015 |
| SHREC’14 track: Extended large scale sketch-based 3D shape retrieval B Li, Y Lu, C Li, A Godil, T Schreck, M Aono, M Burtscher, H Fu, T Furuya, ... Eurographics workshop on 3D object retrieval 2014, 121-130, 2014 | 155 | 2014 |
| Data-driven versus topology-driven irregular computations on GPUs R Nasre, M Burtscher, K Pingali 2013 IEEE 27th International Symposium on Parallel and Distributed …, 2013 | 153 | 2013 |
| A GPU implementation of inclusion-based points-to analysis M Mendez-Lojo, M Burtscher, K Pingali ACM SIGPLAN Notices 47 (8), 107-116, 2012 | 146 | 2012 |
| Effects of dynamic voltage and frequency scaling on a k20 gpu R Ge, R Vogt, J Majumder, A Alam, M Burtscher, Z Zong 2013 42nd International Conference on Parallel Processing, 826-833, 2013 | 138 | 2013 |
| Perfexpert: An easy-to-use performance diagnosis tool for hpc applications M Burtscher, BD Kim, J Diamond, J McCalpin, L Koesterke, J Browne SC'10: Proceedings of the 2010 ACM/IEEE International Conference for High …, 2010 | 137 | 2010 |
| High throughput compression of double-precision floating-point data M Burtscher, P Ratanaworabhan 2007 Data Compression Conference (DCC'07), 293-302, 2007 | 137 | 2007 |
| Morph algorithms on GPUs R Nasre, M Burtscher, K Pingali Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of …, 2013 | 136 | 2013 |
| Measuring GPU power with the K20 built-in sensor M Burtscher, I Zecena, Z Zong Proceedings of Workshop on General Purpose Processing Using GPUs, 28-36, 2014 | 124 | 2014 |
| Ordered vs. unordered: a comparison of parallelism and work-efficiency in irregular algorithms MA Hassaan, M Burtscher, K Pingali Acm Sigplan Notices 46 (8), 3-12, 2011 | 120 | 2011 |
| VPC3: A fast and effective trace-compression algorithm M Burtscher ACM SIGMETRICS Performance Evaluation Review 32 (1), 167-176, 2004 | 92 | 2004 |
Keshav PingaliProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
