| An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness S Hong, H Kim Proceedings of the 36th annual international symposium on Computer …, 2009 | 839 | 2009 |
| Qilin: exploiting parallelism on heterogeneous multiprocessors with adaptive mapping CK Luk, S Hong, H Kim 2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture …, 2009 | 735 | 2009 |
| An integrated GPU power and performance model S Hong, H Kim Proceedings of the 37th annual international symposium on Computer …, 2010 | 655 | 2010 |
| Feedback directed prefetching: Improving the performance and bandwidth-efficiency of hardware prefetchers S Srinath, O Mutlu, H Kim, YN Patt 2007 IEEE 13th International Symposium on High Performance Computer …, 2007 | 409 | 2007 |
| A performance analysis framework for identifying potential benefits in GPGPU applications J Sim, A Dasgupta, H Kim, R Vuduc Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of …, 2012 | 252 | 2012 |
| Graphpim: Enabling instruction-level pim offloading in graph computing frameworks L Nai, R Hadidi, J Sim, H Kim, P Kumar, H Kim 2017 IEEE International symposium on high performance computer architecture …, 2017 | 233 | 2017 |
| Many-thread aware prefetching mechanisms for GPGPU applications J Lee, NB Lakshminarayana, H Kim, R Vuduc 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture, 213-224, 2010 | 175 | 2010 |
| When prefetching works, when it doesn’t, and why J Lee, H Kim, R Vuduc ACM Transactions on Architecture and Code Optimization (TACO) 9 (1), 1-29, 2012 | 166 | 2012 |
| TAP: A TLP-aware cache management policy for a CPU-GPU heterogeneous architecture J Lee, H Kim IEEE International Symposium on High-Performance Comp Architecture, 1-12, 2012 | 160 | 2012 |
| GraphBIG: understanding graph computing in the context of industrial solutions L Nai, Y Xia, IG Tanase, H Kim, CY Lin SC'15: Proceedings of the International Conference for High Performance …, 2015 | 146 | 2015 |
| SD3: A scalable approach to dynamic data-dependence profiling M Kim, H Kim, CK Luk 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture, 535-546, 2010 | 135 | 2010 |
| Transparent hardware management of stacked dram as part of memory J Sim, AR Alameldeen, Z Chishti, C Wilkerson, H Kim 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture, 13-24, 2014 | 129 | 2014 |
| Techniques for efficient processing in runahead execution engines O Mutlu, H Kim, YN Patt 32nd International Symposium on Computer Architecture (ISCA'05), 370-381, 2005 | 123 | 2005 |
| A mostly-clean DRAM cache for effective hit speculation and self-balancing dispatch J Sim, GH Loh, H Kim, M OConnor, M Thottethodi 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture, 247-257, 2012 | 118 | 2012 |
| Age based scheduling for asymmetric multiprocessors NB Lakshminarayana, J Lee, H Kim Proceedings of the conference on high performance computing networking …, 2009 | 104 | 2009 |
| Efficient runahead execution: Power-efficient memory latency tolerance O Mutlu, H Kim, YN Patt IEEE Micro 26 (1), 10-20, 2006 | 86 | 2006 |
| Power modeling for GPU architectures using McPAT J Lim, NB Lakshminarayana, H Kim, W Song, S Yalamanchili, W Sung ACM Transactions on Design Automation of Electronic Systems (TODAES) 19 (3 …, 2014 | 80 | 2014 |
| Macsim: A cpu-gpu heterogeneous simulation framework user guide H Kim, J Lee, NB Lakshminarayana, J Sim, J Lim, T Pho Georgia Institute of Technology, 2012 | 71 | 2012 |
| Effect of instruction fetch and memory scheduling on gpu performance NB Lakshminarayana, H Kim Workshop on Language, Compiler, and Architecture Support for GPGPU 88, 2010 | 67 | 2010 |
| Characterizing the deployment of deep neural networks on commercial edge devices R Hadidi, J Cao, Y Xie, B Asgari, T Krishna, H Kim 2019 IEEE International Symposium on Workload Characterization (IISWC), 35-48, 2019 | 63 | 2019 |
Onur MutluETH Zürich and Carnegie Mellon UniversityVerified email at inf.ethz.ch
