Tree structured analysis on GPU power study
暂无分享,去创建一个
Bin Li | Lu Peng | Ying Zhang | Jianmin Chen | Jih-Kwon Peir | B. Li | Jianmin Chen | Ying Zhang | Lu Peng | J. Peir | Bin Li
[1] Margaret Martonosi,et al. Wattch: a framework for architectural-level power analysis and optimizations , 2000, Proceedings of 27th International Symposium on Computer Architecture (IEEE Cat. No.RS00201).
[2] Mahmut T. Kandemir,et al. The design and use of simplePower: a cycle-accurate energy estimation tool , 2000, Proceedings 37th Design Automation Conference.
[3] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[4] Kevin Skadron,et al. Studying Thermal Management for Graphics-Processor Architectures , 2005, IEEE International Symposium on Performance Analysis of Systems and Software, 2005. ISPASS 2005..
[5] David M. Brooks,et al. Accurate and efficient regression modeling for microarchitectural performance and power prediction , 2006, ASPLOS XII.
[6] Weiguo Liu,et al. Performance Predictions for General-Purpose Computation on GPUs , 2007, 2007 International Conference on Parallel Processing (ICPP 2007).
[7] James Demmel,et al. Benchmarking GPUs to tune dense linear algebra , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.
[8] Erik Lindholm,et al. NVIDIA Tesla: A Unified Graphics and Computing Architecture , 2008, IEEE Micro.
[9] Wen-mei W. Hwu,et al. Optimization principles and application performance evaluation of a multithreaded GPU using CUDA , 2008, PPoPP.
[10] Wen-mei W. Hwu,et al. Program optimization space pruning for a multithreaded gpu , 2008, CGO '08.
[11] Majid Sarrafzadeh,et al. Energy-aware high performance computing with graphic processing units , 2008, CLUSTER 2008.
[12] Henry Wong,et al. Analyzing CUDA workloads using a detailed GPU simulator , 2009, 2009 IEEE International Symposium on Performance Analysis of Systems and Software.
[13] Kevin Skadron,et al. Rodinia: A benchmark suite for heterogeneous computing , 2009, 2009 IEEE International Symposium on Workload Characterization (IISWC).
[14] Hyesoon Kim,et al. An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness , 2009, ISCA '09.
[15] Song Huang,et al. On the energy efficiency of graphics processing units for scientific computing , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.
[16] Arnaud Tisserand,et al. Power Consumption of GPUs from a Software Perspective , 2009, ICCS.
[17] J. Xu. OpenCL – The Open Standard for Parallel Programming of Heterogeneous Systems , 2009 .
[18] Hyesoon Kim,et al. An integrated GPU power and performance model , 2010, ISCA.
[19] Reiji Suda,et al. Investigation on the power efficiency of multi-core and GPU Processing Element in large scale SIMD computation with CUDA , 2010, International Conference on Green Computing.
[20] Justin P. Haldar,et al. Accelerating iterative field-compensated MR image reconstruction on GPUs , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[21] Lu Peng,et al. Weak execution ordering - exploiting iterative methods on many-core GPUs , 2010, 2010 IEEE International Symposium on Performance Analysis of Systems & Software (ISPASS).
[22] Satoshi Matsuoka,et al. Statistical power modeling of GPU kernels using performance counters , 2010, International Conference on Green Computing.
[23] Xiaohan Ma,et al. Statistical Power Consumption Analysis and Modeling for GPU-based Computing , 2011 .
[24] Bin Li,et al. Statistical GPU power analysis using tree-based methods , 2011, 2011 International Green Computing Conference and Workshops.
[25] Kurt Hornik,et al. The Comprehensive R Archive Network , 2012 .
[26] Michael C. Hout,et al. Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.
[27] K. Ramani,et al. PowerRed : A Flexible Modeling Framework for Power Efficiency Exploration in GPUs , .