GPU performance prediction using parametrized models

[1]  Flemming Nielson,et al.  Principles of Program Analysis , 1999, Springer Berlin Heidelberg.

[2]  Henry Wong,et al.  Analyzing CUDA workloads using a detailed GPU simulator , 2009, 2009 IEEE International Symposium on Performance Analysis of Systems and Software.

[3]  Subhash Saini,et al.  Performance prediction and its use in parallel and distributed computing systems , 2006, Future Gener. Comput. Syst..

[4]  Rudolf Eigenmann,et al.  Fast and effective orchestration of compiler optimizations for automatic performance tuning , 2006, International Symposium on Code Generation and Optimization (CGO'06).

[5]  Laszlo A. Belady,et al.  A Study of Replacement Algorithms for Virtual-Storage Computer , 1966, IBM Syst. J..

[6]  R. C. Whaley,et al.  Timing high performance kernels through empirical compilation , 2005, 2005 International Conference on Parallel Processing (ICPP'05).

[7]  H. Rice.  Classes of recursively enumerable sets and their decision problems , 1953 .

[8]  Stephen McCamant,et al.  The Daikon system for dynamic detection of likely invariants , 2007, Sci. Comput. Program..

[9]  Hyesoon Kim,et al.  An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness , 2009, ISCA '09.

[10]  Eric A. Brewer,et al.  PROTEUS: a high-performance parallel-architecture simulator , 1992, SIGMETRICS '92/PERFORMANCE '92.

[11]  William Gropp,et al.  An adaptive performance modeling tool for GPU architectures , 2010, PPoPP '10.

[12]  John M. Mellor-Crummey,et al.  Cross-architecture performance predictions for scientific applications using parameterized models , 2004, SIGMETRICS '04/Performance '04.

[13]  Sally A. McKee,et al.  An Approach to Performance Prediction for Parallel Applications , 2005, Euro-Par.

[14]  Nicholas Nethercote,et al.  Valgrind: a framework for heavyweight dynamic binary instrumentation , 2007, PLDI '07.

[15]  M. J. Quinn,et al.  Analytical performance prediction on multicomputers , 1993, Supercomputing '93.

[16]  D. V. Sidorov,et al.  The use of dynamic analysis for generation of input data that demonstrates critical bugs and vulnerabilities in programs , 2010, Programming and Computer Software.

[17]  Carl Staelin,et al.  lmbench: Portable Tools for Performance Analysis , 1996, USENIX Annual Technical Conference.

[18]  Sudhakar Yalamanchili,et al.  A characterization and analysis of PTX kernels , 2009, 2009 IEEE International Symposium on Workload Characterization (IISWC).

[19]  David Parello,et al.  Barra, a Modular Functional GPU Simulator for GPGPU , 2009 .

[20]  Sudhakar Yalamanchili,et al.  Modeling GPU-CPU workloads and systems , 2010, GPGPU-3.

[21]  David A. Padua,et al.  The Power of Belady?s Algorithm in Register Allocation for Long Basic Blocks , 2003, LCPC.

[22]  Yao Zhang,et al.  A quantitative performance analysis model for GPU architectures , 2011, 2011 IEEE 17th International Symposium on High Performance Computer Architecture.

[23]  Sartaj Sahni,et al.  Performance metrics: keeping the focus on runtime , 1996, IEEE Parallel Distributed Technol. Syst. Appl..

[24]  Keith D. Cooper,et al.  An Experimental Evaluation of List Scheduling , 1998 .

[25]  K. Srinathan,et al.  A performance prediction model for the CUDA GPGPU platform , 2009, 2009 International Conference on High Performance Computing (HiPC).

[26]  Mark N. Wegman,et al.  Efficiently computing static single assignment form and the control dependence graph , 1991, TOPL.