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Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady state (the throughput) is important for both compiler designers and performance engineers.
A stochastic approximation method
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A static parameter based performance prediction tool for parallel programs
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Predicting program execution times by analyzing static and dynamic program paths
Park, C. Y · 1993
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Hierarchical recurrent neural networks for long-term dependencies
El Hihi, S. and Bengio, Y · 1995
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Long short-term memory
Hochreiter, S. and Schmidhuber, J · 1997
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Predicting the running times of parallel programs by simulation
Rugina, R. and Schauser, K · 1998
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Scheduling straight-line code using reinforcement learning and rollouts
McGovern, A. and Moss, E · 1999
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Reliable and precise wcet determination for a real-life processor
Ferdinand, C., Heckmann, R., Langenbach, M., Martin, F., Schmidt, M., Theiling, H., Thesing, S., and Wilhelm, R · 2001
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Dynamic branch prediction with perceptrons
Jimenez, D. A. and Lin, C · 2001
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Meta optimization: Improving compiler heuristics with machine learning
Stephenson, M., Amarasinghe, S., Martin, M., and O’Reilly, U.-M · 2003
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An instruction throughput model of superscalar processors
Taha, T. M. and Wills, D. S · 2003
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Predicting the performance of parallel programs
Blanco, V., González, J. A., León, C., Rodrıguez, C., Rodrıguez, G., and Printista, M · 2004
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Llvm: A compilation framework for lifelong program analysis & transformation
Lattner, C. and Adve, V · 2004
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Spec cpu2006 benchmark suite, 2006
SPEC · 2006
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Fast compiler optimisation evaluation using code-feature based performance prediction
Dubach, C., Cavazos, J., Franke, B., Fursin, G., O’Boyle, M. F., and Temam, O · 2007
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Chronos: A timing analyzer for embedded software
Li, X., Liang, Y., Mitra, T., and Roychoudhury, A · 2007
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A first-order fine-grained multithreaded throughput model
Chen, X. E. and Aamodt, T. M · 2009
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Predicting execution time of computer programs using sparse polynomial regression
Huang, L., Jia, J., Yu, B., gon Chun, B., Maniatis, P., and Naik, M · 2010
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An evaluation of vectorizing compilers
Maleki, S., Gao, Y., Garzar, M. J., Wong, T., Padua, D. A., et al · 2011
Dag-recurrent neural networks for scene labeling
Shuai, B., Zuo, Z., Wang, G., and Wang, B · 2015
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Dag-structured long short-term memory for semantic compositionality
Zhu, X., Sobhani, P., and Guo, H · 2016
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Hierarchical boundary-aware neural encoder for video captioning
Baraldi, L., Grana, C., and Cucchiara, R · 2017
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Hierarchical multiscale recurrent neural networks
Chung, J., Ahn, S., and Bengio, Y · 2017
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Linguistic Knowledge as Memory for Recurrent Neural Networks
Dhingra, B., Yang, Z., Cohen, W. W., and Salakhutdinov, R · 2017
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Intel architecture code analyzer, 2017
Intel · 2017
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Niu, F., Recht, B., Re, C., and Wright, S. J · 2011
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Marss: a full system simulator for multicore x86 cpus
Patel, A., Afram, F., Chen, S., and Ghose, K · 2011
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GameTime: A toolkit for timing analysis of software
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Transparent dynamic instrumentation
Bruening, D., Zhao, Q., and Amarasinghe, S · 2012
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Constraint-based register allocation and instruction scheduling
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Pouchet, L.-N · 2012
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Neural network-based graph embedding for cross-platform binary code similarity detection
Xu, X., Liu, C., Feng, Q., Yin, H., Song, L., and Song, D · 2017
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Learning to represent programs with graphs
Allamanis, M., Brockschmidt, M., and Khademi, M · 2018
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Parallel program performance prediction using deterministic task graph analysis
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