Fetching the paper…
Reading the bibliography…
Production software oftentimes suffers from the issue of performance inefficiencies caused by inappropriate use of data structures, programming abstractions, and conservative compiler optimizations.
Program Classification Using Gated Graph Attention Neural Network for Online Programming Service
Lu, M.; Tan, D.; Xiong, N.; Chen, Z.; and Li, H. 2019 · 1903
Earlier work this paper cites.
gprof: a call graph execution profiler (with retrospective)
Graham, S. L.; Kessler, P. B.; and McKusick, M. K. 1982 · 1982
Earlier work this paper cites.
Exploiting Hardware Performance Counters with Flow and Context Sensitive Profiling
Ammons, G.; Ball, T.; and Larus, J. R. 1997 · 1997
Earlier work this paper cites.
DynamoRIO: Efficient, Transparent, and Comprehensive Runtime Code Manipulation
Bruening, D. 2004 · 2004
Earlier work this paper cites.
Understanding source code evolution using abstract syntax tree matching
I. Neamtiu, J. F.; and Hicks, M. 2005 · 2005
Earlier work this paper cites.
An Imitation Learning Approach for Cache Replacement
Liu, E. Z.; Hashemi, M.; Swersky, K.; Ranganathan, P.; and Ahn, J. 2020 · 2006
Earlier work this paper cites.
Learning Forward Reuse Distance
Li, P.; and Gu, Y. 2020 · 2007
Earlier work this paper cites.
The Graph Neural Network Model
Scarselli, F.; Gori, M.; Tsoi, A. C.; Hagenbuchner, M.; and Monfardini, G. 2009 · 2009
Earlier work this paper cites.
HPCTOOLKIT: Tools for Performance Analysis of Optimized Parallel Programs Http://Hpctoolkit.Org
Adhianto, L.; Banerjee, S.; Fagan, M.; Krentel, M.; Marin, G.; Mellor-Crummey, J.; and Tallent, N. R. 2010 · 2010
Earlier work this paper cites.
DeadSpy: A Tool to Pinpoint Program Inefficiencies
Chabbi, M.; and Mellor-Crummey, J. 2012 · 2012
Earlier work this paper cites.
Intel VTune Amplifier XE 2013
2013 · 2013
Earlier work this paper cites.
Efficient Estimation of Wor Representations in Vector Space
Mikolov, T.; Chen, K.; Corrado, G. S.; and Dean, J. 2013 · 2013
Cited alongside, same era.
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Chung, J.; Gülçehre, Ç.; Cho, K.; and Bengio, Y. 2014 · 2014
Cited alongside, same era.
Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
Cited alongside, same era.
Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N.; and Welling, M. 2016 · 2016
Cited alongside, same era.
Gated Graph Sequence Neural Networks
Li, Y.; Zemel, R.; Brockschmidt, M.; and Tarlow, D. 2016 · 2016
Cited alongside, same era.
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L.; and Polosukhin, I. 2017 · 2017
Later among the works it cites.
REDSPY: Exploring Value Locality in Software
Wen, S.; Chabbi, M.; and Liu, X. 2017 · 2017
Later among the works it cites.
Relational inductive biases, deep learning, and graph networks
Battaglia, P. W.; Hamrick, J. B.; Bapst, V.; Sanchez-Gonzalez, A.; Zambaldi, V. F.; Malinowski, M.; Tacchetti, A.; Raposo, D.; Santoro, A.; Faulkner, R.; Gülçehre, Ç.; Song, H. F.; Ballard, A. J.; Gilmer, J.; Dahl, G. E.; Vaswani, A.; Allen, K. R.; Nash, C.; Langston, V.; Dyer, C.; Heess, N.; Wierstra, D.; Kohli, P.; Botvinick, M.; Vinyals, O.; Li, Y.; and Pascanu, R. 2018 · 2018
Later among the works it cites.
Velickovic, P.; Cucurull, G.; Casanova, A.; Romero, A.; Liò, P.; and Bengio, Y. 2018 · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
SoK: (State of) The Art of War: Offensive Techniques in Binary Analysis
Shoshitaishvili, Y.; Wang, R.; Salls, C.; Stephens, N.; Polino, M.; Dutcher, A.; Grosen, J.; Feng, S.; Hauser, C.; Kruegel, C.; and Vigna, G. 2016 · 2016
Cited alongside, same era.
A Survey of Machine Learning for Big Code and Naturalness
Allamanis, M.; Barr, E. T.; Devanbu, P. T.; and Sutton, C. A. 2017 · 2017
Cited alongside, same era.
Neural Message Passing for Quantum Chemistry
Gilmer, J.; Schoenholz, S. S.; Riley, P. F.; Vinyals, O.; and Dahl, G. E. 2017 · 2017
Cited alongside, same era.
Inductive Representation Learning on Large Graphs
Hamilton, W.; Ying, Z.; and Leskovec, J. 2017 · 2017
Cited alongside, same era.
Nvidia Tesla V100 GPU Architecture
Nvidia-Inc. 2017 · 2017
Cited alongside, same era.
SPEC CPU Benchmarks
SPEC. 2017 · 2017
Cited alongside, same era.
Wang, K.; Su, Z.; and Singh, R. 2018 · 2018
Later among the works it cites.
Watching for Software Inefficiencies with Witch 53(2): 332–347
Wen, S.; Liu, X.; Byrne, J.; and Chabbi, M. 2018 · 2018
Later among the works it cites.
Redundant Loads: A Software Inefficiency Indicator
Su, P.; Wen, S.; Yang, H.; Chabbi, M.; and Liu, X. 2019 · 2019
Later among the works it cites.
HOPPITY: Learning graph transformations to detect and fix bugs in programs
Dinella, E.; Dai, H.; Li, Z.; Naik, M.; Song, L.; and Wang, K. 2020 · 2020
Closest in time.
Learning execution through neural code fusion
Shi, Z.; Swersky, K.; Tarlow, D.; Ranganathan, P.; and Hashemi, M. 2020 · 2020
Closest in time.
Blended, Precise Semantic Program Embeddings
Wang, K.; and Su, Z. 2020 · 2020
Closest in time.
Order Matters: Semantic-Aware Neural Networks for Binary Code Similarity Detection
Yu, Z.; Cao, R.; Tang, Q.; Nie, S.; Huang, J.; and Wu, S. 2020 · 2020
Closest in time.