Selected Publications

LinkCitationAcceptance RateCollaboration(s)
Learned garbage collection Cen, Lujing, Ryan Marcus, Hongzi Mao, Justin Emile Gottschlich, Mohammad Alizadeh and Tim Kraska. “Learned garbage collection.” Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages (2020): n. pag.43%MIT
An Abstraction-Based Framework for Neural Network Verification Elboher, Yizhak Yisrael, Justin Emile Gottschlich and Guy Katz. “An Abstraction-Based Framework for Neural Network Verification.” ArXiv abs/1910.14574 (2019): n. pag.27%Hebrew University
A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions Alam, Mejbah, Justin Emile Gottschlich, Nesime Tatbul, Javier Turek, Timothy G. Mattson and Abdullah Muzahid. “A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions.” NeurIPS (2019).22%Texas A&M University, MIT
SysML: The New Frontier of Machine Learning Systems Ratner, Alexander, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Emile Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Xiaodong Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang and Ameet Talwalkar. “SysML: The New Frontier of Machine Learning Systems.” ArXiv abs/1904.03257 (2019): n. pag.-Stanford, University of Washington, Snorkel AI, IST Austria, ETH Zurich, Carnegie Mellon University, Google, Sisu Data, Microsoft, NVIDIA, University of Texas at Austin, Amazon, Intel, University of California San Diego, cTuning Foundation, Dividiti, UC Santa Cruz, Vector Institute, Univerrsity of Toronto, UC Berkeley, MIT, Facebook, University of Maryland, EPFL, IBM Research, Rice University, University of Wisconsin-Madison, Mila, University of Montreal, SambaNova Systems, University of Toronto, Cornell University, Determined AI, Eindhoven University of Technology, Petuum, Databricks
Precision and Recall for Time Series Tatbul N, Lee TJ, Zdonik S, Alam M, Gottschlich J (2018) Precision and Recall for Time Series. In: Advances in Neural Information Processing Systems, pp 1920–19303.5%Brown University
The three pillars of machine programming Justin Gottschlich, Armando Solar-Lezama, Nesime Tatbul, Michael Carbin, Martin Rinard, Regina Barzilay, Saman Amarasinghe, Joshua B. Tenenbaum, and Tim Mattson. 2018. The three pillars of machine programming. In Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages (MAPL 2018). Association for Computing Machinery, New York, NY, USA, 69–80.57%MIT
Precision and Recall for Range-Based Anomaly Detection Lee, Tae Jun, Justin Emile Gottschlich, Nesime Tatbul, Eric Metcalf and Stanley B. Zdonik. “Precision and Recall for Range-Based Anomaly Detection.” ArXiv abs/1801.03175 (2018): n. pag.57%Brown University
Greenhouse: A Zero-Positive Machine Learning System for Time-Series Anomaly Detection Lee, Tae-Jun, Justin Emile Gottschlich, Nesime Tatbul, Eric Metcalf and Stanley B. Zdonik. “Greenhouse: A Zero-Positive Machine Learning System for Time-Series Anomaly Detection.” ArXiv abs/1801.03168 (2018): n. pag.57%Brown University
Toward Scalable Verification for Safety-Critical Deep Networks Kuper, Lindsey, Guy Katz, Justin Emile Gottschlich, Kyle Julian, Clark W. Barrett and Mykel J. Kochenderfer. “Toward Scalable Verification for Safety-Critical Deep Networks.” ArXiv abs/1801.05950 (2018): n. pag.57%Stanford University
TSXProf: Profiling Hardware Transactions Liu, Yujie, Justin Gottschlich, Gilles Pokam, and Michael Spear. "TSXProf: Profiling hardware transactions." In 2015 International Conference on Parallel Architecture and Compilation (PACT), pp. 75-86. IEEE, 2015.21%Lehigh University
Invyswell: A Hybrid Transactional Memory for Haswell's Restricted Transactional Memory Calciu, Irina, Justin Gottschlich, Tatiana Shpeisman, Maurice Herlihy, and Gilles Pokam. "Invyswell: a hybrid transactional memory for haswell's restricted transactional memory." In 2014 23rd International Conference on Parallel Architecture and Compilation Techniques (PACT), pp. 187-199. IEEE, 2014. 25%Brown University
Towards Transactional Memory for OpenMP Wong, Michael, Eduard Ayguadé, Justin Gottschlich, Victor Luchangco, Bronis R. de Supinski, and Barna Bihari. "Towards transactional memory for openmp." In International Workshop on OpenMP, pp. 130-145. Springer, Cham, 2014.-IBM, Oracle, LLNL
Concurrent Predicates: A Debugging Technique for Every Parallel Programmer (Best Paper Nomination)Gottschlich, Justin, Gilles Pokam, Cristiano Pereira, and Youfeng Wu. "Concurrent predicates: A debugging technique for every parallel programmer." In Proceedings of the 22nd international conference on Parallel architectures and compilation techniques, pp. 331-340. IEEE, 2013.17%Intel Corp.
Using Elimination and Delegation to Implement a Scalable NUMA-Friendly Stack Calciu, Irina, Justin Gottschlich, and Maurice Herlihy. "Using elimination and delegation to implement a scalable NUMA-friendly stack." In 5th {USENIX} Workshop on Hot Topics in Parallelism (HotPar 13). 2013.-Brown University
But How Do We Really Debug Transactional Memory Programs? Gottschlich, Justin E., Rob Knauerhase, and Gilles Pokam. "But how do we really debug transactional memory programs?." In 5th {USENIX} Workshop on Hot Topics in Parallelism (HotPar 13). 2013.48%Intel Labs
QuickRec: Prototyping an Intel Architecture Extension for Record and Replay of Multithreaded Programs Pokam, Gilles, Klaus Danne, Cristiano Pereira, Rolf Kassa, Tim Kranich, Shiliang Hu, Justin Gottschlich et al. "QuickRec: prototyping an intel architecture extension for record and replay of multithreaded programs." In Proceedings of the 40th annual international symposium on computer architecture, pp. 643-654. 2013.19%UIUC
Generic Programming Needs Transactional Memory Gottschlich, Justin E., and Hans-J. Boehm. "Generic programming needs transactional memory." In The 8th ACM SIGPLAN Workshop on Transactional Computing. 2013.-HP Lab
Visualizing Transactional Memory Gottschlich, Justin E., Maurice P. Herlihy, Gilles A. Pokam, and Jeremy G. Siek. "Visualizing transactional memory." In Proceedings of the 21st international conference on Parallel architectures and compilation techniques, pp. 159-170. 2012.19%Brown University, CU-Boulder
Concurrent Predicates: Finding and Fixing the Root Cause of Concurrency Violations Gottschlich, Justin E., Gilles A. Pokam, and Cristiano L. Pereira. "Concurrent predicates: Finding and fixing the root cause of concurrency violations." In Proceedings of the 4th USENIX Workshop on Hot Topics in Parallelism (HotPar). 2012.-Intel Corp.
CoreRacer: A Practical Memory Race Recorder for Multicore x86 TSO Processors Pokam, Gilles, Cristiano Pereira, Shiliang Hu, Ali-Reza Adl-Tabatabai, Justin Gottschlich, Jungwoo Ha, and Youfeng Wu. "CoreRacer: a practical memory race recorder for multicore x86 TSO processors." In Proceedings of the 44th Annual IEEE/ACM International Symposium on Microarchitecture, pp. 216-225. 2011.21%Intel Corp., Google
Programming with Concurrent Predicates (Best Demo Award)Justin Gottschlich, Cristiano Pereira, Gilles Pokam, Jungwoo Ha. "Programming with Concurrent Predicates." 2011 Intel Software Professionals Conference (SWPC).47%Intel Corp.
Optimizing the Concurrent Execution of Locks and Transactions Gottschlich, Justin E., and JaeWoong Chung. "Optimizing the concurrent execution of locks and transactions." In International Workshop on Languages and Compilers for Parallel Computing, pp. 124-140. Springer, Berlin, Heidelberg, 2011.37%Intel Corp.
Reducing the Integration Complexity of Software Transactional Memory with TBoost.STM Escribá, Vicente J. Botet, Justin E. Gottschlich, and Dwight Y. Winkler. "Reducing the integration complexity of software transactional memory with tboost. stm." In Proceedings of the Fifth International Conference on Boost Libraries (BoostCon). 2010.-Alcatel-Lucent, University of Colorado at Boulder, California State Polytechnic University
Proving Conflict Serializability for Full Invalidation Gottschlich, Justin E., Jeremy G. Siek, and Manish Vachharajani. "Proving conflict serializability for full invalidation." 2010 Workshop on the Theory of Transactional Memory (WTTM).-University of Colorado at Boulder
An Efficient Software Transactional Memory Using Commit-Time Invalidation (Best Presentation Award)Gottschlich, Justin E., Manish Vachharajani, and Jeremy G. Siek. "An efficient software transactional memory using commit-time invalidation." In Proceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization, pp. 101-110. 2010.41%University of Colorado at Boulder
An Efficient Lock-Aware Transactional Memory Implementation Gottschlich, Justin E., Jeremy G. Siek, Manish Vachharajani, Dwight Y. Winkler, and Daniel A. Connors. "An efficient lock-aware transactional memory implementation." In Proceedings of the 4th workshop on the Implementation, Compilation, Optimization of Object-Oriented Languages and Programming Systems, pp. 10-17. 2009.-University of Colorado at Boulder, Nodeka, Colorado State University
Toward Simplified Parallel Support in C++ Gottschlich, Justin E., Jeremy G. Siek, Paul J. Rogers, and Manish Vachharajani. "Toward simplified parallel support in C++." In Proceedings of the Fourth International Conference on Boost Libraries (BoostCon). 2009.- University of Colorado at Boulder, Raytheon Company
Shifting the Parallel Programming Paradigm (Best Presentation Award)Gottschlich, Justin E., Dwight Y. Winkler, Mark W. Holmes, Jeremy G. Siek, Manish Vachharajani, and L. L. C. Nodeka. "Shifting the Parallel Programming Paradigm."27%Nodeka, LLC, Raytheon Company, University of Colorado at Boulder
Lock-Aware Transactional Memory Gottschlich, Justin E., Dan A. Connors, Dwight Y. Winkler, Jeremy G. Siek, and Manish Vachharajani. "Lock-aware transactional memory." In In ASPLOS’09: Proc. of the fourteenth international. 2009. -University of Colorado at Boulder, Nodeka, Colorado State University
Optimizing Consistency Checking for Memory-Intensive Transactions Gottschlich, Justin Emile, and Daniel A. Connors. "Optimizing consistency checking for memory-intensive transactions." In Proceedings of the twenty-seventh ACM symposium on Principles of distributed computing, pp. 451-451. 2008.-University of Colorado at Boulder
C++ Move Semantics for Exception Safety and Optimization in Software Transactional Memory Libraries Gottschlich, Justin E., Jeremy G. Siek, and Daniel A. Connors. "C++ move semantics for exception safety and optimization in software transactional memory libraries." In Proceedings of the Third International Workshop on Implementation, Compilation, Optimization of Object-Oriented Languages, Programs and Systems (ICOOOLPS). In conjunction with ECOOP. 2008.-University of Colorado at Boulder
Extending Contention Managers for User-Defined Priority-Based Transactions Gottschlich, Justin, and Daniel A. Connors. "Extending contention managers for user-defined priority-based transactions." In ACM Workshop on Exploiting Parallelism with Transactional Memory and other Hardware Assisted Methods (EPHAM), Boston, MA. 2008.-University of Colorado at Boulder
DracoSTM: A Practical C++ Approach to Software Transactional Memory DracoSTM: A Practical C++ Approach to Software Transactional Memory52%University of Colorado at Boulder