Justin Gottschlich
Justin Gottschlich
Principal AI Scientist & Director of Machine Programming Research, Intel Labs
Verified email at intel.com - Homepage
Cited by
Cited by
An efficient software transactional memory using commit-time invalidation
JE Gottschlich, M Vachharajani, JG Siek
Proceedings of the 8th annual IEEE/ACM international symposium on Code …, 2010
Invyswell: a hybrid transactional memory for haswell's restricted transactional memory
I Calciu, J Gottschlich, T Shpeisman, M Herlihy, G Pokam
2014 23rd International Conference on Parallel Architecture and Compilation …, 2014
QuickRec: Prototyping an Intel architecture extension for record and replay of multithreaded programs
G Pokam, K Danne, C Pereira, R Kassa, T Kranich, S Hu, J Gottschlich, ...
Proceedings of the 40th annual international symposium on computer …, 2013
Coreracer: A practical memory race recorder for multicore x86 tso processors
G Pokam, C Pereira, S Hu, AR Adl-Tabatabai, J Gottschlich, J Ha, Y Wu
Proceedings of the 44th Annual IEEE/ACM International Symposium on …, 2011
Precision and recall for time series
N Tatbul, TJ Lee, S Zdonik, M Alam, J Gottschlich
arXiv preprint arXiv:1803.03639, 2018
Using elimination and delegation to implement a scalable NUMA-friendly stack
I Calciu, J Gottschlich, M Herlihy
5th {USENIX} Workshop on Hot Topics in Parallelism (HotPar 13), 2013
DracoSTM: A practical C++ approach to software transactional memory
JE Gottschlich, DA Connors
Proceedings of the 2007 Symposium on Library-Centric Software Design, 52-66, 2007
The three pillars of machine programming
J Gottschlich, A Solar-Lezama, N Tatbul, M Carbin, M Rinard, R Barzilay, ...
Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine …, 2018
Extending contention managers for user-defined priority-based transactions
J Gottschlich, DA Connors
Proceedings of the 2008 Workshop on Exploiting Parallelism with …, 2008
An abstraction-based framework for neural network verification
YY Elboher, J Gottschlich, G Katz
International Conference on Computer Aided Verification, 43-65, 2020
Greenhouse: A zero-positive machine learning system for time-series anomaly detection
TJ Lee, J Gottschlich, N Tatbul, E Metcalf, S Zdonik
arXiv preprint arXiv:1801.03168, 2018
AI Programmer: autonomously creating software programs using genetic algorithms
K Becker, J Gottschlich
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021
Autonomous vehicle advanced sensing and response
B Lakshamanan, LL Hurd, BJ Ashbaugh, E Ould-Ahmed-Vall, L Ma, J Jin, ...
US Patent 10,332,320, 2019
Toward scalable verification for safety-critical deep networks
L Kuper, G Katz, J Gottschlich, K Julian, C Barrett, M Kochenderfer
arXiv preprint arXiv:1801.05950, 2018
MLSys: The new frontier of machine learning systems
A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ...
arXiv preprint arXiv:1904.03257, 2019
Programmable coarse grained and sparse matrix compute hardware with advanced scheduling
E Nurvitadhi, B Vembu, NCG Von Borries, R Barik, TH Lin, K Sinha, ...
US Patent 10,186,011, 2019
Visualizing transactional memory
JE Gottschlich, MP Herlihy, GA Pokam, JG Siek
Proceedings of the 21st international conference on Parallel architectures …, 2012
Draft specification of transactional language constructs for c++
AR Adl-Tabatabai, T Shpeisman, J Gottschlich
Enabling maximum concurrency in a hybrid transactional memory system
I Calciu, JE Gottschlich, T Shpeisman, GA Pokam
US Patent 9,971,627, 2018
Replay execution of instructions in thread chunks in the chunk order recorded during previous execution
JE Gottschlich, K Danne, CL Pereira, GA Pokam, R Kassa, S Hu, ...
US Patent 9,317,297, 2016
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