2016
Automatic Parallelization of Pure Method Calls via Conditional Future Synthesis. Rishi Surendran and Vivek Sarkar. 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2016), November 2016.
OpenMP as a High-Level Specification Language for Parallelism. Max Grossman, Jun Shirako, Vivek Sarkar. International Workshop on OpenMP (IWOMP), October 2016.
An Extended Polyhedral Model for SPMD Programs and its use in Static Data Race Detection. Prasanth Chatarasi, Jun Shirako, Martin Kong, Vivek Sarkar. The 29th International Workshop on Languages and Compilers for Parallel Computing (LCPC), September 2016 [slides].
Dynamic Determinacy Race Detection for Task Parallelism with Futures. Rishi Surendran and Vivek Sarkar. 16th International Conference on Runtime Verification (RV'16), September 2016.
Integrating Asynchronous Task Parallelism with OpenSHMEM. Max Grossman, Vivek Kumar, Zoran Budimlic, Vivek Sarkar. OpenSHMEM Workshop, August 2016.
Brief Announcement: Dynamic Determinacy Race Detection for Task Parallelism with Futures. Rishi Surendran and Vivek Sarkar. 28th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), July 2016.
SWAT: A Programmable, In-Memory, Distributed, High-Performance Computing Platform . Max Grossman, Vivek Sarkar. International ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC), May 2016.
Automatic Data Layout Generation and Kernel Mapping for CPU+GPU Architectures. DeepakMajeti, KuldeepMeel, RajBarik and Vivek Sarkar. 25th International Conference on Compiler Construction (CC 2016), March 2016.
2015
Efficient Static and Dynamic Memory Management Techniques for Multi-GPU System. Max Grossman, Mauricio Araya-Polo. Workshop on Runtime Systems for Extreme Scale Programming Models and Architectures. November 2015.
Distributed, Heterogeneous Scheduling Techniques Motivated by Production Geophysical Applications. Max Grossman, Mauricio Araya-Polo. Workshop on Many-Task Computing on Clouds, Grids, and Supercomputer. November 2015.
Concurrent Collections. Kathleen Knobe, Michael G. Burke, and Frank Schlimbach. Programming Models for Parallel Computing, Chapter 11, pages 247-280. Pavan Balaj, editor. The MIT Press, November 2015.
Optimized Event-Driven Runtime Systems for Programmability and Performance. Sagnak Tasirlar. Ph.D. Thesis, October 2015.
Extending Polyhedral Model for Analysis and Transformations of OpenMP Programs. Prasanth Chatarasi, and Vivek Sarkar. PACT ACM Student Research Competition, October 2015. [accepted as poster with accompanying extended abstract][poster].
Race Detection in Two Dimensions. Dimitar Dimitrov, Martin Vechev, Vivek Sarkar. 27th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), June 2015.
Cooperative Execution of Parallel Tasks with Synchronization Constraints. Shams Imam. Ph.D. Thesis, May 2015.
Portable Programming Models for Heterogeneous Platforms. Deepak Majeti. Ph.D. Thesis, May 2015.
2014
DFGR: an Intermediate Graph Representation for Macro-Dataflow Programs. Alina Sbirlea, Louis-Noel Pouchet, Vivek Sarkar. Fourth Workshop on Dataflow Execution Models for Extreme Scale Computing - in conjunction with PACT 2014 (DFM 2014)
2013
2012
Integrating Task Parallelism with Actors. Shams Imam, Vivek Sarkar. Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), October 2012. [paper, slides]
Rice ROSE Compositional Analysis and Transformation Framework (R2CAT). Jisheng Zhao, Micheal Burke, Vivek Sarkar. LLNL Technical Report 590233, October 2012.
Determinacy and Repeatability of Parallel Program Schemata. Jack B. Dennis, Guang R. Gao, Vivek Sarkar. Workshop on Data-Flow Execution Models for Extreme Scale Computing (DFM 2012).
Report on Inter-Agency Workshop on HPC Resilience at Extreme Scale. (Editor: John T. Daly.) February 2012.
2011
2010
2009
2008
2007
Acknowledgment
This material is based upon work supported by the National Science Foundation under Grants No. 0833166, 0938018, 0926127, 0964520, 1302570. Any opinions,findings and conclusionsorrecomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).