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ORCIDVivek Sarkar
Person information
- affiliation: Georgia Institute of Technology, GA, USA
- affiliation (former): Rice University, Department of Computer Science
- affiliation (former): IBM Research
- award (2020): ACM-IEEE CS Ken Kennedy Award
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2020 – today
- 2023
[j36]Sri Raj Paul, Akihiro Hayashi, Kun Chen, Youssef Elmougy, Vivek Sarkar:
A Fine-grained Asynchronous Bulk Synchronous parallelism model for PGAS applications. J. Comput. Sci. 69: 102014 (2023)- [i13]Akihiro Hayashi, Austin Adams, Jeffrey Young, Alexander McCaskey, Eugene F. Dumitrescu, Vivek Sarkar, Thomas M. Conte:
Enabling Multi-threading in Heterogeneous Quantum-Classical Programming Models. CoRR abs/2301.11559 (2023) - 2022
- [j35]Seonmyeong Bak, Colleen Bertoni, Swen Boehm, Reuben D. Budiardja, Barbara M. Chapman, Johannes Doerfert
, Markus Eisenbach, Hal Finkel, Oscar R. Hernandez, Joseph Huber, Shintaro Iwasaki, Vivek Kale, Paul R. C. Kent, JaeHyuk Kwack, Meifeng Lin, Piotr Luszczek, Ye Luo, Buu Pham, Swaroop Pophale, Kiran Ravikumar, Vivek Sarkar, Thomas Scogland, Shilei Tian, P. K. Yeung:
OpenMP application experiences: Porting to accelerated nodes. Parallel Comput. 109: 102856 (2022) - [j34]Prasanth Chatarasi, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Tushar Krishna, Vivek Sarkar:
Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators. ACM Trans. Archit. Code Optim. 19(1): 6:1-6:26 (2022) - [c241]Tong Zhou, Ruiqin Tian, Rizwan A. Ashraf, Roberto Gioiosa, Gokcen Kestor, Vivek Sarkar:
ReACT: Redundancy-Aware Code Generation for Tensor Expressions. PACT 2022: 1-13 - [c240]Sana Damani, Prithayan Barua, Vivek Sarkar:
Memory access scheduling to reduce thread migrations. CC 2022: 144-155 - [c239]Matthew Whitlock, Nicolas Morales, George Bosilca, Aurelien Bouteiller, Bogdan Nicolae, Keita Teranishi, Elisabeth Giem, Vivek Sarkar:
Integrating process, control-flow, and data resiliency layers using a hybrid Fenix/Kokkos approach. CLUSTER 2022: 418-428 - [c238]Feiyang Jin, John Jacobson, Samuel D. Pollard, Vivek Sarkar:
MiniKokkos: A Calculus of Portable Parallelism. Correctness@SC 2022: 37-44 - [c237]Lechen Yu, Feiyang Jin, Joachim Protze, Vivek Sarkar:
Leveraging the Dynamic Program Structure Tree to Detect Data Races in OpenMP Programs. Correctness@SC 2022: 54-62 - [c236]Jisheng Zhao, Colleen Bertoni, Jeffrey Young, Kevin Harms, Vivek Sarkar, Brice Videau:
HIPLZ: Enabling Performance Portability for Exascale Systems. Euro-Par Workshops 2022: 197-210 - [c235]Jun Shirako, Akihiro Hayashi, Sri Raj Paul, Alexey Tumanov, Vivek Sarkar:
Automatic Parallelization of Python Programs for Distributed Heterogeneous Computing. Euro-Par 2022: 350-366 - [c234]Sri Raj Paul, Akihiro Hayashi, Kun Chen, Vivek Sarkar:
A Productive and Scalable Actor-Based Programming System for PGAS Applications. ICCS (1) 2022: 233-247 - [c233]Akihiro Hayashi, Sri Raj Paul, Vivek Sarkar:
A Multi-Level Platform-Independent GPU API for High-Level Programming Models. ISC Workshops 2022: 90-107 - [p2]Vivek Sarkar, Fabrice Rastello:
Introduction. SSA-based Compiler Design 2022: 157-163 - [p1]Vivek Sarkar, Kathleen Knobe, Stephen Fink:
Array SSA Form. SSA-based Compiler Design 2022: 227-240 - [i12]Jun Shirako, Akihiro Hayashi, Sri Raj Paul, Alexey Tumanov, Vivek Sarkar:
Automatic Parallelization of Python Programs for Distributed Heterogeneous Computing. CoRR abs/2203.06233 (2022) - 2021
- [j33]Ohad Rau, Caleb Voss, Vivek Sarkar:
Linear Promises: Towards Safer Concurrent Programming (Artifact). Dagstuhl Artifacts Ser. 7(2): 15:1-15:3 (2021) - [c232]Ohad Rau, Caleb Voss, Vivek Sarkar:
Linear Promises: Towards Safer Concurrent Programming. ECOOP 2021: 13:1-13:27 - [c231]Seonmyeong Bak, Oscar R. Hernandez, Mark Gates, Piotr Luszczek, Vivek Sarkar:
Task-graph scheduling extensions for efficient synchronization and communication. ICS 2021: 88-101 - [c230]Lechen Yu, Joachim Protze, Oscar R. Hernandez, Vivek Sarkar:
ARBALEST: Dynamic Detection of Data Mapping Issues in Heterogeneous OpenMP Applications. IPDPS 2021: 464-474 - [c229]Max Grossman, Steve Poole, Howard Pritchard, Vivek Sarkar:
SHMEM-ML: Leveraging OpenSHMEM and Apache Arrow for Scalable, Composable Machine Learning. OpenSHMEM 2021: 111-125 - [c228]Caleb Voss, Vivek Sarkar:
An ownership policy and deadlock detector for promises. PPoPP 2021: 348-361 - [e13]Santosh Pande, Vivek Sarkar:
Languages and Compilers for Parallel Computing - 32nd International Workshop, LCPC 2019, Atlanta, GA, USA, October 22-24, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11998, Springer 2021, ISBN 978-3-030-72788-8 [contents] - [i11]Caleb Voss, Vivek Sarkar:
An Ownership Policy and Deadlock Detector for Promises. CoRR abs/2101.01312 (2021) - [i10]Sri Raj Paul, Akihiro Hayashi, Kun Chen, Vivek Sarkar:
A Scalable Actor-based Programming System for PGAS Runtimes. CoRR abs/2107.05516 (2021) - 2020
- [j32]Hyoukjun Kwon, Prasanth Chatarasi, Vivek Sarkar, Tushar Krishna, Michael Pellauer, Angshuman Parashar:
MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings. IEEE Micro 40(3): 20-29 (2020) - [c227]Prithayan Barua, Jisheng Zhao, Vivek Sarkar:
OmpMemOpt: Optimized Memory Movement for Heterogeneous Computing. Euro-Par 2020: 200-216 - [c226]Prasanth Chatarasi, Stephen Neuendorffer, Samuel Bayliss, Kees A. Vissers, Vivek Sarkar:
Vyasa: A High-Performance Vectorizing Compiler for Tensor Convolutions on the Xilinx AI Engine. HPEC 2020: 1-10 - [c225]Akihiro Hayashi, Sri Raj Paul, Vivek Sarkar:
Exploring a multi-resolution GPU programming model for Chapel. IPDPS Workshops 2020: 675 - [c224]Lechen Yu, Joachim Protze, Oscar R. Hernandez, Vivek Sarkar:
A Study of Memory Anomalies in OpenMP Applications. IWOMP 2020: 328-342 - [c223]Jun Shirako, Vivek Sarkar:
An Affine Scheduling Framework for Integrating Data Layout and Loop Transformations. LCPC 2020: 3-19 - [c222]Tong Zhou, Jun Shirako, Anirudh Jain, Sriseshan Srikanth, Thomas M. Conte, Richard W. Vuduc, Vivek Sarkar:
Intrepydd: performance, productivity, and portability for data science application kernels. Onward! 2020: 65-83 - [c221]Sri Raj Paul, Akihiro Hayashi, Matthew Whitlock, Seonmyeong Bak, Keita Teranishi, Jackson R. Mayo, Max Grossman, Vivek Sarkar:
Integrating Inter-Node Communication with a Resilient Asynchronous Many-Task Runtime System. ExaMPI@SC 2020: 41-51 - [c220]Max Grossman, Howard Pritchard, Steve Poole, Vivek Sarkar:
HOOVER: Leveraging OpenSHMEM for High Performance, Flexible Streaming Graph Applications. PAW-ATM@SC 2020: 55-65 - [e12]Vivek Sarkar, Hyesoon Kim:
PACT '20: International Conference on Parallel Architectures and Compilation Techniques, Virtual Event, GA, USA, October 3-7, 2020. ACM 2020, ISBN 978-1-4503-8075-1 [contents] - [i9]Prasanth Chatarasi, Hyoukjun Kwon, Natesh Raina, Saurabh Malik, Vaisakh Haridas, Tushar Krishna, Vivek Sarkar:
MARVEL: A Decoupled Model-driven Approach for Efficiently Mapping Convolutions on Spatial DNN Accelerators. CoRR abs/2002.07752 (2020) - [i8]Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Paul Petersen, Jesmin Jahan Tithi, Tim Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich:
Context-Aware Parse Trees. CoRR abs/2003.11118 (2020) - [i7]Prasanth Chatarasi, Stephen Neuendorffer, Samuel Bayliss, Kees A. Vissers, Vivek Sarkar:
Vyasa: A High-Performance Vectorizing Compiler for Tensor Convolutions on the Xilinx AI Engine. CoRR abs/2006.01331 (2020) - [i6]Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Nesime Tatbul, Jesmin Jahan Tithi, Paul Petersen, Timothy G. Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich:
MISIM: An End-to-End Neural Code Similarity System. CoRR abs/2006.05265 (2020) - [i5]Fangke Ye, Jisheng Zhao, Vivek Sarkar:
Advanced Graph-Based Deep Learning for Probabilistic Type Inference. CoRR abs/2009.05949 (2020) - [i4]Seonmyeong Bak, Oscar R. Hernandez, Mark Gates, Piotr Luszczek, Vivek Sarkar:
Task-Graph Scheduling Extensions for Efficient Synchronization and Communication. CoRR abs/2011.03196 (2020)
2010 – 2019
- 2019
- [j31]Akihiro Hayashi, Jun Shirako, Ettore Tiotto, Robert Ho, Vivek Sarkar:
Performance evaluation of OpenMP's target construct on GPUs - exploring compiler optimisations. Int. J. High Perform. Comput. Netw. 13(1): 54-69 (2019) - [c219]Tong Zhou, Michael R. Jantz, Prasad A. Kulkarni, Kshitij A. Doshi, Vivek Sarkar:
Valence: variable length calling context encoding. CC 2019: 147-158 - [c218]Sri Raj Paul, Akihiro Hayashi, Nicole Slattengren, Hemanth Kolla, Matthew Whitlock, Seonmyeong Bak, Keita Teranishi, Jackson R. Mayo, Vivek Sarkar:
Enabling Resilience in Asynchronous Many-Task Programming Models. Euro-Par 2019: 346-360 - [c217]Nitish Kumar Srivastava, Hongbo Rong, Prithayan Barua, Guanyu Feng, Huanqi Cao, Zhiru Zhang, David H. Albonesi, Vivek Sarkar, Wenguang Chen, Paul Petersen, Geoff Lowney, Adam Herr, Christopher J. Hughes, Timothy G. Mattson, Pradeep Dubey:
T2S-Tensor: Productively Generating High-Performance Spatial Hardware for Dense Tensor Computations. FCCM 2019: 181-189 - [c216]Vivek Sarkar:
Data Flow Execution Models - A Third Opinion. HiPC 2019: 1 - [c215]Seonmyeong Bak, Yanfei Guo, Pavan Balaji, Vivek Sarkar:
Optimized Execution of Parallel Loops via User-Defined Scheduling Policies. ICPP 2019: 38:1-38:10 - [c214]Jeffrey S. Young, E. Jason Riedy, Thomas M. Conte, Vivek Sarkar, Prasanth Chatarasi, Sriseshan Srikanth:
Experimental Insights from the Rogues Gallery. ICRC 2019: 80-87 - [c213]Bahareh Goodarzi, Farzad Khorasani, Vivek Sarkar, Dhrubajyoti Goswami:
High Performance Multilevel Graph Partitioning on GPU. HPCS 2019: 769-778 - [c212]Prithayan Barua, Jun Shirako, Whitney Tsang, Jeeva Paudel, Wang Chen, Vivek Sarkar:
OMPSan: Static Verification of OpenMP's Data Mapping Constructs. IWOMP 2019: 3-18 - [c211]Sana Damani, Vivek Sarkar:
Common Subexpression Convergence: A New Code Optimization for SIMT Processors. LCPC 2019: 64-73 - [c210]Hyoukjun Kwon, Prasanth Chatarasi, Michael Pellauer, Angshuman Parashar, Vivek Sarkar, Tushar Krishna:
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow: A Data-Centric Approach. MICRO 2019: 754-768 - [c209]Caleb Voss, Tiago Cogumbreiro, Vivek Sarkar:
Transitive joins: a sound and efficient online deadlock-avoidance policy. PPoPP 2019: 378-390 - 2018
- [j30]Dimitar K. Dimitrov, Martin T. Vechev, Vivek Sarkar:
Race Detection in Two Dimensions. ACM Trans. Parallel Comput. 4(4): 19:1-19:22 (2018) - [c208]Prithayan Barua, Jun Shirako, Vivek Sarkar:
Cost-driven thread coarsening for GPU kernels. PACT 2018: 32:1-32:14 - [c207]Oleksandr Zinenko, Sven Verdoolaege, Chandan Reddy, Jun Shirako, Tobias Grosser, Vivek Sarkar, Albert Cohen:
Modeling the conflicting demands of parallelism and Temporal/Spatial locality in affine scheduling. CC 2018: 3-13 - [c206]Jisheng Zhao, Michael G. Burke, Vivek Sarkar:
Parallel sparse flow-sensitive points-to analysis. CC 2018: 59-70 - [c205]Wael R. Elwasif, Eduardo F. D'Azevedo, Arghya Chatterjee, Gonzalo Alvarez, Oscar R. Hernandez, Vivek Sarkar:
MiniApp for Density Matrix Renormalization Group Hamiltonian Application Kernel. CLUSTER 2018: 590-597 - [c204]Cody Hao Yu, Peng Wei, Max Grossman, Peng Zhang, Vivek Sarkar, Jason Cong:
S2FA: an accelerator automation framework for heterogeneous computing in datacenters. DAC 2018: 153:1-153:6 - [c203]Lechen Yu, Vivek Sarkar:
GT-Race: Graph Traversal Based Data Race Detection for Asynchronous Many-Task Parallelism. Euro-Par 2018: 59-73 - [c202]Ankush Mandal, Rajkishore Barik, Vivek Sarkar:
Using Dynamic Compilation to Achieve Ninja Performance for CNN Training on Many-Core Processors. Euro-Par 2018: 265-278 - [c201]Farzad Khorasani, Hodjat Asghari Esfeden, Amin Farmahini Farahani, Nuwan Jayasena, Vivek Sarkar:
RegMutex: Inter-Warp GPU Register Time-Sharing. ISCA 2018: 816-828 - [c200]Prasanth Chatarasi, Jun Shirako, Albert Cohen, Vivek Sarkar:
A Unified Approach to Variable Renaming for Enhanced Vectorization. LCPC 2018: 1-20 - [c199]Farzad Khorasani, Hodjat Asghari Esfeden, Nael B. Abu-Ghazaleh, Vivek Sarkar:
In-Register Parameter Caching for Dynamic Neural Nets with Virtual Persistent Processor Specialization. MICRO 2018: 377-389 - [c198]Ankush Mandal, He Jiang, Anshumali Shrivastava, Vivek Sarkar:
Topkapi: Parallel and Fast Sketches for Finding Top-K Frequent Elements. NeurIPS 2018: 10921-10931 - [c197]Srdan Milakovic, Zoran Budimlic, Howard Pritchard, Anthony Curtis, Barbara M. Chapman, Vivek Sarkar:
SHCOLL - A Standalone Implementation of OpenSHMEM-Style Collectives API. OpenSHMEM 2018: 90-106 - [c196]Max Grossman, Howard Pritchard, Tony Curtis, Vivek Sarkar:
HOOVER: Distributed, Flexible, and Scalable Streaming Graph Processing on OpenSHMEM. OpenSHMEM 2018: 109-124 - [c195]Prasanth Chatarasi, Vivek Sarkar:
A Preliminary Study of Compiler Transformations for Graph Applications on the Emu System. MCHPC@SC 2018: 37-44 - [c194]Fangke Ye, Markus Schordan, Chunhua Liao, Pei-Hung Lin, Ian Karlin, Vivek Sarkar:
Using Polyhedral Analysis to Verify OpenMP Applications are Data Race Free. CORRECTNESS@SC 2018: 42-50 - [c193]Sri Raj Paul, Kun Chen, Akihiro Hayashi, Max Grossman, Vivek Sarkar, Jason DeVinney, Bill Carlson:
A Unified Runtime for PGAS and Event-Driven Programming. ESPM2@SC 2018: 46-53 - [c192]Vivek Sarkar, Max Grossman, Zoran Budimlic, Shams Imam:
A One Year Retrospective on a MOOC in Parallel, Concurrent, and Distributed Programming in Java. EduHPC@SC 2018: 61-68 - [c191]Fangke Ye, Jisheng Zhao, Vivek Sarkar:
Detecting MPI usage anomalies via partial program symbolic execution. SC 2018: 63:1-63:5 - [c190]Arghya Chatterjee, Gonzalo Alvarez, Eduardo F. D'Azevedo, Wael R. Elwasif, Oscar R. Hernandez, Vivek Sarkar:
Porting DMRG++ Scientific Application to OpenPOWER. ISC Workshops 2018: 418-431 - [c189]Jisheng Zhao, Oscar R. Hernandez, Reuben D. Budiardja, M. Graham Lopez, Vivek Sarkar, Jack C. Wells:
Compile-Time Library Call Detection Using CAASCADE and XALT. ISC Workshops 2018: 440-447 - [e11]Xipeng Shen, James Tuck, Ricardo Bianchini, Vivek Sarkar:
Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2018, Williamsburg, VA, USA, March 24-28, 2018. ACM 2018, ISBN 978-1-4503-4911-6 [contents] - 2017
- [j29]Tiago Cogumbreiro, Jun Shirako, Vivek Sarkar:
Formalization of Habanero phasers using Coq. J. Log. Algebraic Methods Program. 90: 50-60 (2017) - [j28]Max Grossman, Maha Aziz, Heng Chi, Anant Tibrewal, Shams Imam, Vivek Sarkar:
Pedagogy and tools for teaching parallel computing at the sophomore undergraduate level. J. Parallel Distributed Comput. 105: 18-30 (2017) - [j27]Tiago Cogumbreiro, Rishi Surendran, Francisco Martins, Vivek Sarkar, Vasco T. Vasconcelos, Max Grossman:
Deadlock avoidance in parallel programs with futures: why parallel tasks should not wait for strangers. Proc. ACM Program. Lang. 1(OOPSLA): 103:1-103:26 (2017) - [c188]Jun Shirako, Akihiro Hayashi, Vivek Sarkar:
Optimized two-level parallelization for GPU accelerators using the polyhedral model. CC 2017: 22-33 - [c187]Vivek Sarkar, Max Grossman, Zoran Budimlic, Shams Imam:
Preparing an Online Java Parallel Computing Course. IPDPS Workshops 2017: 360-366 - [c186]Max Grossman, Vivek Kumar, Nick Vrvilo, Zoran Budimlic, Vivek Sarkar:
A Pluggable Framework for Composable HPC Scheduling Libraries. IPDPS Workshops 2017: 723-732 - [c185]Nick Vrvilo, Lechen Yu, Vivek Sarkar:
A marshalled data format for pointers in relocatable data blocks. ISMM 2017: 25-35 - [c184]Max Grossman, Joseph Doyle, James Dinan, Howard Pritchard, Kayla Seager, Vivek Sarkar:
Implementation and Evaluation of OpenSHMEM Contexts Using OFI Libfabric. OpenSHMEM 2017: 19-34 - [c183]Arghya Chatterjee, Srdan Milakovic, Bing Xue, Zoran Budimlic, Vivek Sarkar:
DAMMP: A Distributed Actor Model for Mobile Platforms. ManLang 2017: 48-59 - [c182]Max Grossman, Howard Pritchard, Zoran Budimlic, Vivek Sarkar:
Graph500 on OpenSHMEM: Using A Practical Survey of Past Work to Motivate Novel Algorithmic Developments. PAW@SC 2017: 2:1-2:8 - [c181]Akihiro Hayashi, Sri Raj Paul, Max Grossman, Jun Shirako, Vivek Sarkar:
Chapel-on-X: Exploring Tasking Runtimes for PGAS Languages. ESPM2@SC 2017: 5:1-5:8 - [c180]Gloria Y. K. Kim, Akihiro Hayashi, Vivek Sarkar:
Exploration of Supervised Machine Learning Techniques for Runtime Selection of CPU vs. GPU Execution in Java Programs. WACCPD@SC 2017: 125-144 - [e10]Vivek Sarkar, Lawrence Rauchwerger:
Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Austin, TX, USA, February 4-8, 2017. ACM 2017, ISBN 978-1-4503-4493-7 [contents] - 2016
- [j26]Dragos Sbirlea, Jun Shirako, Ryan Newton, Vivek Sarkar:
SCnC: Efficient Unification of Streaming with Dynamic Task Parallelism. Int. J. Parallel Program. 44(2): 233-256 (2016) - [j25]Max Grossman, Maurício Breternitz Jr., Vivek Sarkar:
HadoopCL2: Motivating the Design of a Distributed, Heterogeneous Programming System With Machine-Learning Applications. IEEE Trans. Parallel Distributed Syst. 27(3): 762-775 (2016) - [c179]Kumud Bhandari, Vivek Sarkar:
Tree-based Read-only Data Chunks for NVRAM Programming. DFM@PACT 2016: 2:1-2:8 - [c178]Deepak Majeti, Kuldeep S. Meel, Rajkishore Barik, Vivek Sarkar:
Automatic data layout generation and kernel mapping for CPU+GPU architectures. CC 2016: 240-250 - [c177]Max Grossman, Vivek Sarkar:
SWAT: A Programmable, In-Memory, Distributed, High-Performance Computing Platform. HPDC 2016: 81-92 - [c176]Timothy G. Mattson, Romain Cledat, Vincent Cavé, Vivek Sarkar, Zoran Budimlic, Sanjay Chatterjee, Joshua B. Fryman, Ivan Ganev, Robin Knauerhase, Min Lee, Benoît Meister, Brian Nickerson, Nick Pepperling, Bala Seshasayee, Sagnak Tasirlar, Justin Teller, Nick Vrvilo:
The Open Community Runtime: A runtime system for extreme scale computing. HPEC 2016: 1-7 - [c175]Sanjay Chatterjee, Nick Vrvilo, Zoran Budimlic, Kathleen Knobe, Vivek Sarkar:
Declarative Tuning for Locality in Parallel Programs. ICPP 2016: 452-457 - [c174]Max Grossman, Vivek Sarkar:
Efficient Checkpointing of Multi-threaded Applications as a Tool for Debugging, Performance Tuning, and Resiliency. IPDPS 2016: 232-241 - [c173]Max Grossman, Jun Shirako, Vivek Sarkar:
OpenMP as a High-Level Specification Language for Parallelism - And its use in Evaluating Parallel Programming Systems. IWOMP 2016: 141-155 - [c172]Prasanth Chatarasi, Jun Shirako, Martin Kong, Vivek Sarkar:
An Extended Polyhedral Model for SPMD Programs and Its Use in Static Data Race Detection. LCPC 2016: 106-120 - [c171]Rishi Surendran, Vivek Sarkar:
Automatic parallelization of pure method calls via conditional future synthesis. OOPSLA 2016: 20-38 - [c170]Max Grossman, Vivek Kumar, Zoran Budimlic, Vivek Sarkar:
Integrating Asynchronous Task Parallelism with OpenSHMEM. OpenSHMEM 2016: 3-17 - [c169]Arghya Chatterjee, Branko Gvoka, Bing Xue, Zoran Budimlic, Shams Imam, Vivek Sarkar:
A Distributed Selectors Runtime System for Java Applications. PPPJ 2016: 3:1-3:11 - [c168]Rishi Surendran, Vivek Sarkar:
Dynamic Determinacy Race Detection for Task Parallelism with Futures. RV 2016: 368-385 - [c167]Akihiro Hayashi, Jun Shirako, Ettore Tiotto, Robert Ho, Vivek Sarkar:
Exploring Compiler Optimization Opportunities for the OpenMP 4.× Accelerator Model on a POWER8+GPU Platform. WACCPD@SC 2016: 68-78 - [c166]Vivek Kumar, Karthik Murthy, Vivek Sarkar, Yili Zheng:
Optimized Distributed Work-Stealing. IA3@SC 2016: 74-77 - [c165]Yuhan Peng, Max Grossman, Vivek Sarkar:
Static Cost Estimation for Data Layout Selection on GPUs. PMBS@SC 2016: 76-86 - [c164]Matthew Francis-Landau, Bing Xue, Jason Eisner, Vivek Sarkar:
Fine-Grained Parallelism in Probabilistic Parsing with Habanero Java. IA3@SC 2016: 78-81 - [c163]Martin Kong, Louis-Noël Pouchet, P. Sadayappan, Vivek Sarkar:
PIPES: a language and compiler for task-based programming on distributed-memory clusters. SC 2016: 456-467 - [c162]Rishi Surendran, Vivek Sarkar:
Brief Announcement: Dynamic Determinacy Race Detection for Task Parallelism with Futures. SPAA 2016: 95-97 - [c161]Tiago Cogumbreiro, Jun Shirako, Vivek Sarkar:
Formalization of Phase Ordering. PLACES 2016: 13-24 - [e9]Vishakha Gupta-Cledat, Donald E. Porter, Vivek Sarkar:
Proceedings of the 12th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, Atlanta, GA, USA, April 2-3, 2016. ACM 2016, ISBN 978-1-4503-3947-6 [contents] - [i3]Max Grossman, Christopher Thiele, Mauricio Araya-Polo, Florian Frank, Faruk O. Alpak, Vivek Sarkar:
A survey of sparse matrix-vector multiplication performance on large matrices. CoRR abs/1608.00636 (2016) - 2015
- [j24]Shams Imam, Vivek Sarkar:
The Eureka Programming Model for Speculative Task Parallelism (Artifact). Dagstuhl Artifacts Ser. 1(1): 06:1-06:2 (2015) - [j23]Peter Anderson, Nick Vrvilo, Eric Mercer, Vivek Sarkar:
JPF Verification of Habanero Java Programs using Gradual Type Permission Regions. ACM SIGSOFT Softw. Eng. Notes 40(1): 1-5 (2015) - [c160]