Using a" codelet" program execution model for exascale machines: position paper S Zuckerman, J Suetterlein, R Knauerhase, GR Gao Proceedings of the 1st International Workshop on Adaptive Self-Tuning …, 2011 | 151 | 2011 |
Using a" codelet" program execution model for exascale machines: position paper S Zuckerman, J Suetterlein, R Knauerhase, GR Gao Proceedings of the 1st International Workshop on Adaptive Self-Tuning …, 2011 | 151 | 2011 |
Toward an execution model for extreme-scale systems-runnemede and beyond GR Gao, J Suetterlein, S Zuckerman Technical Memo, 2011 | 32 | 2011 |
Mapa: Multi-accelerator pattern allocation policy for multi-tenant gpu servers K Ranganath, JD Suetterlein, JB Manzano, SL Song, D Wong Proceedings of the International Conference for High Performance Computing …, 2021 | 16 | 2021 |
Application characterization at scale: lessons learned from developing a distributed open community runtime system for high performance computing J Landwehr, J Suetterlein, A Márquez, J Manzano, GR Gao Proceedings of the ACM International Conference on Computing Frontiers, 164-171, 2016 | 14 | 2016 |
Position paper: Using a codelet program execution model for exascale machines S Zuckerman, J Suetterlein, R Knauerhase, GR Gao EXADAPT Workshop 10 (2000417.2000424), 2011 | 12 | 2011 |
DARTS: a runtime based on the Codelet execution model J Suetterlein University of Delaware, 2014 | 11 | 2014 |
Extending the roofline model for asynchronous many-task runtimes JD Suetterlein, J Landwehr, A Marquez, J Manzano, GR Gao 2016 IEEE International Conference on Cluster Computing (CLUSTER), 493-496, 2016 | 9 | 2016 |
Automatic locality exploitation in the codelet model C Chen, Y Wu, J Suetterlein, L Zheng, M Guo, GR Gao 2013 12th IEEE International Conference on Trust, Security and Privacy in …, 2013 | 9 | 2013 |
Asynchronous runtimes in action: An introspective framework for a next gen runtime J Suetterlein, J Landwehr, A Márquez, JB Manzano, GR Gao 2016 IEEE International Parallel and Distributed Processing Symposium …, 2016 | 8 | 2016 |
Designing scalable distributed memory models: A case study J Landwehr, J Suetterlein, J Manzano, A Marquez, KJ Barker, GR Gao Proceedings of the Computing Frontiers Conference, 174-182, 2017 | 7 | 2017 |
TAZeR: Hiding the cost of remote I/O in distributed scientific workflows J Suetterlein, RD Friese, NR Tallent, M Schram 2019 IEEE International Conference on Big Data (Big Data), 383-394, 2019 | 6 | 2019 |
CAPSL Technical Memo 104: Toward an Execution Model for Extreme-Scale Systems-Runnemede and Beyond G Gao, J Suetterlein, S Zuckerman April, 2011 | 6 | 2011 |
A parallel graph environment for real-world data analytics workflows VG Castellana, M Drocco, J Feo, J Firoz, T Kanewala, A Lumsdaine, ... 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2019 | 5 | 2019 |
Effectively using remote I/O for work composition in distributed workflows RD Friese, BO Mutlu, NR Tallent, J Suetterlein, J Strube 2020 IEEE International Conference on Big Data (Big Data), 426-433, 2020 | 4 | 2020 |
A case for asynchronous many task runtimes: a modeling approach for high performance computing and Big Data analytics J Suetterlein University of Delaware, 2017 | 3 | 2017 |
Lc-memento: A memory model for accelerated architectures K Ranganath, J Firoz, J Suetterlein, J Manzano, A Marquez, M Raugas, ... International Workshop on Languages and Compilers for Parallel Computing, 67-82, 2021 | 2 | 2021 |
Toward a unified hpc and big data runtime J Suetterlein, J Landwehr, JF Manzano, A Marquez STREAM Workshop, 2015 | 2 | 2015 |
Extending an asynchronous runtime system for high throughput applications: A case study J Suetterlein, J Manzano, A Marquez, GR Gao Journal of Parallel and Distributed Computing 163, 214-231, 2022 | 1 | 2022 |
Hardware Evaluation Analytical Modeling and Node Simulation: Benefits of Tighter GPU Integration B Austin, R Bair, K Barker, A Cabrera, A Chien, N Ding, J Firoz, K Ibrahim, ... | 1 | 2021 |