%0 Conference Paper %B 2020 IEEE/ACM 5th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2) %D 2020 %T The Template Task Graph (TTG) - An Emerging Practical Dataflow Programming Paradigm for Scientific Simulation at Extreme Scale %A George Bosilca %A Robert Harrison %A Thomas Herault %A Mohammad Mahdi Javanmard %A Poornima Nookala %A Edward Valeev %K dag %K dataflow %K exascale %K graph %K High-performance computing %K workflow %X We describe TESSE, an emerging general-purpose, open-source software ecosystem that attacks the twin challenges of programmer productivity and portable performance for advanced scientific applications on modern high-performance computers. TESSE builds upon and extends the ParsecDAG/-dataflow runtime with a new Domain Specific Languages (DSL) and new integration capabilities. Motivating this work is our belief that such a dataflow model, perhaps with applications composed in domain specific languages, can overcome many of the challenges faced by a wide variety of irregular applications that are poorly served by current programming and execution models. Two such applications from many-body physics and applied mathematics are briefly explored. This paper focuses upon the Template Task Graph (TTG), which is TESSE's main C++ Api that provides a powerful work/data-flow programming model. Algorithms on spatial trees, block-sparse tensors, and wave fronts are used to illustrate the API and associated concepts, as well as to compare with related approaches. %B 2020 IEEE/ACM 5th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2) %I IEEE %8 2020-11 %G eng %R https://doi.org/10.1109/ESPM251964.2020.00011 %0 Generic %D 2018 %T Tensor Contraction on Distributed Hybrid Architectures using a Task-Based Runtime System %A George Bosilca %A Damien Genet %A Robert Harrison %A Thomas Herault %A Mohammad Mahdi Javanmard %A Chong Peng %A Edward Valeev %X The needs for predictive simulation of electronic structure in chemistry and materials science calls for fast/reduced-scaling formulations of quantum n-body methods that replace the traditional dense tensors with element-, block-, rank-, and block-rank-sparse (data-sparse) tensors. The resulting, highly irregular data structures are a poor match to imperative, bulk-synchronous parallel programming style due to the dynamic nature of the problem and to the lack of clear domain decomposition to guarantee a fair load-balance. TESSE runtime and the associated programming model aim to support performance-portable composition of applications involving irregular and dynamically changing data. In this paper we report an implementation of irregular dense tensor contraction in a paradigmatic electronic structure application based on the TESSE extension of PaRSEC, a distributed hybrid task runtime system, and analyze the resulting performance on a distributed memory cluster of multi-GPU nodes. Unprecedented strong scaling and promising efficiency indicate a viable future for task-based programming of complete production-quality reduced scaling models of electronic structure. %B Innovative Computing Laboratory Technical Report %I University of Tennessee %8 2018-12 %G eng