no code implementations • 8 Feb 2024 • Bibrak Qamar Chandio, Prateek Srivastava, Maciej Brodowicz, Martin Swany, Thomas Sterling
The paper provides a unified co-design of 1) a programming and execution model that allows spawning tasks from within the vertex data at runtime, 2) language constructs for \textit{actions} that send work to where the data resides, combining parallel expressiveness of local control objects (LCOs) to implement asynchronous graph processing primitives, 3) and an innovative vertex-centric data-structure, using the concept of Rhizomes, that parallelizes both the out and in-degree load of vertex objects across many cores and yet provides a single programming abstraction to the vertex objects.
no code implementations • 1 Jul 2019 • Bruno Magalhães, Michael Hines, Thomas Sterling, Felix Schuermann
However, simulations driven by stiff dynamics or a wide range of time scales - such as multiscale simulations of neural networks - struggle with fixed step interpolation methods, yielding excessive computation of intervals of quasi-constant activity, inaccurate interpolation of periods of high volatility solution, and being incapable of handling unknown or distinct time constants.
no code implementations • 14 Jul 2018 • Jeremy Kepner, Ron Brightwell, Alan Edelman, Vijay Gadepally, Hayden Jananthan, Michael Jones, Sam Madden, Peter Michaleas, Hamed Okhravi, Kevin Pedretti, Albert Reuther, Thomas Sterling, Mike Stonebraker
In this context, an operating system can be viewed as software that brokers and tracks the resources of the compute engines and is akin to a database management system.
Distributed, Parallel, and Cluster Computing Databases Operating Systems Performance
