Can parallel data structures rely on automatic memory managers?

2012 ◽  
Author(s):  
Erez Petrank
Keyword(s):  
Data Structures ◽  
Parallel Data ◽  
Automatic Memory

3D Printing Complex Structures Using Modeling and Simulation

2015 ◽  
Author(s):  
Hammad Mazhar
Keyword(s):  
3D Printing ◽  
Open Source ◽  
Data Structures ◽  
Large Scale ◽  
Selective Layer ◽  
Parallel Data ◽  
Wide Range ◽  
Data Structures And Algorithms ◽  
Multi Body ◽  
Dynamics Problems

This paper describes an open source parallel simulation framework capable of simulating large-scale granular and multi-body dynamics problems. This framework, called Chrono::Parallel, builds upon the modeling capabilities of Chrono::Engine, another open source simulation package, and leverages parallel data structures to enable scalable simulation of large problems. Chrono::Parallel is somewhat unique in that it was designed from the ground up to leverage parallel data structures and algorithms so that it scales across a wide range of computer architectures and yet has a rich modeling capability for simulating many different types of problems. The modeling capabilities of Chrono::Parallel will be demonstrated in the context of additive manufacturing and 3D printing by modeling the Selective Layer Sintering layering process and simulating large complex interlocking structures which require compression and folding to fit into a 3D printer’s build volume.

Abstractions and Middleware for Petascale Computing and Beyond

2012 ◽  
pp. 161-178
Author(s):  
Ivo F. Sbalzarini
Keyword(s):  
Numerical Simulations ◽  
High Performance Computing ◽  
Data Structures ◽  
High Performance ◽  
Source Code ◽  
Limiting Factors ◽  
Communication Overhead ◽  
Parallel Data ◽  
Petascale Computing ◽  
Performance Computing

As high-performance computing moves to the petascale and beyond, a number of algorithmic and software challenges need to be addressed. This paper reviews the main performance-limiting factors in today’s high-performance computing software and outlines a possible new programming paradigm to address them. The proposed paradigm is based on abstract parallel data structures and operations that encapsulate much of the complexity of an application, but still make communication overhead explicit. The authors argue that all numerical simulations can be formulated in terms of the presented abstractions, which thus define an abstract semantic specification language for parallel numerical simulations. Simulations defined in this language can automatically be translated to source code containing the appropriate calls to a middleware that implements the underlying abstractions. Finally, the structure and functionality of such a middleware are outlined while demonstrating its feasibility on the example of the parallel particle-mesh library (PPM).

HCL: Distributing Parallel Data Structures in Extreme Scales

2020 ◽  
Author(s):  
Hariharan Devarajan ◽  
Anthony Kougkas ◽  
Keith Bateman ◽  
Xian-He Sun
Keyword(s):  
Data Structures ◽  
Parallel Data
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