scholarly journals CHRONO: a parallel multi-physics library for rigid-body, flexible-body, and fluid dynamics

2013 ◽  
Vol 4 (1) ◽  
pp. 49-64 ◽  
Author(s):  
H. Mazhar ◽  
T. Heyn ◽  
A. Pazouki ◽  
D. Melanz ◽  
A. Seidl ◽  
...  
Keyword(s):  
Parallel Computing ◽  
Large Scale ◽  
Flexible Structures ◽  
Particulate Flows ◽  
Loosely Coupled ◽  
Processing Power ◽  
Select Group ◽  
Physics Simulation ◽  
Physics Modeling ◽  
Many Core

Abstract. The last decade witnessed a manifest shift in the microprocessor industry towards chip designs that promote parallel computing. Until recently the privilege of a select group of large research centers, Teraflop computing is becoming a commodity owing to inexpensive GPU cards and multi to many-core x86 processors. This paradigm shift towards large scale parallel computing has been leveraged in CHRONO, a freely available C++ multi-physics simulation package. CHRONO is made up of a collection of loosely coupled components that facilitate different aspects of multi-physics modeling, simulation, and visualization. This contribution provides an overview of CHRONO::Engine, CHRONO::Flex, CHRONO::Fluid, and CHRONO::Render, which are modules that can capitalize on the processing power of hundreds of parallel processors. Problems that can be tackled in CHRONO include but are not limited to granular material dynamics, tangled large flexible structures with self contact, particulate flows, and tracked vehicle mobility. The paper presents an overview of each of these modules and illustrates through several examples the potential of this multi-physics library.

Research on highly parallel embedded control system design and implementation method

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 44-46
Author(s):  
Masato Edahiro ◽  
Masaki Gondo
Keyword(s):  
Computer Architecture ◽  
Intelligent Systems ◽  
Large Scale ◽  
General Purpose ◽  
Heterogeneous Structure ◽  
Single Chip ◽  
Powertrain Control ◽  
Processing Power ◽  
Hardware Description ◽  
Many Core

The pace of technology's advancements is ever-increasing and intelligent systems, such as those found in robots and vehicles, have become larger and more complex. These intelligent systems have a heterogeneous structure, comprising a mixture of modules such as artificial intelligence (AI) and powertrain control modules that facilitate large-scale numerical calculation and real-time periodic processing functions. Information technology expert Professor Masato Edahiro, from the Graduate School of Informatics at the Nagoya University in Japan, explains that concurrent advances in semiconductor research have led to the miniaturisation of semiconductors, allowing a greater number of processors to be mounted on a single chip, increasing potential processing power. 'In addition to general-purpose processors such as CPUs, a mixture of multiple types of accelerators such as GPGPU and FPGA has evolved, producing a more complex and heterogeneous computer architecture,' he says. Edahiro and his partners have been working on the eMBP, a model-based parallelizer (MBP) that offers a mapping system as an efficient way of automatically generating parallel code for multi- and many-core systems. This ensures that once the hardware description is written, eMBP can bridge the gap between software and hardware to ensure that not only is an efficient ecosystem achieved for hardware vendors, but the need for different software vendors to adapt code for their particular platforms is also eliminated.

High Performance Computing Design by Code Migration for Distributed Desktop Computing Grids

2013 ◽  
pp. 185-203
Author(s):  
Makoto Yoshida ◽  
Kazumine Kojima
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Workload Management ◽  
Transfer Policy ◽  
Loosely Coupled ◽  
Design Methodologies ◽  
Processing Power ◽  
Network Delays ◽  
Desktop Computing ◽  
Code Migration

Large scale loosely coupled PCs can organize clusters and form desktop computing grids on sharing each processing power; power of PCs, transaction distributions, network scales, network delays, and code migration algorithms characterize the performance of the computing grids. This article describes the design methodologies of workload management in distributed desktop computing grids. Based on the code migration experiments, transfer policy for computation was determined and several simulations for location policies were examined, and the design methodologies for distributed desktop computing grids are derived from the simulation results. The language for distributed desktop computing is designed to accomplish the design methodologies.

High Performance Computing Design by Code Migration for Distributed Desktop Computing Grids

2011 ◽  
Vol 3 (4) ◽  
pp. 53-70
Author(s):  
Makoto Yoshida ◽  
Kazumine Kojima
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Workload Management ◽  
Transfer Policy ◽  
Loosely Coupled ◽  
Design Methodologies ◽  
Processing Power ◽  
Network Delays ◽  
Desktop Computing ◽  
Code Migration

Large scale loosely coupled PCs can organize clusters and form desktop computing grids on sharing each processing power; power of PCs, transaction distributions, network scales, network delays, and code migration algorithms characterize the performance of the computing grids. This article describes the design methodologies of workload management in distributed desktop computing grids. Based on the code migration experiments, transfer policy for computation was determined and several simulations for location policies were examined, and the design methodologies for distributed desktop computing grids are derived from the simulation results. The language for distributed desktop computing is designed to accomplish the design methodologies.

Chrono: A Parallel Physics Library for Rigid-Body, Flexible-Body, and Fluid Dynamics

2013 ◽  
Author(s):  
Toby Heyn ◽  
Hammad Mazhar ◽  
Arman Pazouki ◽  
Daniel Melanz ◽  
Andrew Seidl ◽  
...  
Keyword(s):  
Parallel Computing ◽  
Rigid Body ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Gpu Computing ◽  
Rigid Bodies ◽  
Flexible Body ◽  
Simulation Engine ◽  
Physics Simulation ◽  
Flexible Body Dynamics

This contribution discusses a multi-physics simulation engine, called Chrono, that relies heavily on parallel computing. Chrono aims at simulating the dynamics of systems containing rigid bodies, flexible (compliant) bodies, and fluid-rigid body interaction. To this end, it relies on five modules: equation formulation (modeling), equation solution (simulation), collision detection support, domain decomposition for parallel computing, and post-processing analysis with emphasis on high quality rendering/visualization. For each component we point out how parallel CPU and/or GPU computing have been leveraged to allow for the simulation of applications with millions of degrees of freedom such as rover dynamics on granular terrain, fluid-structure interaction problems, or large-scale flexible body dynamics with friction and contact for applications in polymer analysis.

Thermal-Scalable 3D Parallel-Heat-Sinking Integration Methodology: Key SoC Technology for Large-Scale Parallel Computing

2011 ◽  
Vol 34 (4) ◽  
pp. 717-728
Author(s):  
Zu-Ying LUO ◽  
Yin-He HAN ◽  
Guo-Xing ZHAO ◽  
Xian-Chuan YU ◽  
Ming-Quan ZHOU
Keyword(s):  
Parallel Computing ◽  
Large Scale ◽  
Heat Sinking

scholarly journals A Survey on Edge Performance Benchmarking

2021 ◽  
Vol 54 (3) ◽  
pp. 1-33
Author(s):  
Blesson Varghese ◽  
Nan Wang ◽  
David Bermbach ◽  
Cheol-Ho Hong ◽  
Eyal De Lara ◽  
...  
Keyword(s):  
Large Scale ◽  
Future Internet ◽  
Coupled Systems ◽  
Operational Conditions ◽  
Loosely Coupled ◽  
Performance Benchmarking ◽  
The Past ◽  
Geographically Dispersed ◽  
Tightly Coupled ◽  
History Of

Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. Therefore, it is envisioned that a large-scale, geographically dispersed, and resource-rich distributed system will emerge and play a key role in the future Internet. However, given the loosely coupled nature of such complex systems, their operational conditions are expected to change significantly over time. In this context, the performance characteristics of such systems will need to be captured rapidly, which is referred to as performance benchmarking, for application deployment, resource orchestration, and adaptive decision-making. Edge performance benchmarking is a nascent research avenue that has started gaining momentum over the past five years. This article first reviews articles published over the past three decades to trace the history of performance benchmarking from tightly coupled to loosely coupled systems. It then systematically classifies previous research to identify the system under test, techniques analyzed, and benchmark runtime in edge performance benchmarking.

THE CONNECTION MACHINE IN A UNIVERSITY ENVIRONMENT: GESAMTHOCHSCHULE WUPPERTAL

1993 ◽  
Vol 04 (01) ◽  
pp. 137-141
Author(s):  
KLAUS SCHILLING
Keyword(s):  
Parallel Computing ◽  
Computer Science ◽  
Large Scale ◽  
Early History ◽  
Short Account ◽  
University Environment ◽  
Connection Machine ◽  
The University

A short account is presented on the early history, the intentions and the development of large scale parallel computing at the University of Wuppertal. It might serve as an illustration how common activities between computational and computer science can be stimulated, in the university environment.

Sign in / Sign up

Export Citation Format

Share Document