Abstractions and Middleware for Petascale Computing and Beyond

2012 ◽  
pp. 1998-2015
Author(s):  
Ivo F. Sbalzarini

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).

Author(s):  
Ivo F. Sbalzarini

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).


Author(s):  
Ivo F. Sbalzarini

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).


Author(s):  
Italo Epicoco ◽  
Silvia Mocavero ◽  
Andrew R Porter ◽  
Stephen M Pickles ◽  
Mike Ashworth ◽  
...  

This work describes the introduction of a second level of parallelism based on the OpenMP shared memory paradigm to NEMO, one of the most widely used ocean models in the European climate community. Although the existing parallelisation scheme in NEMO, based on the MPI paradigm, has served it well for many years, it is becoming unsuited to current high-performance computing architectures due to their increasing tendency to have fat nodes containing tens of compute cores. Three different parallel approaches for introducing OpenMP are presented, discussed and compared on several platforms. Finally we have also considered the effect on performance of the data layout employed in NEMO.


Author(s):  
Al Geist ◽  
Daniel A Reed

Commodity clusters revolutionized high-performance computing when they first appeared two decades ago. As scale and complexity have grown, new challenges in reliability and systemic resilience, energy efficiency and optimization and software complexity have emerged that suggest the need for re-evaluation of current approaches. This paper reviews the state of the art and reflects on some of the challenges likely to be faced when building trans-petascale computing systems, using insights and perspectives drawn from operational experience and community debates.


Author(s):  
Edgar Gabriel

This chapter discusses runtime adaption techniques targeting high-performance computing applications. In order to exploit the capabilities of modern high-end computing systems, applications and system software have to be able to adapt their behavior to hardware and application characteristics. Using the Abstract Data and Communication Library (ADCL) as the driving example, the chapter shows the advantage of using adaptive techniques to exploit characteristics of the network and of the application. This allows to reduce the execution time of applications significantly and to avoid having to maintain different architecture dependent versions of the source code.


2017 ◽  
Vol 17 (5) ◽  
pp. 37-48
Author(s):  
Ivelina Georgieva ◽  
Georgi Gadzhev ◽  
Kostadin Ganev ◽  
Dimitrios Melas ◽  
Tijian Wang

Abstract Some extensive numerical simulations of the atmospheric composition fields in Bulgaria and Sofia have been recently performed. The US EPA Model-3 system was chosen as а modeling tool. A very extensive database was created from simulations which was used for different studies of the atmospheric composition, including the Air Quality (AQ) climate.


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