Enhancing Muesli's Data Parallel Skeletons for Multi-core Computer Architectures

Author(s):  
P Ciechanowicz ◽  
H Kuchen
Author(s):  
Jörg Fischer ◽  
Sergei Gorlatch ◽  
Holger Bischof

2002 ◽  
Vol 12 (02) ◽  
pp. 141-155 ◽  
Author(s):  
HERBERT KUCHEN ◽  
MURRAY COLE

We describe a skeletal parallel programming library which integrates task and data parallel constructs within an API for C++. Traditional skeletal requirements for higher orderness and polymorphism are achieved through exploitation of operator overloading and templates, while the underlying parallelism is provided by MPI. We present a case study describing two algorithms for the travelling salesman problem.


2008 ◽  
Vol 18 (01) ◽  
pp. 117-131 ◽  
Author(s):  
MICHAEL POLDNER ◽  
HERBERT KUCHEN

Algorithmic skeletons intend to simplify parallel programming by providing a higher level of abstraction compared to the usual message passing. Task and data parallel skeletons can be distinguished. In the present paper, we will consider several approaches to implement one of the most classical task parallel skeletons, namely the farm, and compare them w.r.t. scalability, overhead, potential bottlenecks, and load balancing. We will also investigate several communication modes for the implementation of skeletons. Based on experimental results, the advantages and disadvantages of the different approaches are shown. Moreover, we will show how to terminate the system of processes properly.


2012 ◽  
Vol 9 ◽  
pp. 1817-1826 ◽  
Author(s):  
Herbert Kuchen ◽  
Steffen Ernsting

Author(s):  
Jose-Maria Carazo ◽  
I. Benavides ◽  
S. Marco ◽  
J.L. Carrascosa ◽  
E.L. Zapata

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.


AIAA Journal ◽  
1998 ◽  
Vol 36 ◽  
pp. 1603-1609 ◽  
Author(s):  
Michael J. Wright ◽  
Graham V. Candler ◽  
Deepak Bose

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