scholarly journals DDT: A Research Tool for Automatic Data Distribution in High Performance Fortran

1997 ◽  
Vol 6 (1) ◽  
pp. 73-94 ◽  
Author(s):  
Eduard AyguadÉ ◽  
Jordi Garcia ◽  
MercÉ GironÈs ◽  
M. Luz Grande ◽  
JesÚs Labarta
Keyword(s):  
High Performance ◽  
Data Distribution ◽  
Control Flow ◽  
Research Tool ◽  
Automatic Data ◽  
Computation Cost ◽  
Data Movement ◽  
High Performance Fortran ◽  
Automatic Data Distribution ◽  
The Cost

This article describes the main features and implementation of our automatic data distribution research tool. The tool (DDT) accepts programs written in Fortran 77 and generates High Performance Fortran (HPF) directives to map arrays onto the memories of the processors and parallelize loops, and executable statements to remap these arrays. DDT works by identifying a set of computational phases (procedures and loops). The algorithm builds a search space of candidate solutions for these phases which is explored looking for the combination that minimizes the overall cost; this cost includes data movement cost and computation cost. The movement cost reflects the cost of accessing remote data during the execution of a phase and the remapping costs that have to be paid in order to execute the phase with the selected mapping. The computation cost includes the cost of executing a phase in parallel according to the selected mapping and the owner computes rule. The tool supports interprocedural analysis and uses control flow information to identify how phases are sequenced during the execution of the application.

scholarly journals Automatic Data Distribution for Composite Grid Applications

1997 ◽  
Vol 6 (1) ◽  
pp. 95-113 ◽  
Author(s):  
Lorie M. Liebrock ◽  
Ken Kennedy
Keyword(s):  
Large Class ◽  
High Performance ◽  
Nuclear Reactor ◽  
Data Distribution ◽  
Fortran Program ◽  
Simulation Code ◽  
Automatic Data ◽  
Automatic Data Distribution ◽  
Grid Applications ◽  
Composite Grid

Problem topology is the key to efficient parallelization support for partially regular applications. Specifically, problem topology provides the information necessary for automatic data distribution and regular application optimization of a large class of partially regular applications. Problem topology is the connectivity of the problem. This research focuses on composite grid applications and strives to take advantage of their partial regularity in the parallelization and compilation process. Composite grid problems arise in important application areas, e.g., reactor and aerodynamic simulation. Related physical phenomena are inherently parallel and their simulations are computationally intensive. We present algorithms that automatically determine data distributions for composite grid problems. Our algorithm's alignment and distribution specifications may be used as input to a High Performance Fortran program to apply the mapping for execution of the simulation code. These algorithms eliminate the need for user-specified data distribution for this large class of complex topology problems. We test the algorithms using a number of topological descriptions from aerodynamic and water-cooled nuclear reactor simulations. Speedup-bound predictions with and without communication, based on the automatically generated distributions, indicate that significant speedups are possible using these algorithms.

Data redistribution in an automatic data distribution tool

1996 ◽  
pp. 407-421 ◽  
Author(s):  
Eduard Ayguadé ◽  
Jordi Garcia ◽  
Mercè Gironès ◽  
M. Luz Grande ◽  
Jesús Labarta
Keyword(s):  
Data Distribution ◽  
Automatic Data ◽  
Automatic Data Distribution ◽  
Data Redistribution

scholarly journals Kemari: A Portable High Performance Fortran System for Distributed Memory Parallel Processors

1997 ◽  
Vol 6 (1) ◽  
pp. 41-58 ◽  
Author(s):  
T. Kamachi ◽  
A. MÜller ◽  
R. RÜhl ◽  
Y. Seo ◽  
K. Suehiro ◽  
...  
Keyword(s):  
Message Passing ◽  
High Performance ◽  
Message Passing Interface ◽  
Data Distribution ◽  
Programming Environment ◽  
Performance Measurements ◽  
High Performance Fortran ◽  
Additional Control ◽  
Compilation Process ◽  
Structured Problems

We have developed a compilation system which extends High Performance Fortran (HPF) in various aspects. We support the parallelization of well-structured problems with loop distribution and alignment directives similar to HPF's data distribution directives. Such directives give both additional control to the user and simplify the compilation process. For the support of unstructured problems, we provide directives for dynamic data distribution through user-defined mappings. The compiler also allows integration of message-passing interface (MPI) primitives. The system is part of a complete programming environment which also comprises a parallel debugger and a performance monitor and analyzer. After an overview of the compiler, we describe the language extensions and related compilation mechanisms in detail. Performance measurements demonstrate the compiler's applicability to a variety of application classes.

scholarly journals Visualization of Distributed Data Structures for High Performance Fortran-Like Languages

1997 ◽  
Vol 6 (1) ◽  
pp. 115-126 ◽  
Author(s):  
Rainer Koppler ◽  
Siegfried Grabner ◽  
Jens Volkert
Keyword(s):  
Data Structures ◽  
Load Distribution ◽  
High Performance ◽  
Data Distribution ◽  
Distributed Data ◽  
Visualization Tool ◽  
Efficient Utilization ◽  
Distributed Data Structures ◽  
High Performance Fortran

This article motivates the usage of graphics and visualization for efficient utilization of High Performance Fortran's (HPF's) data distribution facilities. It proposes a graphical toolkit consisting of exploratory and estimation tools which allow the programmer to navigate through complex distributions and to obtain graphical ratings with respect to load distribution and communication. The toolkit has been implemented in a mapping design and visualization tool which is coupled with a compilation system for the HPF predecessor Vienna Fortran. Since this language covers a superset of HPF's facilities, the tool may also be used for visualization of HPF data structures.

scholarly journals Automatic Data Distribution in Large-scale OLTP Applications

2014 ◽  
Vol 7 (4) ◽  
pp. 37-46 ◽  
Author(s):  
Xiaoyan Wang ◽  
Xu Fan ◽  
Jinchuan Chen ◽  
Xiaoyong Du
Keyword(s):  
Large Scale ◽  
Data Distribution ◽  
Automatic Data ◽  
Automatic Data Distribution

Scheduling Data Intensive Scientific Workflows in Cloud Environment Using Nature Inspired Algorithms

2019 ◽  
pp. 196-217 ◽  
Author(s):  
Shikha Mehta ◽  
Parmeet Kaur
Keyword(s):  
High Performance ◽  
Heuristic Algorithms ◽  
Control Flow ◽  
Grey Wolf ◽  
Data Intensive ◽  
Np Hard Problem ◽  
Shuffled Frog Leaping ◽  
Nature Inspired Algorithms ◽  
The Cost ◽  
Performance Computing

Workflows are a commonly used model to describe applications consisting of computational tasks with data or control flow dependencies. They are used in domains of bioinformatics, astronomy, physics, etc., for data-driven scientific applications. Execution of data-intensive workflow applications in a reasonable amount of time demands a high-performance computing environment. Cloud computing is a way of purchasing computing resources on demand through virtualization technologies. It provides the infrastructure to build and run workflow applications, which is called ‘Infrastructure as a Service.' However, it is necessary to schedule workflows on cloud in a way that reduces the cost of leasing resources. Scheduling tasks on resources is a NP hard problem and using meta-heuristic algorithms is an obvious choice for the same. This chapter presents application of nature-inspired algorithms: particle swarm optimization, shuffled frog leaping algorithm and grey wolf optimization algorithm to the workflow scheduling problem on the cloud. Simulation results prove the efficacy of the suggested algorithms.

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