NDLI: A modified method of calculating High Dimensional Model Representation (HDMR) Terms for parallelization with MPI and CUDA

Content Provider	Springer Nature Link
Author	Kanal, M. E. Demiralp, M.
Copyright Year	2011
Abstract	If the values of a multivariate function f(x $_{1}$,x $_{2}$,…,x $_{ N }$) are given at only a finite number of points in the space of its arguments and an interpolation which employs continuous functions is considered standard multivariate routines may become cumbersome as the dimensionality grows. This urges us to develop a divide-and-conquer algorithm which approximates the function. The given multivariate data are partitioned into low-variate data. This approach is called High Dimensional Model Representation (HDMR). However, the method in its current form is not applicable to problems having huge volumes of data. With the increasing dimension number and the number of the corresponding nodes, the volume of data in question reaches such a high level that it is beyond the capacity of any individual PC because huge volume of data requires much higher RAM capacity. Another aspect is that the structure of equalities used in the calculation of HDMR terms varies according to the dimension number of the problem. The number of loops in the algorithm increases with the increasing dimension number. In this work, as a first step, the equations used are modified in such a way that their structure does not depend on the dimension number. With the newly obtained equalities, the method becomes appropriate for parallelization. Due to the parallelization, the RAM problem arising from problems with high volume of data is solved. Finally, the performance of the parallelized method is analyzed.
Starting Page	199
Ending Page	213
Page Count	15
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	62
Issue Number	1
e-ISSN	15730484
Language	English
Publisher	Springer US
Publisher Date	2011-09-28
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Parallel algorithms Data partitioning Multivariate interpolation MPI programming CUDA programming Computer Science Programming Languages, Compilers, Interpreters Processor Architectures
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Analysis of scalable data-privatization threading algorithms for hybrid MPI/OpenMP parallelization of molecular dynamics

Concurrent programming constructs for parallel MPI applications : The MPI threads library

Hierarchical redesign of classic MPI reduction algorithms

Exploitation of a parallel clustering algorithm on commodity hardware with P2P-MPI

Neville elimination on multi- and many-core systems: OpenMP, MPI and CUDA

Coarse-Grained Parallel Algorithms for Multi-Dimensional Wavelet Transforms

Dynamic-CoMPI: dynamic optimization techniques for MPI parallel applications

Raising the level of abstraction for developing message passing applications

Highly scalable implementation of an implicit matrix-free solver for gas dynamics on GPU-accelerated clusters

A modified method of calculating High Dimensional Model Representation (HDMR) Terms for parallelization with MPI and CUDA

Similar Documents

Analysis of scalable data-privatization threading algorithms for hybrid MPI/OpenMP parallelization of molecular dynamics

Concurrent programming constructs for parallel MPI applications : The MPI threads library

Hierarchical redesign of classic MPI reduction algorithms

Exploitation of a parallel clustering algorithm on commodity hardware with P2P-MPI

Neville elimination on multi- and many-core systems: OpenMP, MPI and CUDA

Coarse-Grained Parallel Algorithms for Multi-Dimensional Wavelet Transforms

Dynamic-CoMPI: dynamic optimization techniques for MPI parallel applications

Raising the level of abstraction for developing message passing applications

Highly scalable implementation of an implicit matrix-free solver for gas dynamics on GPU-accelerated clusters

A modified method of calculating High Dimensional Model Representation (HDMR) Terms for parallelization with MPI and CUDA