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Aladin Kamel

dblp:11/1910 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2012
0000-0003-0199-4281ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 1 first-authorArtificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 50% Parallel and multicore computing · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
High-performance computing
scientific computing systems
0.011990
Large-scale computing on clustered vector multiprocessors · SC 1990
Parallel and multicore computing › parallelization strategies
two-level parallelism
0.011990
Large-scale computing on clustered vector multiprocessors · SC 1990

Methods — techniques the papers use, named apart from their topics

clustered fortran · 0.0
YearPublicationVenuePosition
2012 Magnetic gradient and neutron backscattering fusion for landmine detection
Mohamed Elkattan, Ahmed M. Osman, Aladin Kamel, Hadia M. El-Hennawy
FUSION4
1990 Elastodynamics on clustered vector multiprocessors
abstract
We present the parallelization of an elastodynamic code on a firmly coupled configuration consisting of two IBM 3090-600 VF, a total of 12 processors, joined with a connection facility. The programming environment used is Clustered FORTRAN which is a facility for writing and executing parallel programs on two coupled IBM 3090 vector multiprocessors (VMP). Clustered FORTRAN provides extensions to FORTRAN so that a single application program can execute across multiple 3090 systems as well as across the processors of a single 3090 system. To exploit parallelism on each VMP, we used the parallel DO LOOP construct and to exploit parallelism across VMP we used the SCHEDULE statement allowing concurrent execution of subprograms. It is shown that such a problem, characterized by sufficiently large amounts of arithmetic operations within the parallel tasks, can be efficiently parallelized obtaining average speed-ups of more than five on one 3090-600 VF and nearly ten on a two 3090-600 VF cluster with a small programming effort.
Vittorio Zecca, Aladin Kamel
ICS2
1990 Large-scale computing on clustered vector multiprocessors
abstract
A two-level parallel implementation of a large-scale geophysical simulation code is presented. The software/hardware environment utilizes IBM Clustered Fortran, allowing a single application program to execute concurrently on two IBM 3090 computers (first level of parallelism) while exploiting the multiple vector processors of each 3090 system (second level of parallelism). The experiments reported show that the problem is characterized by large task granularity and small communication/computation ratio, thus leading to sustained parallel speed-ups of nearly ten on a cluster of two 3090 computers, totalling twelve vector processors.>
Aladin Kamel, Piero Sguazzero, Vittorio Zecca
SC1
1990 Arabic character recognition system: A statistical approach for recognizing cursive typewritten text
Sherif Sami El-Dabi, Refat Ramsis, Aladin Kamel
Pattern Recognit.3