DocumentCode :
2200035
Title :
SMART: a neurocomputer using sparse matrices
Author :
Lawson, J.C. ; Maria, N. ; Hérault, J.
Author_Institution :
Inst. Nat. Polytech. de Grenoble, France
fYear :
1993
fDate :
27-29 Jan 1993
Firstpage :
59
Lastpage :
64
Abstract :
SMART (Sparse Matrix Adaptive Recursive Transforms) is a new architecture supporting sparse matrix transforms. Though it is primarily designed for neural network simulations, the approach used is general enough to encompass other domains (e.g. signal processing). SMART efficiently implements algorithms that use a vectorial formalism. A simple sparse matrix compaction procedure is given which parallelizes computations thanks to dedicated data structures. Using this architecture, we design a vector processor that interfaces with a host machine which is thus relieved from intensive computational tasks
Keywords :
data structures; digital simulation; matrix algebra; neural nets; parallel architectures; signal processing; transforms; vector processor systems; SMART; Sparse Matrix Adaptive Recursive Transforms; computation parallelization; dedicated data structures; host machine interfacing; intensive computational tasks; neural network simulations; neurocomputer architecture; signal processing; sparse matrix compaction procedure; vector processor; vectorial formalism; Adaptive signal processing; Compaction; Computational modeling; Computer architecture; Concurrent computing; Data structures; Neural networks; Signal design; Signal processing algorithms; Sparse matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing, 1993. Proceedings. Euromicro Workshop on
Conference_Location :
Gran Canaria
Print_ISBN :
0-8186-3610-6
Type :
conf
DOI :
10.1109/EMPDP.1993.336420
Filename :
336420
Link To Document :
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