A compiler method for the parallel execution of irregular reductions in scalable shared memory multiprocessors

2000 ◽  
Author(s):  
E. Gutiérrez ◽  
O. Plata ◽  
E. L. Zapata
Keyword(s):  
Shared Memory ◽  
Parallel Execution ◽  
Shared Memory Multiprocessors

Parallel execution of prolog on shared-memory multiprocessors

1993 ◽  
Vol 8 (4) ◽  
pp. 329-336
Author(s):  
Yaoqing Gao ◽  
Dingxing Wang ◽  
Weimin Zheng ◽  
Meiming Shen ◽  
Zhiyi Huang ◽  
...  
Keyword(s):  
Shared Memory ◽  
Parallel Execution ◽  
Shared Memory Multiprocessors

Benefits of cache-affinity scheduling in shared-memory multiprocessors

1993 ◽  
Vol 21 (1) ◽  
pp. 272-274 ◽  
Author(s):  
Josep Torrellas ◽  
Andrew Tucker ◽  
Anoop Gupta
Keyword(s):  
Shared Memory ◽  
Shared Memory Multiprocessors ◽  
Cache Affinity

Parallel Nonnegative Matrix Factorization via Newton Iteration

2016 ◽  
Vol 26 (03) ◽  
pp. 1650014 ◽  
Author(s):  
Markus Flatz ◽  
Marián Vajteršic
Keyword(s):  
Shared Memory ◽  
Matrix Factorization ◽  
Message Passing ◽  
Nonnegative Matrix Factorization ◽  
Nonnegative Matrix ◽  
Newton Iteration ◽  
Parallel Execution ◽  
Kkt Conditions ◽  
Nonnegative Matrices ◽  
First Order

The goal of Nonnegative Matrix Factorization (NMF) is to represent a large nonnegative matrix in an approximate way as a product of two significantly smaller nonnegative matrices. This paper shows in detail how an NMF algorithm based on Newton iteration can be derived using the general Karush-Kuhn-Tucker (KKT) conditions for first-order optimality. This algorithm is suited for parallel execution on systems with shared memory and also with message passing. Both versions were implemented and tested, delivering satisfactory speedup results.

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