EQUALS – a fast parallel implementation of a lazy language

1997 ◽  
Vol 7 (2) ◽  
pp. 183-217 ◽  
Author(s):  
OWEN KASER ◽  
C. R. RAMAKRISHNAN ◽  
I. V. RAMAKRISHNAN ◽  
R. C. SEKAR

This paper describes EQUALS, a fast parallel implementation of a lazy functional language on a commercially available shared-memory parallel machine, the Sequent Symmetry. In contrast to previous implementations, we propagate normal form demand at compile time as well as run time, and detect parallelism automatically using strictness analysis. The EQUALS implementation indicates the effectiveness of NF-demand propagation in identifying significant parallelism and in achieving good sequential as well as parallel performance. Another important difference between EQUALS and previous implementations is the use of reference counting for memory management, instead of mark-and-sweep or copying garbage collection. Implementation results show that reference counting leads to very good scalability and low memory requirements, and offers sequential performance comparable to generational garbage collectors. We compare the performance of EQUALS with that of other parallel implementations (the 〈v, G〉-machine and GAML) as well as with the performance of SML/NJ, a sequential implementation of a strict language.

2009 ◽  
Vol 19 (03) ◽  
pp. 469-476
Author(s):  
JOSEPH TANG

This paper describes a simple shared-memory parallel implementation of an octree adaptive mesh Computational Fluid Dynamics (CFD) code with an explicit time discretization scheme. The parallel performance of the code when running a realistic simulation gives a serial code fraction of no more than 13%. This should be suitable for small multicore engineering workstations where a simple code is desired and medium-sized simulations are sufficient.


2006 ◽  
Vol 34 (1) ◽  
pp. 3-10 ◽  
Author(s):  
Scott Friedman ◽  
Praveen Krishnamurthy ◽  
Roger Chamberlain ◽  
Ron K. Cytron ◽  
Jason E. Fritts

2020 ◽  
Vol 1 (3) ◽  
pp. 1-7
Author(s):  
Sarbani Dasgupta ◽  
Banani Saha

In data mining, Apriori technique is generally used for frequent itemsets mining and association rule learning over transactional databases. The frequent itemsets generated by the Apriori technique provides association rules which are used for finding trends in the database. As the size of the database increases, sequential implementation of Apriori technique will take a lot of time and at one point of time the system may crash. To overcome this problem, several algorithms for parallel implementation of Apriori technique have been proposed. This paper gives a comparative study on various parallel implementation of Apriori technique .It also focuses on the advantages of using the Map Reduce technology, the latest technology used in parallelization of large dataset mining.


Author(s):  
K. G. Langendoen ◽  
H. L. Muller ◽  
W. G. Vree

1997 ◽  
Vol 08 (04) ◽  
pp. 869-877 ◽  
Author(s):  
Giorgio Amati ◽  
Sauro Succi ◽  
Renzo Piva

High resolution lattice-Boltzmann simulations of turbulent channel flow on the Quadrics parallel machine are presented. The parallel performance is discussed together with some preliminary results concerning the vorticity structures which appear near the wall layer and their influence on the scaling laws.


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