A Paradigm of Extensions of Parallel Execution Model

2012 ◽  
Author(s):  
Zhao Jun ◽  
Zhang Li-Lun ◽  
Song Jun-Qiang
Keyword(s):  
Parallel Execution ◽  
Execution Model

A parallel execution model of logic programs

1983 ◽  
Vol 11 (3) ◽  
pp. 349-355 ◽  
Author(s):  
Shinji Umeyama ◽  
Koichiro Tamura
Keyword(s):  
Parallel Execution ◽  
Logic Programs ◽  
Execution Model

Shared memory multiprocessor support for functional array processing in SAC

2005 ◽  
Vol 15 (3) ◽  
pp. 353-401 ◽  
Author(s):  
CLEMENS GRELCK
Keyword(s):  
Shared Memory ◽  
Array Processing ◽  
Numerical Data ◽  
Parallel Execution ◽  
Real Performance ◽  
Execution Model ◽  
Series Of Experiments ◽  
High Level ◽  
Performance Gains ◽  
The Impact

Classical application domains of parallel computing are dominated by processing large arrays of numerical data. Whereas most functional languages focus on lists and trees rather than on arrays, SAC is tailor-made in design and in implementation for efficient high-level array processing. Advanced compiler optimizations yield performance levels that are often competitive with low-level imperative implementations. Based on SAC, we develop compilation techniques and runtime system support for the compiler-directed parallel execution of high-level functional array processing code on shared memory architectures. Competitive sequential performance gives us the opportunity to exploit the conceptual advantages of the functional paradigm for achieving real performance gains with respect to existing imperative implementations, not only in comparison with uniprocessor runtimes. While the design of SAC facilitates parallelization, the particular challenge of high sequential performance is that realization of satisfying speedups through parallelization becomes substantially more difficult. We present an initial compilation scheme and multi-threaded execution model, which we step-wise refine to reduce organizational overhead and to improve parallel performance. We close with a detailed analysis of the impact of certain design decisions on runtime performance, based on a series of experiments.

A HYBRID SHARED MEMORY EXECUTION MODEL FOR A DATA PARALLEL LANGUAGE WITH I/O

2008 ◽  
Vol 18 (01) ◽  
pp. 23-37 ◽  
Author(s):  
CLEMENS GRELCK ◽  
STEFFEN KUTHE ◽  
SVEN-BODO SCHOLZ
Keyword(s):  
Program Analysis ◽  
Flow Characteristics ◽  
Parallel Execution ◽  
Parallel Language ◽  
Data Parallel ◽  
Execution Model ◽  
Execution Mode ◽  
Parallel Code ◽  
Execution Models ◽  
Compilation Techniques

We propose a novel execution model for the implicitly parallel execution of data parallel programs in the presence of general I/O operations. This model is called hybrid because it combines the advantages of the standard execution models fork/join and SPMD. Based on program analysis the hybrid model adapts itself to one or the other on the granularity of individual instructions. We outline compilation techniques that systematically derive the organization of parallel code from data flow characteristics aiming at the reduction of execution mode switches in general and synchronization/communication requirements in particular. Experiments based on a prototype implementation show the effectiveness of the hybrid execution model for reducing parallel overhead.

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