A number of parallel programming techniques have been used in the construction of parallel linear algebra algorithms at KSLA. These techniques rely on the use of invariants and clustering of invariants in order to obt...
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A scale-out system is a cluster of commodity machines, and offers a good platform to support steadily increasing workloads that process growing data sets. Sharding [4] is a method of partitioning data and processing a...
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ISBN:
(纸本)9781605589084
A scale-out system is a cluster of commodity machines, and offers a good platform to support steadily increasing workloads that process growing data sets. Sharding [4] is a method of partitioning data and processing a computation on a scale-out system. In a database system, a large table can be partitioned into small tables so each node can process its part of the computation. The sharding approach in a large batch transaction processing, which is important in financial area, presents two hard problems to programmers. Programmers have to write complex code (1) to transfer the input data so as to align the computations with the data partitions, and (2) to manage the distributed transactions. This paper presents a new parallel programming framework that makes parallel transactional programming easier by specifying transaction scopes and partitioners to simplify the code. Transaction scopes include series of subtransactions, each of which performs local operations. The system manages the distributed transactions automatically. A partitioner represents how the computation should be decomposed and aligned with the data partitions to avoid remote database accesses. Between paired of subtransactions, the system handles the data shuffling across the network. We implemented our parallel programming framework as a new Java class library. We hide all of the complex details of data transfer and distributed transaction management in the library. Our programming framework can eliminate almost 66% of the lines of code compared to a current programming approach without programming framework support. We also confirmed good scalability, with a scaling factor of 20.6 on 24 nodes using our modified batch program for the TPC-C benchmark. Copyright 2010 ACM.
To overcome the restriction of unbiased predictors in kriging interpolation, Bayesian Kriging integrates prior distribution of variogram parameters such as coefficients, data vari-Ance, range, and nugget to be adopted...
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ISBN:
(纸本)9783000503375
To overcome the restriction of unbiased predictors in kriging interpolation, Bayesian Kriging integrates prior distribution of variogram parameters such as coefficients, data vari-Ance, range, and nugget to be adopted as a qualified gueb in the spatial estimation . The observation uncertainty is represented as a posterior distribution and predictive parame-Ter distribution avoiding unrealistic small regions within the observations to attain optimal unbiased linear interpolation through Bayesian kriging algorithm. Prior to estimate the pre-dictive spatial distributions, the procedure includes multiple computations of an emperical variogram for the petrophysical properties given posterior distribution of the variogram pa-rameters to create many equiprobable reservoir stochastic images. Based on the statistical evaluation, these realizations are ranked to select three quartiles (P10, P50, and P90).
Moore's Law will continue to increase the number of transistors on die for a couple of decades, as silicon technology moves from 65nm today to 45nm, 32 nm and 22nm in the future. Since the power and thermal constr...
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parallel programs display two fundamentally different kinds of execution behavior: synchronous and asynchronous. Some methodologies, such as distributed data structures, are best suited to the construction of asynchro...
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We describe Actors, a flexible, scalable and efficient model of computation, and develop a framework for analyzing the parallel complexity of programs written in it. Actors are asynchronous, autonomous objects which i...
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Efficient, scalable and productive parallel programming is a major challenge for exploiting the future multiprocessor SoC platforms. This article presents the MultiFlex programming environment which has been developed...
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In this paper, bye present a new powerful method for parallel program representation called Data Driven Graph (DDG). DDG takes all advantages of classical Directed Acyclic graph (DAC) and adds much more. Simple defini...
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parallel hardware is today's reality and language extensions that ease exploiting its promised performance ourish. For most mainstream languages, one or more tailored solutions exist that address the specific need...
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