We propose an unified parallel programming framework which supports both heterogeneity and fault tolerance in MPI programs on a variety of parallel computing platforms. This paper is mainly dedicated to heterogeneity ...
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ISBN:
(纸本)9781424468904
We propose an unified parallel programming framework which supports both heterogeneity and fault tolerance in MPI programs on a variety of parallel computing platforms. This paper is mainly dedicated to heterogeneity support in our framework. In our framework, a variety of parallel and sequential jobs submitted by multiple users are optimally scheduled on heterogeneous parallel computing environment. To balance the loads among the nodes on such heterogeneous computing environments, some of the parallel processes should be transferred between the nodes. We adopted the migration facility provided by Xen virtualization to realize a load balancing system where an MPI process running on a Xen virtual machine is migrated between the nodes. We confirmed that the protype system offers efficient load balancing facilities for heterogeneous computing environment with low overhead incurred by Xen virtualization.
Given the ubiquity of parallel computing hardware, we introduced parallelprogramming with pictures to the block-based Snap! environment and called it pSnap!, short for parallel Snap! We then created an accessible curr...
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ISBN:
(纸本)9798350311990
Given the ubiquity of parallel computing hardware, we introduced parallelprogramming with pictures to the block-based Snap! environment and called it pSnap!, short for parallel Snap! We then created an accessible curriculum for students of all ages to learn how to program serially and then how to program with explicit parallelism. This paper presents a new and innovative extension to our curriculum on parallel programming with pSnap!, one that broadens its appeal to the masses by teaching the application of parallel programming as a "choose your own learning adventure" activity, inspired by the Choose Your Own Adventure book series of the 1980s and 1990s. Specifically, after students learn the basics of parallel programming with pictures, they are ready to choose their next learning adventure, which applies their newfound parallel programming skills to create a video game of their choice, i.e., Missile Command or Do You Want to Build a Snowman?
GPU and multicore hardware architectures are commonly used in many different application areas to accelerate problem solutions relative to single CPU architectures. The typical approach to accessing these hardware arc...
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ISBN:
(纸本)9781450336185
GPU and multicore hardware architectures are commonly used in many different application areas to accelerate problem solutions relative to single CPU architectures. The typical approach to accessing these hardware architectures requires embedding logic into the programming language used to construct the application;the two primary forms of embedding are: calls to API routines to access the concurrent functionality, or pragmas providing concurrency hints to a language compiler such that particular blocks of code are targeted to the concurrent functionality. The former approach is verbose and semantically bankrupt, while the success of the latter approach is restricted to simple, static uses of the functionality. This paper presents an extension to an existing actor-based programming model and runtime to support executing applications on parallel hardware architectures. Besides the glove-like fit of a kernel to the actor abstraction, quantitative code analysis shows that actor-based kernels are always significantly simpler than API-based coding, and generally simpler than pragma-based coding. The structuring of applications in this manner, enables the runtime to automate the initialisation and interaction with these parallel hardware platforms. Performance measurements show that the overheads of actor-based kernels are commensurate to API based kernels, and range from equivalent to vastly improved for pragma-based annotations, both for sample and real world applications.
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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