Imagine stream processor has shown high performance and efficiency for media applications. Its potential for scientific applications is of great interest to the high performance computing community. This paper investi...
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Imagine stream processor has shown high performance and efficiency for media applications. Its potential for scientific applications is of great interest to the high performance computing community. This paper investigates this subject from a new angle. It roughly classifies the scientific programs into three classes based on their computation to memory access ratios. For each class, typical programs are programmed with StreamC/KernelC stream language and simulated based on the cycle-accurate simulator of Imagine. In-depth analysis is carried out for the performance data, with special attentions on the performance bottlenecks. The performance data obtained on Imagine are compared against data on two general-purpose x86 processors. The results show that programs with no DRAM accesses attain high floating point performance and efficiencies on Imagine. These programs' performance is only restricted by limited ILP (Instruction-Level parallelism) and load imbalance across ALUs. Programs with computation to memory operation ratios O(n) attain absolute floating point performance on Imagine comparable to that obtained on general-purpose processors, but their floating-point efficiencies are not satisfactory. It is essential to optimize these programs for high SRF (Stream Register File) and LRF (Local Register File) reuse and high ILP on Imagine. Programs with lower computation to memory operation ratios attain much lower floating-point performance and efficiencies on Imagine, compared to those obtained on x86 processors.
The paper presents the ongoing work of studying FMEA method for embedded safely critical software via formal analysis of various dependence relations among software elements, which can fairly improve the automation an...
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The paper presents the ongoing work of studying FMEA method for embedded safely critical software via formal analysis of various dependence relations among software elements, which can fairly improve the automation and precision of both system level and detailed level FMEA. These dependence relations are depicted by the formal models abstracted from software design and implementation, and the FMEA processes for both structural and object-oriented software are proposed respectively. The initial result of case study shows the effectiveness of the approach.
In most DHTs proposed so far, all nodes are assumed to be homogeneous, and all messages are routed using a common algorithm. In practice, however, nodes in large-scale systems might be heterogeneous with respect to th...
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In most DHTs proposed so far, all nodes are assumed to be homogeneous, and all messages are routed using a common algorithm. In practice, however, nodes in large-scale systems might be heterogeneous with respect to their capabilities, reputations, affiliations of administrative domains, and so on, which consequently makes it preferable to distinguish the heterogeneity of participant nodes. To achieve this, in this paper we present grouped tapestry (GTap), a novel tapestry-based DHT that supports organizing nodes into groups and allows flexible DHT routing. The effectiveness of our proposals is demonstrated through theoretical analysis and extensive simulations.
Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a parallel, cOllaborative and Probabilistic sea...
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UML dynamic models are important for software analysis and design. Verifying UML dynamic models to find design errors earlier is a key issue for ensuring software quality. Because of the characteristics such as concur...
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UML dynamic models are important for software analysis and design. Verifying UML dynamic models to find design errors earlier is a key issue for ensuring software quality. Because of the characteristics such as concurrency and hierarchy, model checking of UML Statecharts and collaboration diagrams faces the problem of state explosion. In this paper, UML Statecharts is firstly structurally expressed by hierarchical automata and its semantics for open systems is introduced. Then, the synchronization composition of objects in UML collaboration diagrams is expatiated, based on which the global system behaviors can be constructed. Based on hierarchical automata and simulation relation between semantics structures, the compositional rules for verifying concurrent object systems are proposed. It makes possible that the construction of global state space will be unnecessary in model checking of UML collaboration diagrams. The hierarchical structures of UML Statecharts are also brought into the compositional verification, which makes the model checking of implementation models can be carried out through replacing detailed components by abstract specifications.
Feature (gene) selection is a frequently used preprocessing technology for successful cancer classification task in microarray gene expression data analysis. Widely used gene selection approaches are mainly focused on...
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Feature (gene) selection is a frequently used preprocessing technology for successful cancer classification task in microarray gene expression data analysis. Widely used gene selection approaches are mainly focused on the filter methods. Filter methods are usually considered to be very effective and efficient for high-dimensional data. This paper reviews the existing filter methods, and shows the performance of the representative algorithms on microarray data by extensive experimental study. Surprisingly, the experimental results show that filter methods are not very effective on microarray data. We analyze the cause of the result and provide the basic ideas for potential solutions.
Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a parallel, collaborative and Probabilistic sea...
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Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a parallel, collaborative and Probabilistic search mechanism, in which query messages are viewed as search units to collaborate with each other and aggregate the distributed hints during the search process. A scheme called distributed Bloom filter (DBF) is presented to propagate the hints with a bandwidth-aware manner, in which a node divides the received Bloom filter vector into subvectors and disseminates the fragments to its neighbors according to their bandwidth capacity. The effectiveness of POP is demonstrated through theoretical analysis and extensive simulations.
Data replication introduces well-known consistency issues. This paper puts forward the question about data dependence in data consistency, which embodies pseudo-conflict updates and update dependency. According to tha...
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Program mode is a regular trajectory of the execution of a program that is determined by the values of its input variables. By exploiting program modes we may make Worst Case Execution Time (WCET) analysis more precis...
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ISBN:
(纸本)1595934081
Program mode is a regular trajectory of the execution of a program that is determined by the values of its input variables. By exploiting program modes we may make Worst Case Execution Time (WCET) analysis more precise. This paper presents a novel method to automatically find program modes and calculate the WCET of programs. It consists of two phases. In phase one, we firstly automatically find the modes of a program by mode-relevant program slicing;then we compute the precondition for each mode using a path-wise test data generation method;after that, we can either conclude that it is an infeasible path, or get its precondition. In phase two, we calculate the WCET estimate of each given mode for modern RISC processors with caches and pipelines. The experiments are demonstrated to show the effectiveness of the method. Copyright 2006 ACM.
Rough set theory has been widely and successfully used in data mining, especially in classification field. But most existing rough set based classification approaches require computing optimal attribute reduction, whi...
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