The success of social network services has brought up many interesting Web 2.0 applications, while posed great challenges for human-real-time data management for huge volume of data with unstructured nature. Timeline ...
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On-chip caches are commonly used in computer systems to hide long off-chip memory access latencies. To manage on-chip caches, either software-managed or hardware-managed schemes can be employed. State-of-art accelerat...
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On-chip caches are commonly used in computer systems to hide long off-chip memory access latencies. To manage on-chip caches, either software-managed or hardware-managed schemes can be employed. State-of-art accelerators, such as the NVIDIA Fermi or Kepler GPUs and Intel's forthcoming MIC “Knights Landing” (KNL), support both software-managed caches, aka. shared memory (GPUs) or near memory (KNL), and hardware-managed L1 data caches (D-caches). Furthermore, shared memory and the L1 D-cache on a GPU utilize the same physical storage and their capacity can be configured at runtime (same for KNL). In this paper, we present an in-depth study to reveal interesting and sometimes unexpected tradeoffs between shared memory and the hardware-managed L1 D- caches in GPU architecture. In our study, the kernels utilizing the L1 D-caches are generated from those leveraging shared memory to ensure that the same optimizations such as tiling are applied equally in both versions. Our detailed analyses reveal that rather than cache hit rates, the following tradeoffs often have more profound performance impacts. On one hand, the kernels utilizing the L1 caches may support higher degrees of thread-level parallelism, offer more opportunities for data to be allocated in registers, and sometimes result in lower dynamic instruction counts. On the other hand, the applications utilizing shared memory enable more coalesced accesses and tend to achieve higher degrees of memory-level parallelism. Overall, our results show that most benchmarks perform significantly better with shared memory than the L1 D-caches due to the high impact of memory-level parallelism and memory coalescing.
with the increasing popularity of cloud services,attacks on the cloud infrastructure also increase ***,how to monitor the integrity of cloud execution environments is still a difficult *** this paper,a real-time dynam...
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with the increasing popularity of cloud services,attacks on the cloud infrastructure also increase ***,how to monitor the integrity of cloud execution environments is still a difficult *** this paper,a real-time dynamic integrity validation(DIV) framework is proposed to monitor the integrity of virtual machine based execution environments in the *** can detect the integrity of the whole architecture stack from the cloud servers up to the VM OS by extending the current trusted chain into virtual machine's architecture *** introduces a trusted third party(TTP) to collect the integrity information and detect remotely the integrity violations on VMs periodically to avoid the heavy involvement of cloud tenants and unnecessary information leakage of the cloud *** evaluate the effectiveness and efficiency of DIV framework,a prototype on KVM/QEMU is implemented,and extensive analysis and experimental evaluation are *** results show that the DIV can efficiently validate the integrity of files and loaded programs in real-time,with minor performance overhead.
We consider the problem of online dynamic channel accessing in multi-hop cognitive radio networks. Previous works on online dynamic channel accessing mainly focus on single-hop networks that assume complete conflicts ...
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We consider the problem of online dynamic channel accessing in multi-hop cognitive radio networks. Previous works on online dynamic channel accessing mainly focus on single-hop networks that assume complete conflicts among all secondary users. In the multi-hop multi-channel network settings studied here, there is more general competition among different communication pairs. A simple application of models for single-hop case to multi-hop case with N nodes and M channels leads to exponential time/space complexity O (M N ), and poor theoretical guarantee on throughput performance. We thus novelly formulate the problem as a linearly combinatorial multi-armed bandits (MAB) problem that involves a maximum weighted independent set (MWIS) problem with unknown weights. To efficiently address the problem, we propose a distributed channel access algorithm that can achieve 1/ρ of the optimum averaged throughput where each node has communication complexity O (r 2 +D) and space complexity O (m) in the learning process, and time complexity O (D m ρr ) in strategy decision process for an arbitrary wireless network. Here ρ = 1 + ε is the approximation ratio to MWIS for a local r-hop network with m
Preprocessors such as cpp are often used to manage families of programs from a common code base. The approach is simple, but code instrumented with preprocessing commands may become unreadable and dificult to work wit...
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ISBN:
(纸本)9789633062289
Preprocessors such as cpp are often used to manage families of programs from a common code base. The approach is simple, but code instrumented with preprocessing commands may become unreadable and dificult to work with. We describe a system called VCL (variant configuration language) that enhances cpp to provide a better solution to the same problem. The main extensions have to do with propagation of parameters across source files during VCL processing, the ability to adapt source files for reuse depending on the reuse context, and the ability to form general templates to represent any group of similar program structures (methods, functions, classes, files, directories) in generic, adaptable form. In the paper, we describe salient features of VCL, explain how they alleviate some of the problems of cpp, and illustrate reuse capabilities of VCL with an example.
Recently, negative databases (NDBs) are proposed for privacy protection. Similar to the traditional databases, some basic operations could be conducted over the NDBs, such as select, intersection, update, delete and...
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Recently, negative databases (NDBs) are proposed for privacy protection. Similar to the traditional databases, some basic operations could be conducted over the NDBs, such as select, intersection, update, delete and so on. However, both classifying and clustering in negative databases have not yet been studied. Therefore, two algorithms, i.e., a k nearest neighbor (kNN) classification algorithm and a k-means clustering algorithm in NDBs, are proposed in this paper, respectively. The core of these two algorithms is a novel method for estimating the Hamming distance between a binary string and an NDB. Experimental results demonstrate that classifying and clustering in NDBs are promising.
The specification of modeling and analysis of real-time and embedded systems (MARTE) is an extension of the unified modeling language (UML) in the domain of real-time and embedded systems. Even though MARTE time m...
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The specification of modeling and analysis of real-time and embedded systems (MARTE) is an extension of the unified modeling language (UML) in the domain of real-time and embedded systems. Even though MARTE time model offers a support to describe both discrete and dense clocks, the biggest effort has been put so far on the specifi- cation and analysis of discrete MARTE models. To address hybrid real-time and embedded systems, we propose to ex- tend statecharts using both MARTE and the theory of hybrid automata. We call this extension hybrid MARTE statecharts. It provides an improvement over the hybrid automata in that: the logical time variables and the chronometric time vari- ables are unified. The formal syntax and semantics of hybrid MARTE statecharts are given based on labeled transition sys- tems and live transition systems. As a case study, we model the behavior of a train control system with hybrid MARTE statecharts to demonstrate the benefit.
There is a demand from simulation users for speed, the ability to obtain quickly results from simulation runs. Cloud computing offers the potential for scalable, on-demand access to resources that can be used to speed...
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There is a demand from simulation users for speed, the ability to obtain quickly results from simulation runs. Cloud computing offers the potential for scalable, on-demand access to resources that can be used to speed up simulation. However, developing cloud computing solutions for industry is difficult without appropriate expertise. This paper introduces the CloudSME project that is dedicated to developing cloud computing solutions for simulation in industry and presents an overview of the CloudSME Simulation Platform that is being used to support an initial set of Cloud-based versions of Simul8's discrete-event simulation environment, Ascomp's TransAT computational fluid dynamics application, Ingecon's 3D Scan Insole Designer tool and 2MORO's Bfly software for aircraft maintenance logistics. The paper presents an overview of cloud computing, the CloudSME project, the architecture of the CloudSME Simulation Platform and its two key elements: gUse and CloudBroker.
This paper presents an overview of a pilot implementation of the ISO/IEC 29110 standard, with a group of very small software development companies based in Ireland. This paper may serve as guidance for both researcher...
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Presently existing lightweight indoor/outdoor detection schemes on phones acquire accuracy by sensing variations of ambient physical environmental properties with inherent sensors on mobile phones, with which, however...
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Presently existing lightweight indoor/outdoor detection schemes on phones acquire accuracy by sensing variations of ambient physical environmental properties with inherent sensors on mobile phones, with which, however, the detection scheme cannot work well in some ambient environments, where the variations are not very observable. This detection scheme is with very high dependency on light. The I/O detector does not work well in poor lighting or fast changing lighting settings, therefore the I/O detection is very much challenged at times like dawn, dusk, or night. The target of this paper is finding a pervasive detection scheme independent of physical environments. In this paper, we present MobiIO, an lightweight indoor and outdoor detection scheme based on analyses of human activities. By recording human indoor and outdoor motion activities with sensors, typical features of their activities are extracted. We compare assorted combinations or groupings of various properties with SVM classifier. We classify indoor/outdoor settings through classifiers like SVM, Bayes, decision trees, HMM and compare the effects of classification in between various classifying algorithms.
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