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Approximate computing is an emerging design paradigm that exploits the intrinsic ability of applications to produce acceptable outputs even when their computations are executed approximately. In this paper, we explore approximate computing for a key computation pattern, reduce-and-rank (RnR), which is prevalent in a wide range of workloads, including video processing, recognition, search, and data...
As many real-world data can elegantly be represented as graphs, various graph kernels and methods for computing them have been proposed. Surprisingly, many of the recent graph kernels do not employ the kernel trick anymore but rather compute an explicit feature map and report higher efficiency. So, is there really no benefit of the kernel trick when it comes to graphs? Triggered by this question,...
Spatial data mining techniques enable the knowledge extraction from spatial databases. However, the high computational cost and the complexity of algorithms are some of the main problems in this area. This work proposes a new algorithm referred to as VDBSCAN+, which derived from the algorithm VDBSCAN (Varied Density Based Spatial Clustering of Applications with Noise) and focuses on the use of parallelism...
The shift towards using increasing numbers of processing elements has placed new burdens on the programming community to fully exploit the potential performance gain of multiprocessor systems. The programming problem is even more complex in the case of systems that utilize reconfigurable devices. The increased complexity of programming necessitates the use of tools that can support programmers in...
As data sizes continue to increase, the concept of active storage is well fitted for many data analysis kernels. Nevertheless, while this concept has been investigated and deployed in a number of forms, enabling it from the parallel I/O software stack has been largely unexplored. In this paper, we propose and evaluate an active storage system that allows data analysis, mining, and statistical operations...
We proceed from a method for protein structure comparison in which information about the geometry and physico-chemical properties of such structures are represented in the form of labeled point clouds, that is, a set of labeled points in three-dimensional Euclidean space. Two point clouds are then compared by computing an optimal spatial superposition. This approach has recently been introduced in...
For a long time, dynamic tracing has been an enabling technique for reverse engineering tools. Tracing can not only be used to record the control flow of a particular component such as a piece of malware itself, it is also a way to analyze the interactions of a component and their impact on the rest of the system. Unlike Unix-based systems, for which several dynamic tracing tools are available, Windows...
In this paper, we present LiteView, an experimental toolkit for end-user diagnosis of communication path problems in sensor network systems. This toolkit provides an on-site, interactive environment that helps answering questions related to the instantaneous communication environments. For example, it allows users to identify broken links or asymmetric links, which are likely to become traffic bottlenecks...
Many problems in intelligent data analysis involve some forms of dimensionality reduction. The paper discusses a new supervised dimensionality reduction method where samples are accompanied with class labels. We also show that it can be easily extended to the non-linear dimensionality reduction scenarios by the kernel tricks, and then we proposes an effective orthogonal feature subspace and correlation...
In recent years, Java enterprise edition (Java EE) technologies keep expanding with more and more features. The customization of application server is becoming multifarious owing to different environments and domains. And delivering a continuous evolving application server is more frequent and costly. However, current application servers cannot meet such requirements, due to their inexplicit module...
Remote attestation of system integrity is an essential part of trusted computing. However, current remote attestation techniques only provide integrity proofs of static properties of the system. To address this problem we present a novel remote dynamic attestation system named ReDAS (Remote Dynamic Attestation System) that provides integrity evidence for dynamic system properties. Such dynamic system...
In this paper, we present a runtime optimization targeting the speedup of applications running on a reconfigurable platform supporting the MOLEN programming paradigm. More specifically, for functions that have an execution time dependent on parameters, we propose an online adaptive decision algorithm to determine if the gain of running that function in hardware outweighs the overhead of transferring...
Efficiently using the computational power made available through desktop grids based distributed systems is a complicated and many-sided problem, caused by the intermittent resource availability. In this paper a novel solution is presented for predicting the runtimes of parameter sweep jobs. These jobs are characterized by their lack of inter-dependence and suitability for runtime prediction by modeling...
Most practical signal processing problems have to deal with uncertainties, e. g., due to noisy input data. Usual strategies to do this are based on estimating these uncertainties by statistical methods in advance. For some systems with multi-staged signal processing it is possible to identify these estimates at runtime and to relate a degree of certainty to them. If such degrees of certainty are known...
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