417212
Taxonomy of Data Prefetching for Multicore Processors
Data prefetching is an effective data access latency hiding technique to mask the CPU stall caused by cache misses and to bridge the performance gap between processor and memory. With hardware and/or software support, data prefetching brings data closer to a processor before it is actually needed. Many prefetching techniques have been developed for single-core processors. Recent developments in processor technology have brought multicore processors into mainstream. While some of the single-core prefetching techniques are directly applicable to multicore processors, numerous novel strategies have been proposed in the past few years to take advantage of multiple cores. This paper aims to provide a comprehensive review of the state-of-the-art prefetching techniques, and proposes a taxonomy that classifies various design concerns in developing a prefetching strategy, especially for multicore processors. We compare various existing methods through analysis as well.
5789716
Reevaluating Amdahl's law in the multicore era
Microprocessor architecture has entered the multicore era. Recently, Hill and Marty presented a pessimistic view of multicore scalability. Their analysis was based on Amdahl's law (i.e. fixed-workload condition) and challenged readers to develop better models. In this study, we analyze multicore scalability under fixed-time and memory-bound conditions and from the data access (memory wall) perspective. We use the same hardware cost model of multicore chips used by Hill and Marty, but achieve very different and more optimistic performance models. These models show that there is no inherent, immovable upper bound on the scalability of multicore architectures. These results complement existing studies and demonstrate that multicore architectures are capable of extensive scalability.
206370432
An accurate sampling-based method for approximating geometry
We present a sampling-based method for approximating the boundary of a geometry defined by various geometric operations. Based on a novel adaptive sampling condition, we first construct volumetric grids such that an error-minimizing point can be found in each cell to capture all the geometric objects inside the cell. We then construct a polygonal model from the grid. We guarantee the boundary approximation has the same topology as the exact surfaces, and the maximum approximation error from the exact surfaces is bounded by a user specified tolerance. Our method is robust and easy to implement. We have applied it in various applications such as remeshing of polygonal models, Boolean operations, and offsetting operations. We report experimental results on a variety of CAD models.
16631254
Using data mining techniques and rough set theory for language modeling
In this article, we propose a new postprocessing strategy, word suggestion, based on a multiple word trigger-pair language model for Chinese character recognizers. With the word suggestion strategy, Chinese character recognizers may even achieve a recognition rate greater than the top-n candidate recognition rate. To construct the multiple word trigger-pair model, data mining techniques are used to alleviate the intensive computation problem. Furthermore, rough set theory is first used in the study to discover negatively correlated relationships between words in order to prevent introducing wrong words in the process of word suggestion.
135614560
Gold nanohole arrays for biochemical sensing fabricated by soft UV nanoimprint lithography
We report on results of fabrication and optical characterisation of sub-250nm periodic gold nanohole arrays on glass by using UV nanoimprint lithography (UV-NIL) combined with both reactive ion etching (RIE) and Cr/Au lift-off processes. The transmission spectra of the fabricated nanohole gratings were measured for different hole diameters and periods. We also show preliminary results of chemical sensing after surface modification of the gold hole arrays. In agreement with the theoretical prediction, we found that any change in the dielectric index of the surrounding environment of the metallic array produces a transmission peak red shift.
20461063
The function cascade synchronization approach with uncertain parameters or not for hyperchaotic systems
The function cascade synchronization scheme for the hyperchaotic systems is proposed to make the states of two identical the hyperchaotic systems both with and without uncertain parameters asymptotically synchronized. Based on Lyapunov stability theory and the proposed scheme, the Lu system and Chen hyperchaotic system with and without uncertain parameters are chosen to achieve the function cascade synchronization simultaneously. Numerical simulations are used to verify the effectiveness and feasibility of the presented control scheme.
37352290
Comparison of Two Fitness Functions for GA-Based Path-Oriented Test Data Generation
Automatic path-oriented test data generation is not only a crucial problem but also a hot issue in the research area of software testing today. As a robust metaheuritstic search method in complex spaces, genetic algorithm (GA) has been used to path-oriented test data generation since 1992 and outperforms other approaches. A fitness function based on branch distance (BDBFF) and another based on normalized extended Hamming distance (SIMILARITY) are both applied in GA-based path-oriented test data generation. To compare performance of these two fitness functions, a triangle classification program was chosen as the example. Experimental results show that BDBFF-based approach can generate path-oriented test data more effectively and efficiently than SIMILARITY- based approach does.