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Li S.,Hefei University of Technology | Li S.,Key Laboratory on High Performance Computing of Anhui Province | Li S.,Intel Corporation | Cheng B.,Intel Corporation | And 5 more authors.
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | Year: 2012

As the Internet and the World Wide Web become more and more popular nowadays, and the JavaScript programming language is becoming a key role in Web browsers, investigation on the behavior of JavaScript applications is important to improve Web browser's performance and user experience. Traditional study believes that, the dynamic typing nature of the JavaScript language is the major performance bottleneck. So the main optimizations of most advanced mainstream JavaScript engines are all focused on dynamic typing problems. To learn the dynamic typing nature of JavaScript language in depth, two novel predication-based algorithms, called "type prediction" and "position-based inline caching", are introduced to tackle the problems. With these algorithms, the typing system of JavaScript language is studied systematically and the techniques are evaluated with a representative JavaScript performance benchmark-SunSpider. In experiments with the SunSpider applications, the predication-based algorithms can identify the types with 99% accuracy on average. And so it is believed that although the JavaScript language provides abundant dynamics with its typing system, the actual applications do not really use all the features and hence their behaviors are static at most time. This is the first time that such discovery is made and published.

Long B.,Anhui University of Science and Technology | Long B.,Key Laboratory on High Performance Computing of Anhui Province | Sun G.-Z.,Anhui University of Science and Technology | Sun G.-Z.,Key Laboratory on High Performance Computing of Anhui Province | And 3 more authors.
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2011

We present a hybrid-index structure for high-dimensional data which named HKD-tree (Hybrid K-Dimensional Tree). To make use of two-level parallelization of multi-core clusters, we combined with KD-tree and LSH, which uses LSH in the leaf nodes of KD-tree. Compared with the traditional index structure, the hybrid index structure has effective parallel processing ability and good scalability, which is suitable for the multi-core cluster platform and high-dimensional data indexing. The experiment results show that the performance of the hybrid index structure is superior to the traditional index structure on the multi-core cluster systems.

Fang W.,Hefei University of Technology | Fang W.,Key Laboratory on High Performance Computing of Anhui Province | Sun G.,Hefei University of Technology | Sun G.,Key Laboratory on High Performance Computing of Anhui Province | And 4 more authors.
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | Year: 2011

Three-dimensional fast Fourier transform(3D-FFT) is widely used in physics. It is crucial to many applications because it demands heavy calculation and communications. Thus in most cases it is 3D-FFT that dominates the computational time. The traditional parallel algorithms of 3D-FFT are not suitable for the sparse lattice which is often encountered in the field of quantum computing, because the block partitioning used may involve many redundant computing and communications, due to the sparse of non-zero elements in FFT grid. In this paper we propose a noval parallel algorithm of 3D-FFT. Unlike the previous methods, the new algorithm uses slice partitioning, and redesigns the computing order in order to minimize the calculation time and communication cost. Taking advantage of the slice partitioning, the new method are highly scalable and can automatically satisfy the demands of load balancing. We compare it with traditional algorithms in theory and in practice. Theoretical performance analysis shows that the new method can greatly reduce the computational time and increase parallel speedup. The experiments have been carried cut in some high-performance machines, such as KD-50, IBM JS22 and DAWNING. The results show that our new algorithm behaves much better than traditional algorithms in performing 3D-FFT for sparse lattice.

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