206929170
Optimizing the Fast Fourier Transform on a Multi-core Architecture
The rapid revolution in microprocessor chip architecture due to multicore technology is presenting unprecedented challenges to the application developers as well as system software designers: how to best exploit the parallelism potential due to such multi-core architectures? In this paper, we report an in-depth study on such challenges based on our experience of optimizing the fast Fourier transform (FFT) on the IBM Cyclops-64 chip architecture - a large-scale multi-core chip architecture consisting 160 thread units, associated memory banks and an interconnection network that connect them together in a shared memory organization. We demonstrate how multi-core architectures like the C64 could be used to achieve a high performance implementation of FFT both in 1D and 2D cases. We analyze the optimization challenges and opportunities including problem decomposition, load balancing, work distribution, and data-reuse, together with the exploiting of the C64 architecture features such as the multi-level of memory hierarchy and large register files. Furthermore, the experience learned during the hand-tuned optimization process have provided valuable guidance in our compiler optimization design and implementation. The main contributions of this paper include: 1) our study demonstrates that successful optimization for C64-like large-scale multi-core architectures requires a careful analysis that can identify certain domain-specific features of a target application (e.g. FFT) and match them well with some key multi-core architecture features; 2) our optimization, assisted with hand-tuned process, provided quantitative evidence on the importance of each optimization identified in 1); 3) automatic optimization by our compiler, the design and implementation of which is guided by the feedbacks from 1) and 2), shows excellent results that are often comparable to the results derived from our time-consuming hand-tuned code.
8575175
A User-Friendly Methodology for Automatic Exploration of Compiler Options
This paper introduces a practical methodology for automatic exploring compiler optimization options. The strategy behind this methodology is to provide an intelligent mechanism, in which the compiler will automatically identify optimized combination of compiler options for a given application. The decision made by the compiler is based on user requirements on what aspects of the generated code are the most critical for the compiled application through a specialized user interface. A set of pre-built databases of candidate optimized combinations of compiler options will help the compiler to make the right decision. This methodology will dramatically help users to get rid of the burden of fully understanding the compiler’s inner structure and organization to make the most profitable combination of options. All this work is taken by the compiler and the infrastructure proposed in this paper. This paper presents this methodology and describes its principles and technical mechanisms of the components.
33621532
Emotional expressions in audiovisual human computer interaction
Visual and auditory modalities are two of the most commonly used media in interactions between humans. The authors describe a system to continuously monitor the user's voice and facial motions for recognizing emotional expressions. Such an ability is crucial for intelligent computers that take on a social role such as an actor or a companion. We outline methods to extract audio and visual features useful for classifying emotions. Audio and visual information must be handled appropriately in single-modal and bimodal situations. We report audio-only and video-only emotion recognition on the same subjects, in person-dependent and person-independent fashions, and outline methods to handle bimodal recognition.
11658624
Statistical Feature Selection for Mandarin Speech Emotion Recognition
Performance of speech emotion recognition largely depends on the acoustic features used in a classifier. This paper studies the statistical feature selection problem in Mandarin speech emotion recognition. This study was based on a speaker dependent emotional mandarin database. Pitch, energy, duration, formant related features and some velocity information were selected as base features. Some statistics of them consisted of original feature set and full stepwise discriminant analysis (SDA) was employed to select extracted features. The results of feature selection were evaluated through a LDA based classifier. Experiment results indicate that pitch, log energy, speed and 1st formant are the most important factors and the accuracy rate increases from 63.1 % to 76.5 % after feature selection. Meanwhile, the features selected by SDA are better than the results of other feature selection methods in a LDA based classifier and SVM. The best performance is achieved when the feature number is in the range of 9 to 12.
335267
VLSI implementation of shape-adaptive discrete wavelet transform
In this paper, several VLSI architectures and implementations of Shape-Adaptive Discrete Wavelet Transform (SA-DWT) with odd symmetric biorthogonal filters are presented. The hardware implementation issues of SA-DWT algorithm are first addressed, and one lifting scheme together with some appropriate shape information processing units is introduced for the 1-D SA-DWT architectures. These architectures can efficiently perform 1-D length-adaptive DWT on continuous line segments and solve the corresponding boundary extension and subsampling problems without any overhead. In addition to 1-D architectures, two 2-D SA-DWT architectures are also proposed. One is the direct method, which uses the 1-D SA-DWT architectures as basis to extend to 2-D SA-DWT by direct row-column approach. The other is the line-based method, which is an efficient and feasible architecture that uses internal line buffers rather than external frame memory. These two 2-D SA-DWT architectures are both VLSI implemented by using cell-based chip design flow. The Daubechies (9,7) filter is used for the implementation by direct method, and the Daubechies (9,3) filter is used for the line-based implementation. The proposed architectures can be applied both in arbitrarily shaped visual objects coding such as MPEG-4 still texture coding and rectangular region image coding such as JPEG2000 still image coding.
8887048
Using a Soft Core in a SoC Design: Experiences with picoJava
Through our experience in synthesis, validation, test, and integration of the picoJava processor core in a system-on-chip (SoC) design we point out the challenges faced and issues to address in efficient reuse of a soft core.
5771208
Image annotation by large-scale content-based image retrieval
Image annotation has been an active research topic in recent years due to its potentially large impact on both image understanding and Web image search. In this paper, we target at solving the automatic image annotation problem in a novel search and mining framework. Given an uncaptioned image, first in the search stage, we perform content-based image retrieval (CBIR) facilitated by high-dimensional indexing to find a set of visually similar images from a large-scale image database. The database consists of images crawled from the World Wide Web with rich annotations, e.g. titles and surrounding text. Then in the mining stage, a search result clustering technique is utilized to find most representative keywords from the annotations of the retrieved image subset. These keywords, after salience ranking, are finally used to annotate the uncaptioned image. Based on search technologies, this framework does not impose an explicit training stage, but efficiently leverages large-scale and well-annotated images, and is potentially capable of dealing with unlimited vocabulary. Based on 2.4 million real Web images, comprehensive evaluation of image annotation on Corel and U. Washington image databases show the effectiveness and efficiency of the proposed approach.