21499977
Predicate Analysis Based on Path Information
Predicated execution leads new challenges to traditional optimizers. Limited by predicate representations, current predicate analysis methods could only perform locally or have low efficiency. A new representation based on path information is proposed in this paper, based on which a global predicate relation query system is constructed. Experiment results indicate that precise and efficient global predicate analysis could be achieved with this system and the performance of optimized codes can also be improved.
31522150
Hardware Support for Arithmetic Units of Processor with Multimedia Extension
Multimedia extension technique is very popular in designing processors to improve multimedia processing performance. This paper carries on the study of hardware implementation of arithmetic units with multimedia extension support, and proposes new design methods for subword multiplier and SIMD (single instruction multiple data) IEEE FPU (floating-point unit). To verify the correctness and effectiveness of these methods, a multimedia coprocessor with SIMD fixed-point and floating-point units is designed. The implemented chip successfully demonstrates that the proposed SIMD Arithmetic units get good tradeoff between cost and performance.
60639655
Parallel simulation of chip-multiprocessor by using multi-threading
Multi-core on one chip becomes the current main trend of micro processors' architecture, and simulation plays an important role in evaluating new processor architectures. Traditional ways of sequential simulation for chip-multiprocessor (CMP) require lots of simulation time which can't be afford during processor design phase. Therefore, exploiting parallelism is necessary for speeding up the multi-core processor simulation. 
 
In this paper, we present a parallel CMP simulator, which is implemented by using POSIX threads, and also present the programming methodology for converting a sequential single core simulator to a parallel CMP simulator. Furthermore, the tradeoffs in parallel simulator implementation are also discussed. The experiments are carried out on a four-CPU dual core Xeon server. Under weak consistence order model, the parallel simulator achieves a speedup of 7.2X comparing with the sequential one.
40046861
A New CORDIC Algorithm and Software Implementation Based on Synchronized Data Triggering Architecture
A new CORDIC algorithm based on sign bits prediction is presented. It is an effective method for transforming arbitrary iterations of classic CORDIC to simple matrix multiplications. At the same time, this algorithm is implemented based on synchronized data triggering architecture (SDTA). Experimental results show that the average speed-up of transcendental functions tested based on our version CORDIC compared with mathematic library supported in gcc3.2.2 is up to 283% under the given Neuron microprocessor.
33440658
A New Technique for Program Code Compression in Embedded Microprocessor
Program code compression has become a critical technology nowadays, and it can promote the performance of microprocessor systems. But compression techniques nowadays can hardly achieve both satisfactory compression ratio and low hardware complexity. A new program code compression method is proposed in this paper. Experiment results show that the code sizes of ARM and OR1200 microprocessor can be efficiently reduced by 32.2% and 36.9% individually with this algorithm, resulting to a sharp decrease in memory traffic. A hardware decompressing prototype is also presented, revealing its advantage in ultra high speed decompression and low hardware complexity.
14935665
Optimal Matrix Computing Using Vector Division with Sub-word Parallel
Available computing is expected to be effective and efficient in ubiquitous multimedia services. And, matrix multiplication is particular to ubiquitous computing such as image transformation so that it is urgent to exploit potential parallelism as well as data reuse in matrix multiplication. Therefore, based on synchronized data triggered architecture (SDTA), we propose a method of parallel vector division (PVD) as well as sub-word parallel (SWP) supported on SDTA to optimize the matrix computation on specified architecture. Experimental results show that PVD with SWP is suitable for matrix multiplication on SDTA instruction set architecture. Besides, we could extend the proposed model into other data-intensive computing on SDTA.
14116656
The design and implementation of a program development system based on rewriting method
In this paper, we present a program development system based on rewriting method with the goal of providing an powerful tool for automatic software development and rapid prototyping. New mechanisms for defining constrained types and optimal rules are introduced to functional programming languages to achieve strong expressiveness. The enhanced functional programming language is combined with an algebraic specification language. Thus, the design from specification to program can be supported, and the efficiency and flexibility of programming can also be improved. In this system, both static and dynamic techniques are used to deal with constrained type check. All function definitions, computation constraints and optimal rules are regarded as rewriting rules. In order to provide a strong support for a large group of TRSs which may be neither terminating nor orthogonal, we propose a method using structure measure to decide TRSs' confluences. Based on this method, we present a partial completion algorithm to generate a rewriting model from a specification. Depending on term rewriting system, the mixed language system computes with parallel outermost and needed reduction. We explain the principles and implementation techniques in detail, some examples are provided.
74980
PLS and SVD based penalized logistic regression for cancer classification using microarray data
Accurate cancer prediction is important for treatment of cancers. The combination of two dimension reduction methods, partial least squares (PLS) and singular value decomposition (SVD), with the penalized logistic regression (PLR) has created powerful classifiers for cancer prediction using microarray data. Comparing with support vector machine (SVM) on seven publicly available cancer datasets, the new algorithms can achieve very good performance and run much faster. They also have the advantage that the probabilities of predictions can be directly given. PLS based PLR is also combined with recursive feature elimination (RFE) to select a 16-gene subset for acute leukemia cancer classification. The testing error on this subset of genes is empirically zero.
8343773
A spatio-temporal multi-modal data management and analysis environment for tracking MS lesions
We describe the development of a system that automates data collection, metadata extraction and analysis of spatio-temporal multi-modal data, combining data management and data analysis to provide an efficient resource for clinicians. Though the system is extensible to many applications, the current focus is on managing Multiple Sclerosis (MS) lesion data, which are disparate streams of image, numeric, and text data. In order to discover patterns of MS pathology and plan early and effective treatment, multispectral magnetic resonance (MR) image streams collected over time need to be correlated efficiently with each other and with patient performance and clinical data streams.
18590624
Fourier method for large-scale surface modeling and registration
Spherical harmonic (SPHARM) description is a powerful Fourier shape modeling method for processing arbitrarily shaped but simply connected 3D objects. As a highly promising method, SPHARM has been widely used in several domains including medical imaging. However, its primary use has been focused on modeling small or moderately-sized surfaces that are relatively smooth, due to challenges related to its applicability, robustness and scalability. This paper presents an enhanced SPHARM framework that addresses these issues and show that the use of SPHARM can expand into broader areas. In particular, we present a simple and efficient Fourier expansion method on the sphere that enables large scale modeling, and propose a new SPHARM registration method that aims to preserve the important homological properties between 3D models. Although SPHARM is a global descriptor, our experimental results show that the proposed SPHARM framework can accurately describe complicated graphics models and highly convoluted 3D surfaces and the proposed registration method allows for effective alignment and registration of these 3D models for further processing or analysis. These methods greatly enable the potential of applying SPHARM to broader areas such as computer graphics, medical imaging, CAD/CAM, bioinformatics, and other related geometric modeling and processing fields.
2536263
Multi-scale Voxel-Based Morphometry Via Weighted Spherical Harmonic Representation
Although the voxel-based morphometry (VBM) has been widely used in quantifying the amount of gray matter of the human brain, the optimal amount of registration that should be used in VBM has not been addressed. In this paper, we present a novel multi-scale VBM using the weighted spherical harmonic (SPHARM) representation to address the issue. The weighted-SPHARM provides the explicit smooth functional representation of a true unknown cortical boundary. Based on this new representation, the gray matter tissue density is constructed using the Euclidean distance map from a voxel to the estimated smooth cortical boundary. The methodology is applied in localizing abnormal cortical regions in a group of autistic subjects.