Parallel data compression

Data compression schemes remove data redundancy in communicated and stored data and increase the effective capacities of communication and storage devices. Parallel algorithms and implementations for textual data compression are surveyed. Related concepts from parallel computation and information theory are briefly discussed. Static and dynamic methods for codeword construction and transmission on various models of parallel computation are described. Included are parallel methods which boost system speed by coding data concurrently, and approaches which employ multiple compression techniques to improve compression ratios. Theoretical and empirical comparisons are reported and areas for future research are suggested

Reconfigurable acceleration of genetic sequence alignment: A survey of two decades of efforts

Genetic sequence alignment has always been a computational challenge in bioinformatics. Depending on the problem size, software-based aligners can take multiple CPU-days to process the sequence data, creating a bottleneck point in bioinformatic analysis flow. Reconfigurable accelerator can achieve high performance for such computation by providing massive parallelism, but at the expense of programming flexibility and thus has not been commensurately used by practitioners. Therefore, this paper aims to provide a thorough survey of the proposed accelerators by giving a qualitative categorization based on their algorithms and speedup. A comprehensive comparison between work is also presented so as to guide selection for biologist, and to provide insight on future research direction for FPGA scientists

A study on the effect of stroop test on the formation of students discipline by using the Heart Rate Variability (HRV) technique

Discipline refers to self-control and individual behaviour. Other than that, discipline is an important element in the formation of integrity level. The objective of the study is to assess the effects of using the Stroop test of biofeedback protocol in order to evaluate individual level of discipline. A clinical study has been conducted on 50 participants which is the participants is a undergraduate student from Universiti Malaysia Pahang, who were divided into two groups. First group is students get high achiever and second group is students get low achierver in academic. The Heart Rate Variability (HRV) technique has been used in the assessment of this protocol. The findings show that there was a positive relationship between the Stroop test and the students discipline that those who excelled managed to get higher score of LF spectrum as compared to HF and VLF, while the students with lower achievement showed higher score of VLF and HF spectrum than LF. In conclusion, this test is one of the tests that can be used in increasing the level of individual discipline

The Mercury System: Exploiting Truly Fast Hardware in Data Mining

In many data mining applications, the size of the database is not only extremely large, it is also growing rapidly. Even for relatively simple searches, the time required to move the data off magnetic media, cross the system bus into main memory, copy into processor cache, and then execute code to perform a search is prohibitive. We are building a system in which a significant portion of the data mining task (i.e., the portion that examines the bulk of the raw data) is implemented in fast hardware, close to the magnetic media on which it is stored. Furthermore, this hardware can be replicated allowing mining tasks to be performed in parallel, thus providing further speedup for the overall mining application. In this paper, we describe a general framework under which this can be accomplished and provide initial performance results for a set of applications

FPGA acceleration of DNA sequence alignment: design analysis and optimization

Existing FPGA accelerators for short read mapping often fail to utilize the complete biological information in sequencing data for simple hardware design, leading to missed or incorrect alignment. In this work, we propose a runtime reconfigurable alignment pipeline that considers all information in sequencing data for the biologically accurate acceleration of short read mapping. We focus our efforts on accelerating two string matching techniques: FM-index and the Smith-Waterman algorithm with the affine-gap model which are commonly used in short read mapping. We further optimize the FPGA hardware using a design analyzer and merger to improve alignment performance. The contributions of this work are as follows. 1. We accelerate the exact-match and mismatch alignment by leveraging the FM-index technique. We optimize memory access by compressing the data structure and interleaving the access with multiple short reads. The FM-index hardware also considers complete information in the read data to maximize accuracy. 2. We propose a seed-and-extend model to accelerate alignment with indels. The FM-index hardware is extended to support the seeding stage while a Smith-Waterman implementation with the affine-gap model is developed on FPGA for the extension stage. This model can improve the efficiency of indel alignment with comparable accuracy versus state-of-the-art software. 3. We present an approach for merging multiple FPGA designs into a single hardware design, so that multiple place-and-route tasks can be replaced by a single task to speed up functional evaluation of designs. We first experiment with this approach to demonstrate its feasibility for different designs. Then we apply this approach to optimize one of the proposed FPGA aligners for better alignment performance.Open Acces