Design and application of reconfigurable circuits and systems

Open Acces

Multiple Biolgical Sequence Alignment: Scoring Functions, Algorithms, and Evaluations

Aligning multiple biological sequences such as protein sequences or DNA/RNA sequences is a fundamental task in bioinformatics and sequence analysis. These alignments may contain invaluable information that scientists need to predict the sequences\u27 structures, determine the evolutionary relationships between them, or discover drug-like compounds that can bind to the sequences. Unfortunately, multiple sequence alignment (MSA) is NP-Complete. In addition, the lack of a reliable scoring method makes it very hard to align the sequences reliably and to evaluate the alignment outcomes. In this dissertation, we have designed a new scoring method for use in multiple sequence alignment. Our scoring method encapsulates stereo-chemical properties of sequence residues and their substitution probabilities into a tree-structure scoring scheme. This new technique provides a reliable scoring scheme with low computational complexity. In addition to the new scoring scheme, we have designed an overlapping sequence clustering algorithm to use in our new three multiple sequence alignment algorithms. One of our alignment algorithms uses a dynamic weighted guidance tree to perform multiple sequence alignment in progressive fashion. The use of dynamic weighted tree allows errors in the early alignment stages to be corrected in the subsequence stages. Other two algorithms utilize sequence knowledge-bases and sequence consistency to produce biological meaningful sequence alignments. To improve the speed of the multiple sequence alignment, we have developed a parallel algorithm that can be deployed on reconfigurable computer models. Analytically, our parallel algorithm is the fastest progressive multiple sequence alignment algorithm

BioScript: programming safe chemistry on laboratories-on-a-chip

This paper introduces BioScript, a domain-specific language (DSL) for programmable biochemistry which executes on emerging microfluidic platforms. The goal of this research is to provide a simple, intuitive, and type-safe DSL that is accessible to life science practitioners. The novel feature of the language is its syntax, which aims to optimize human readability; the technical contributions of the paper include the BioScript type system and relevant portions of its compiler. The type system ensures that certain types of errors, specific to biochemistry, do not occur, including the interaction of chemicals that may be unsafe. The compiler includes novel optimizations that place biochemical operations to execute concurrently on a spatial 2D array platform on the granularity of a control flow graph, as opposed to individual basic blocks. Results are obtained using both a cycle-accurate microfluidic simulator and a software interface to a real-world platform

Prototyping environment for robot manipulators

Journal ArticlePrototyping is an important activity in engineering. Prototype development is a good test for checking the viability of a proposed system. Prototypes can also help in determining system parameters, ranges, or in designing better systems. We are proposing a prototyping environment for electro-mechanical systems, and we chosen a 3-link robot manipulator as an example. In Designing a robot manipulator, the interaction between several modules (S/W, VLSI, CAD, CAM, Robotics, and Control) illustrates an interdisciplinary prototyping environment that includes different types of information that are radically different but combined in a coordinated way. This environment will enable optimal and flexible design using reconfigurable links, joints, actuators, and sensors. Such an environment should have the right "mix" of software and hardware components for designing the physical parts and the controllers, and for the algorithmic control for the robot modules (kinematics, inverse kinematics, dynamics, trajectory planning, analog control and computer (digital) control). Specifying object-based communications and catalog mechanisms between the software modules, controllers, physical parts, CAD designs, and actuator and sensor components is a necessary step in the prototyping activities. In this report a framework for flexible prototyping environment for robot manipulators is proposed along with the required sub-systems and interfaces between the different components of this environment

Design and Evaluation of a BLAST Ungapped Extension Accelerator, Master\u27s Thesis

The amount of biosequence data being produced each year is growing exponentially. Extracting useful information from this massive amount of data is becoming an increasingly difficult task. This thesis focuses on accelerating the most widely-used software tool for analyzing genomic data, BLAST. This thesis presents Mercury BLAST, a novel method for accelerating searches through massive DNA databases. Mercury BLAST takes a streaming approach to the BLAST computation by offloading the performance-critical sections onto reconfigurable hardware. This hardware is then used in combination with the processor of the host system to deliver BLAST results in a fraction of the time of the general-purpose processor alone. Mercury BLAST makes use of new algorithms combined with reconfigurable hardware to accelerate BLAST-like similarity search. An evaluation of this method for use in real BLAST-like searches is presented along with a characterization of the quality of results associated with using these new algorithms in specialized hardware. The primary focus of this thesis is the design of the ungapped extension stage of Mercury BLAST. The architecture of the ungapped extension stage is described along with the context of this stage within the Mercury BLAST system. The design is compact and performs over 20× faster than that of the standard software ungapped extension, yielding close to 50× speedup over the complete software BLAST application. The quality of Mercury BLAST results is essentially equivalent to the standard BLAST results

On the Feasibility and Limitations of Just-in-Time Instruction Set Extension for FPGA-Based Reconfigurable Processors

Reconfigurable instruction set processors provide the possibility of tailor the instruction set of a CPU to a particular application. While this customization process could be performed during runtime in order to adapt the CPU to the currently executed workload, this use case has been hardly investigated. In this paper, we study the feasibility of moving the customization process to runtime and evaluate the relation of the expected speedups and the associated overheads. To this end, we present a tool flow that is tailored to the requirements of this just-in-time ASIP specialization scenario. We evaluate our methods by targeting our previously introduced Woolcano reconfigurable ASIP architecture for a set of applications from the SPEC2006, SPEC2000, MiBench, and SciMark2 benchmark suites. Our results show that just-in-time ASIP specialization is promising for embedded computing applications, where average speedups of 5x can be achieved by spending 50 minutes for custom instruction identification and hardware generation. These overheads will be compensated if the applications execute for more than 2 hours. For the scientific computing benchmarks, the achievable speedup is only 1.2x, which requires significant execution times in the order of days to amortize the overheads

Active data structures on GPGPUs

Active data structures support operations that may affect a large number of elements of an aggregate data structure. They are well suited for extremely fine grain parallel systems, including circuit parallelism. General purpose GPUs were designed to support regular graphics algorithms, but their intermediate level of granularity makes them potentially viable also for active data structures. We consider the characteristics of active data structures and discuss the feasibility of implementing them on GPGPUs. We describe the GPU implementations of two such data structures (ESF arrays and index intervals), assess their performance, and discuss the potential of active data structures as an unconventional programming model that can exploit the capabilities of emerging fine grain architectures such as GPUs