Web-based programming exercises are a useful way for students to practice and master essential concepts and techniques presented in introductory programming courses. Although these systems are used fairly widely, we have a limited understanding of how students use these systems, and what can be learned from the data collected by these systems.

The search for homologous RNA molecules---sequences of RNA that might behave simiarly due to similarity in their physical (secondary) structure---is currently a computationally intensive task. Moreover, RNA sequences are populating genome databases at a pace unmatched by gains in standard processor performance. While software tools such as Infernal can efficiently find homologies among RNA families and genome databases of modest size, the continuous advent of new RNA families and the explosive growth in volume of RNA sequences necessitate a faster approach. This work introduces two different architectures for accelerating the task of finding homologous RNA molecules in a genome database. The first architecture takes advantage of the tree-like configuration of the covariance models used to represent the consensus secondary structure of an RNA family and converts it directly into a highly-pipelined processing engine. Results for this architecture show a 24× speedup over Infernal when processing a small RNA model. It is estimated that the architecture could potentially offer several thousands of times speedup over Infernal on larger models, provided that there are sufficient hardware resources available. The second architecture is introduced to address the steep resource requirements of the first architecture. It utilizes a uniform array of processing elements and schedules all of the computations required to scan for an RNA homolog onto those processing elements. The estimated speedup for this architecture over the Infernal software package ranges from just under 20× to over 2,350×.

This article presents a dense logic design for matching multiple regular expressions with a field programmable gate array (FPGA) at 10+ Gbps. It leverages on the design techniques that enforce the shortest critical path on most FPGA architectures while optimizing the circuit size. The architecture is capable of supporting a maximum throughput of 12.90 Gbps on a Xilinx Virtex 4 LX200 and its performance is linearly scalable with size. Additionally, this article presents techniques for parsing data streams to provide semantic information for patterns found within a data stream. We illustrate how a content-based router can be implemented with our parsing techniques using an XML parser as an example. The content-based router presented was designed, implemented, and tested in a Xilinx Virtex XCV2000E FPGA on the FPX platform. It is capable of processing 32-bits of data per clock cycle and runs at 100 MHz. This allows the system to process and route XML messages at 3.2 Gbps.

A growing number of embedded computing systems are used outside of environmentally controlled locations. In locations such as remote parts of deserts, deep ocean floors, and outer space, it is not only difficult to predict environmental effects on a system, they also allow very limited accessibility once a system is deployed. Therefore, it is often necessary for system parameters to be over provisioned to guarantee correct functionality under worst case environmental conditions. This often leads to an end system that is suboptimal for typical conditions.

A biological organism's ability to sense and adapt to its environment is essential to its survival. Likewise, environmentally aware computing systems avail themselves to a longer operational life and a wider range of applications than traditional systems. In this paper, we propose a novel circuit design methodology that allows parameterizable hardware to self-regulate its temperature. We apply this methodology to an image recognition system on an Xilinx Virtex 4 FX100 field programmable gate array (FPGA). The image recognition system sustains a safe operational temperature by automatically adjusting its frequency and output quality. The circuit sacrifices output performance and quality to lower its internal temperature as the ambient temperature increases, and can leverage cooler temperatures by increasing output performance and quality. Furthermore, the circuit will shutdown if the ambient temperature becomes too hot for the device to function properly. A performance evaluation of our adaptive circuit under various thermal conditions shows up to a 4× factor increase in performance and a 2× factor increase in quality over a system without dynamic thermal control.

In this paper, the authors present a reconfigurable hardware architecture for searching for regular expression patterns in streaming data. This new architecture is created by combining two popular pattern matching techniques: a pipelined character grid architecture (Baker, 2004), and a regular expression NFA architecture (Cho, 2006). The resulting hybrid architecture can scale the number of input characters while still maintaining the ability to scan for regular expression patterns

We present a high performance reconfigurable hardware architecture for detecting patterns as well as their contextual meaning. By analyzing for both semantic content and structure, the accuracy of content-level processing systems can be improved. Our system is built using semantics defined by context-free-grammar (CFG) to tag the streaming data. Unlike the traditional table look up and stack based engines used in CFG parsers, we explore a new method that maps the grammar structure on to the Field Programmable Gate Arrays (FPGA) hardware. The structure is a direct translation of the grammar which enables the meaning of the patterns to be determined based on the location of its detection. The parallel pattern detection engines are instantiated using FPGA resources. Our implementation scans for the regular expression patterns and determines their semantics as defined by a grammar. This highly parallel and fine grained pipelined engine with 8 bit input bus can operate in bandwidth above 2 Gbps. For a simple XML grammar example, our engine can detect and tag the patterns at 1.57 Gbps on Xilinx VirtexE FPGA and 4.26 Gbps on the new Virtex 4 devices.

This paper presents an implementation of a high-performance network application layer parser in FPGAs. At the core of the architecture resides a pattern matcher and a parser. The pattern matcher scans for patterns in high-speed streaming TCP data streams. The parser core augments each pattern found with semantic information determined from the patterns location within the data stream. The packet payload parser can provide a higher level of understanding of a data stream for many network applications. Such applications include high performance XML parsers, content-based/aware routers, and others. Additionally, a TCP processor allows stateful packet payload parsing of up to 8 million simultaneous TCP flows. The payload parser has been implemented in a Xilinx Virtex E 2000 FPGA on the Field-Programmable Port Extender platform. The parsing module runs at 200 MHz and parse raw data at 6.4 Gbps. The payload parser, integrated with the TCP processor, runs at 100 MHz for a throughput of 3.2 Gbps

This paper presents an architecture for context-free grammar (CFG) based data processing hardware for re-configurable devices. Our system leverages on CFGs to tokenize and parse data streams into a sequence of words with corresponding semantics. Such a tokenizing and parsing engine is sufficient for processing grammatically correct input data. However, most pattern recognition applications must consider data sets that do not always conform to the predefined grammar. Therefore, we augment our system to detect and recover from grammatical errors while extracting useful information. Unlike the table look up method used in traditional CFG parsers, we map the structure of the grammar rules directly onto the field programmable gate array (FPGA). Since every part of the grammar is mapped onto independent logic, the resulting design is an efficient parallel data processing engine. To evaluate our design, we implement several XML parsers in an FPGA. Our XML parsers are able to process the full content of the packets up to 3.59 Gbps on Xilinx Virtex 4 devices

A circuit and an associated lightweight protocol have been developed to secure communication between a control console and remote programmable network devices. The circuit provides encryption, data integrity checking and sequence number verification to ensure confidentiality, integrity and authentication of control messages sent over the public Internet. All of these functions are performed directly in FPGA hardware to provide high throughput and near-zero latency. The circuit has been used to control and configure remote firewalls and intrusion detection systems. The circuit could also be used to control and configure other distributed network applications.

A module has been implemented in Field Programmable Gate Array (FPGA) hardware that scans the content of Internet packets at Gigabits/second rates. All of the packet processing operations are performed using reconfigurable hardware within a single Xilinx Virtex XCV2000E FPGA. A set of layered protocol wrappers is used to parse the headers and payloads of packets for Internet protocol data. A content matching server automatically generates the Finite State Machines (FSMs) to search for regular expressions. The complete system is operated on the Field-programmable Port Extender (FPX) platform.