Dynamic Scheduling, Allocation, and Compaction Scheme for Real-Time Tasks on FPGAs

Run-time reconfiguration (RTR) is a method of computing on reconfigurable logic, typically FPGAs, changing hardware configurations from phase to phase of a computation at run-time. Recent research has expanded from a focus on a single application at a time to encompass a view of the reconfigurable logic as a resource shared among multiple applications or users. In real-time system design, task deadlines play an important role. Real-time multi-tasking systems not only need to support sharing of the resources in space, but also need to guarantee execution of the tasks. At the operating system level, sharing logic gates, wires, and I/O pins among multiple tasks needs to be managed. From the high level standpoint, access to the resources needs to be scheduled according to task deadlines. This thesis describes a task allocator for scheduling, placing, and compacting tasks on a shared FPGA under real-time constraints. Our consideration of task deadlines is novel in the setting of handling multiple simultaneous tasks in RTR. Software simulations have been conducted to evaluate the performance of the proposed scheme. The results indicate significant improvement by decreasing the number of tasks rejected

ASC: A stream compiler for computing with FPGAs

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Regular Datapaths on Field-Programmable Gate Arrays

Field-Programmable Gate Arrays (FPGAs) are a recent kind of programmable logic device. They allow the implementation of integrated digital electronic circuits without requiring the complex optical, chemical and mechanical processes used in a conventional chip fabrication. FPGAs can be embedded in traditional system designflows to perform prototyping and emulation tasks. In addition, they also enable novel applications such as configurable computers with hardware dynamically adaptable to a specific problem. The growing chip capacity now allows even the implementation of CPUs and DSPs on single FPGAs. However, current design automation tools trace their roots to times of very limited FPGA sizes, and are primarily optimized for the implementation of random glue logic. The wide datapaths common to CPUs and DSPs are only processed with reduced performance. This thesis presents Structured Design Implementation (SDI), a suite of specialized tools coordinated by a common strategy, which aims to efficiently map even larger regular datapaths to FPGAs. In all steps, regularity is preserved whenever possible, or restored after disruptive operations were required. The circuits are composed from parametrizable modules providing a variety of logical, arithmetical and storage functions. For each module, multiple target FPGA-specific implementation alternatives may be generated in both gatelevel netlist and layout views. A floorplanner based on a genetic algorithm is then used to simultaneously choose an actual implementation from the set of alternatives for each module, and to arrange the selected module implementations in a linear placement. The floorplanning operation optimizes for short routing delays, high routability, and fit into the target FPGA.Field-Programmable Gate-Arrays (FPGAs) sind eine noch junge Art von programmierbaren Logikbausteinen. Sie erlauben die Implementierung von integrierten Digitalschaltungen ohne die komplizierten optischen, chemischen und mechanischen Prozesse, die normalerweise für die Chipfertigung erforderlich sind. FPGAs können im Rahmen konventioneller Entwurfsmethoden zu Emulationszwecken und Prototyp-Aufbauten herangezogen werden. Sie erlauben aber auch völlig neue Anwendungen wie rekonfigurierbare Computer, deren Hardware dynamisch an ein spezielles Problem angepaßt werden kann. Die gewachsene Chip-Kapazität erlaubt nun sogar die Implementierung von CPUs und digitalen Signalprozessoren (DSPs) auf einem einzelnen FPGA. Die Leistungsfähigkeit der entstandenen Schaltungen wird jedoch durch die zur Zeit erhältlichen CAD-Werkzeuge limitiert, da diese noch auf stark beschränkte FPGA-Größen ausgerichtet sind und primär der platzsparenden Verarbeitung unregelmäßiger Logik dienen. Die breiten Datenpfade in Bit-Slice-Struktur, die den Kern vieler CPUs und DSPs darstellen, werden nur suboptimal behandelt. Diese Arbeit stellt Structured Design Implementation (SDI) vor, ein System von spezialisierten CAD-Werkzeugen, die auch größere reguläre Datenpfade effizient auf FPGAs abbilden. In allen Verarbeitungsschritten wird dabei die bestehende Regularität soweit wie möglich erhalten oder nach regularitätsvernichtenden Operationen wiederhergestellt. Zur Schaltungseingabe steht eine Bibliothek von allgemeinen Modulen aus den Bereichen Logik, Arithmetik und Speicherung bereit. Diese können durch Belegung verschiedener Parameter wie Bit-Breiten und Datentypen an aktuelle Anforderungen angepaßt werden

Implementation of Viterbi decoder on Xilinx XC4005XL FPGA

The Viterbi decoding algorithm is used to decode convolutional codes and is found in many systems that receive digital data that might contain errors. The use of error-correcting codes has proven tobe an effective way to overcome data corruption in digital communication channels. In previous works, researchers describe the Viterbi Algorithm, but the accuracy does not exceed 10% of data points. Also, a lot of previous works do not follow IEEE 802.16 new specifications. Viterbi decoders are generally implemented using programmable digital signal processors (DSPs) or special purpose chip sets and application-specific integrated circuits (ASICs). Here, we aim to implement such decoder on an FPGA. In This paper, we provide a more accurate Viterbi decoder according to IEEE 802.16 specifications. We used VHDL hardware description language to implement the algorithm. We also used OrCAD Capture V9.1 to compile, synthesize, and simulate our code. IEEE 802.16 standard specifies the air interface of fixed point-to-multipoint broadband wireless access (BWA) systems providing multiple services. This standard is intended to enable rapid worldwide deployment of broadband wireless access products. The new IEEE 802.16 specifications require a Viterbi block decoder with constraint length of 3, traceback length of 32, and minimum throughput requirement of 44.8 Mbps. The Implementation parameters for the decoder have been determined through simulation and the decoder has been implemented on a Xilinx XC4005XL FPGA

Fault-Tolerant FPGA-Based Systems

This paper presents a new approach to on-line fault tolerance via reconfiguration for the systems mapped onto field programmable gate arrays (FPGAs). The fault detection, based on self-checking technique, is introduced at application level; therefore our approach can detect the faults of configurable logic blocks (CLBs) and routing interconnections in the FPGAs concurrently with the normal system work. A grid of tiles is projected on the FPGA structure and a certain number of spare CLBs is reserved inside every tile. The number of spare CLBs per tile, which will be used as a backup upon detecting any faulty CLB, is estimated in accordance with the probability of failure. After locating the faulty CLBs, the faulty tile will be reconfigured with avoiding the faulty CLBs. Our proposed approach uses a combination of hardware and software redundancy. We assume that a module external to the FPGA controls automatically the reconfiguration process in addition to the diagnosis process (DIRC); typically this is an embedded microprocessor having some storage for the various tile configurations. We have implemented our approach using Xilinx Virtex FPGA. The DIRC code is written in JBits software tools. In response to a component failure this approach capitalizes on the unique reconfiguration capabilities of FPGAs and replaces the affected tile with a functionally equivalent one that does not rely on the faulty component. Unlike fixed structure fault-tolerance techniques for ASICs and microprocessors, this approach allows a single physical component to provide redundant backup for several types of components

Compiling dataflow graphs into hardware

Department Head: L. Darrell Whitley.2005 Fall.Includes bibliographical references (pages 121-126).Conventional computers are programmed by supplying a sequence of instructions that perform the desired task. A reconfigurable processor is "programmed" by specifying the interconnections between hardware components, thereby creating a "hardwired" system to do the particular task. For some applications such as image processing, reconfigurable processors can produce dramatic execution speedups. However, programming a reconfigurable processor is essentially a hardware design discipline, making programming difficult for application programmers who are only familiar with software design techniques. To bridge this gap, a programming language, called SA-C (Single Assignment C, pronounced "sassy"), has been designed for programming reconfigurable processors. The process involves two main steps - first, the SA-C compiler analyzes the input source code and produces a hardware-independent intermediate representation of the program, called a dataflow graph (DFG). Secondly, this DFG is combined with hardware-specific information to create the final configuration. This dissertation describes the design and implementation of a system that performs the DFG to hardware translation. The DFG is broken up into three sections: the data generators, the inner loop body, and the data collectors. The second of these, the inner loop body, is used to create a computational structure that is unique for each program. The other two sections are implemented by using prebuilt modules, parameterized for the particular problem. Finally, a "glue module" is created to connect the various pieces into a complete interconnection specification. The dissertation also explores optimizations that can be applied while processing the DFG, to improve performance. A technique for pipelining the inner loop body is described that uses an estimation tool for the propagation delay of the nodes within the dataflow graph. A scheme is also described that identifies subgraphs with the dataflow graph that can be replaced with lookup tables. The lookup tables provide a faster implementation than random logic in some instances

Automatic mapping of graphical programming applications to microelectronic technologies

Adaptive computing systems (ACSs) and application-specific integrated circuits (ASICs) can serve as flexible hardware accelerators for applications in domains such as image processing and digital signal processing. However, the mapping of applications onto ACSs and ASICs using the traditional methods can take months for a hardware engineer to develop and debug. In this dissertation, a new approach for automatic mapping of software applications onto ACSs and ASICs has been developed, implemented and validated. This dissertation presents the design flow of the software environment called CHAMPION, which is being developed at the University of Tennessee. This environment permits high-level design entry using the Cantata graphical programming software fromKRI. Using Cantata as the design entry, CHAMPION hides from the user the low-level details of the hardware architecture and the finer issues of application mapping onto the hardware. Validation of the CHAMPION environment was performed using multiple applications of moderate complexity. In one case, theapplication mapping time which required six weeks to perform manually took only six minutes for CHAMPION, yet comparable results were produced. Furthermore, the CHAMPION environment was constructed such that retargeting to a new adaptive computing system could be accomplished in just a few hours as opposed to weeks using manual methods. Thus, CHAMPION permits both ACSs and ASICs to be utilized by a wider audience and application development accomplished in less time

Obtaining performance and programmability using reconfigurable hardware for media processing

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2002.Includes bibliographical references (p. 127-132).An imperative requirement in the design of a reconfigurable computing system or in the development of a new application on such a system is performance gains. However, such developments suffer from long-and-difficult programming process, hard-to-predict performance gains, and limited scope of applications. To address these problems, we need to understand reconfigurable hardware's capabilities and limitations, its performance advantages and disadvantages, re-think reconfigurable system architectures, and develop new tools to explore its utility. We begin by examining performance contributors at the system level. We identify those from general-purpose and those from dedicated components. We propose an architecture by integrating reconfigurable hardware within the general-purpose framework. This is to avoid and minimize dedicated hardware and organization for programmability. We analyze reconfigurable logic architectures and their performance limitations. This analysis leads to a theory that reconfigurable logic can never be clocked faster than a fixed-logic design based on the same fabrication technology. Though highly unpredictable, we can obtain a quick upper bound estimate on the clock speed based on a few parameters. We also analyze microprocessor architectures and establish an analytical performance model. We use this model to estimate performance bounds using very little information on task properties. These bounds help us to detect potential memory-bound tasks. For a compute-bound task, we compare its performance upper bound with the upper bound on reconfigurable clock speed to further rule out unlikely speedup candidates.(cont.) These performance estimates require very few parameters, and can be quickly obtained without writing software or hardware codes. They can be integrated with design tools as front end tools to explore speedup opportunities without costly trials. We believe this will broaden the applicability of reconfigurable computing.by Ling-Pei Kung.Ph.D

Hardware implementation of intelligent systems

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