ACM TECS CAPA’09 Special Issue
Configuring Algorithms, Processes and Architecture
Guest Editor: London, UK
Associate Guest Editors:
Univ. of Central Florida, USA
Wright State Univ., USA
Virginia Tech., USA
Univ. of Paderborn, Germany
List of accepted papers
Hierarchical Benchmark Circuit Generation for FPGA Architecture Evaluation
*University of British Columbia, Canada; **Simon Fraser University, Canada
We describe a stochastic circuit generator that can be used to automatically create benchmark circuits for use in FPGA architecture studies. The circuits consist of a hierarchy of interconnected modules, reflecting the structure of circuits designed using a system-on-chip design flow. Within each level of hierarchy, modules can be connected in a bus, star, or dataflow configuration. Our circuit generator is calibrated based on a careful study of existing system-on-chip circuits. We show that our benchmark circuits lead to more realistic architectural conclusions than circuits generated using previous generators.
RapidRadio: Signal Classification and Radio Deployment Framework
Virginia Polytechnic Institute and State University, USA
The RapidRadio framework is a productivity enhancing tool that reduces the required knowledge-base for implementing a receiver on an FPGA-based SDR platform. The objective of this framework is to identify unknown signals and to build FPGA-based receivers capable of receiving them. RapidRadio divides the process of radio creation into two phases; the analysis phase and radio synthesis phase. The analysis phase guides the user through the process of classifying a signal and determining its modulation scheme and parameters, resulting in a radio receiver model. In the second phase, this model is transformed into a functional receiver in an FPGA-based platform.
RCML: An Environment for Estimation Modeling of Reconfigurable Computing Systems
NSF Center for High-performance Reconfigurable Computing (CHREC), University of Florida, Gainesville, FL, USA
Reconfigurable computing (RC) is emerging as a promising field for embedded computing, where complex systems must balance performance, flexibility, cost, and power consumption. The difficulty associated with RC development suggests improved strategic planning and analysis techniques can save designers significant development time and effort. This article presents an abstract modeling environment called the RC Modeling Language (RCML) to facilitate efficient design-space exploration of RC systems at the estimation modeling level, i.e. before building a functional implementation. Two integrated analysis tools and case studies, one analytical and one simulative, are presented illustrating relatively accurate automated analysis of systems modeled in RCML.
Architecture Optimization of Dynamically Configured Application-Specific Implicit Instructions
Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy
Dynamic configuration of application specific implicit instructions has been proposed to better exploit the available parallelism in pipelined processors. This requires the pipeline to be extended with a trigger table that describes the instruction implicitly issued as a response to a value written into a triggering register. In this paper, we explore the design optimization of the trigger table to maximize the number of instructions that can be implicitly issued while keeping limited the size of the trigger table. The proposed solutions have been applied to the case of a baseline scalar MIPS processor obtaining an average speedup of 17%.
Multi-Core Reconfigurable Computing for Advanced Video Coding
National Cheng Kung University, Department Of Electrical Engineering, Tainan,Taiwan
Computational load of motion estimation in advanced video coding standard is significantly high and even worse for HDTV and super-resolution sequences. In this paper, video processing algorithm is dynamically mapped onto a new parallel reconfigurable computing (PRC) architecture, which consists of multiple dynamic reconfigurable computing (DRC) units. We construct a directed acyclic graph (DAG) to represent video coding algorithms, in which motion estimation is focused. A novel parallel partition approach is then proposed to map motion estimation DAG onto the multiple DRC units in a PRC system. This speeds up the video processing with minimum sacrifice.