Data Acquisition Applications

Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book

Compiler and Architecture Design for Coarse-Grained Programmable Accelerators

abstract: The holy grail of computer hardware across all market segments has been to sustain performance improvement at the same pace as silicon technology scales. As the technology scales and the size of transistors shrinks, the power consumption and energy usage per transistor decrease. On the other hand, the transistor density increases significantly by technology scaling. Due to technology factors, the reduction in power consumption per transistor is not sufficient to offset the increase in power consumption per unit area. Therefore, to improve performance, increasing energy-efficiency must be addressed at all design levels from circuit level to application and algorithm levels. At architectural level, one promising approach is to populate the system with hardware accelerators each optimized for a specific task. One drawback of hardware accelerators is that they are not programmable. Therefore, their utilization can be low as they perform one specific function. Using software programmable accelerators is an alternative approach to achieve high energy-efficiency and programmability. Due to intrinsic characteristics of software accelerators, they can exploit both instruction level parallelism and data level parallelism. Coarse-Grained Reconfigurable Architecture (CGRA) is a software programmable accelerator consists of a number of word-level functional units. Motivated by promising characteristics of software programmable accelerators, the potentials of CGRAs in future computing platforms is studied and an end-to-end CGRA research framework is developed. This framework consists of three different aspects: CGRA architectural design, integration in a computing system, and CGRA compiler. First, the design and implementation of a CGRA and its instruction set is presented. This design is then modeled in a cycle accurate system simulator. The simulation platform enables us to investigate several problems associated with a CGRA when it is deployed as an accelerator in a computing system. Next, the problem of mapping a compute intensive region of a program to CGRAs is formulated. From this formulation, several efficient algorithms are developed which effectively utilize CGRA scarce resources very well to minimize the running time of input applications. Finally, these mapping algorithms are integrated in a compiler framework to construct a compiler for CGRADissertation/ThesisDoctoral Dissertation Computer Science 201

DESIGNING COST-EFFECTIVE COARSE-GRAINED RECONFIGURABLE ARCHITECTURE

Application-specific optimization of embedded systems becomes inevitable to satisfy the market demand for designers to meet tighter constraints on cost, performance and power. On the other hand, the flexibility of a system is also important to accommodate the short time-to-market requirements for embedded systems. To compromise these incompatible demands, coarse-grained reconfigurable architecture (CGRA) has emerged as a suitable solution. A typical CGRA requires many processing elements (PEs) and a configuration cache for reconfiguration of its PE array. However, such a structure consumes significant area and power. Therefore, designing cost-effective CGRA has been a serious concern for reliability of CGRA-based embedded systems. As an effort to provide such cost-effective design, the first half of this work focuses on reducing power in the configuration cache. For power saving in the configuration cache, a low power reconfiguration technique is presented based on reusable context pipelining achieved by merging the concept of context reuse into context pipelining. In addition, we propose dynamic context compression capable of supporting only required bits of the context words set to enable and the redundant bits set to disable. Finally, we provide dynamic context management capable of reducing reduce power consumption in configuration cache by controlling a read/write operation of the redundant context words In the second part of this dissertation, we focus on designing a cost-effective PE array to reduce area and power. For area and power saving in a PE array, we devise a costeffective array fabric addresses novel rearrangement of processing elements and their interconnection designs to reduce area and power consumption. In addition, hierarchical reconfigurable computing arrays are proposed consisting of two reconfigurable computing blocks with two types of communication structure together. The two computing blocks have shared critical resources and such a sharing structure provides efficient communication interface between them with reducing overall area. Based on the proposed design approaches, a CGRA combining the multiple design schemes is shown to verify the synergy effect of the integrated approach. Experimental results show that the integrated approach reduces area by 23.07% and power by up to 72% when compared with the conventional CGRA