Coarse-grained reconfigurable array architectures

Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code

ASAM : Automatic Architecture Synthesis and Application Mapping; dl. 3.2: Instruction set synthesis

No abstract

A High Performance Fuzzy Logic Architecture for UAV Decision Making

The majority of Unmanned Aerial Vehicles (UAVs) in operation today are not truly autonomous, but are instead reliant on a remote human pilot. A high degree of autonomy can provide many advantages in terms of cost, operational resources and safety. However, one of the challenges involved in achieving autonomy is that of replicating the reasoning and decision making capabilities of a human pilot. One candidate method for providing this decision making capability is fuzzy logic. In this role, the fuzzy system must satisfy real-time constraints, process large quantities of data and relate to large knowledge bases. Consequently, there is a need for a generic, high performance fuzzy computation platform for UAV applications. Based on Lees’ [1] original work, a high performance fuzzy processing architecture, implemented in Field Programmable Gate Arrays (FPGAs), has been developed and is shown to outclass the performance of existing fuzzy processors

Reconfigurable Architectures for Wireless Systems: Design Exploration and Integration Challenges

Mobile devices are severely power and area limited due to battery capacity and system size. In many of these example systems, advanced features require computationally complex signal processing on high-speed data streams for enhanced networking capabilities. Thus, mapping high-level communication and networking algorithms to system architectures is a complex and challenging procedure. An important challenge is to characterize the area, time, and power requirements of these embedded system modules and to use this information effectively to determine the architecture of programmable, reconfigurable, and fixed-function modules. In this paper, we will focus on application examples in wireless networking which highlight these challenges in reconfigurable systems integration.Nokia CorporationTexas Instruments IncorporatedNational Science Foundatio

A Comparative Study of Scheduling Techniques for Multimedia Applications on SIMD Pipelines

Parallel architectures are essential in order to take advantage of the parallelism inherent in streaming applications. One particular branch of these employ hardware SIMD pipelines. In this paper, we analyse several scheduling techniques, namely ad hoc overlapped execution, modulo scheduling and modulo scheduling with unrolling, all of which aim to efficiently utilize the special architecture design. Our investigation focuses on improving throughput while analysing other metrics that are important for streaming applications, such as register pressure, buffer sizes and code size. Through experiments conducted on several media benchmarks, we present and discuss trade-offs involved when selecting any one of these scheduling techniques.Comment: Presented at DATE Friday Workshop on Heterogeneous Architectures and Design Methods for Embedded Image Systems (HIS 2015) (arXiv:1502.07241

Cognitive Radio Programming: Existing Solutions and Open Issues

Software defined radio (sdr) technology has evolved rapidly and is now reaching market maturity, providing solutions for cognitive radio applications. Still, a lot of issues have yet to be studied. In this paper, we highlight the constraints imposed by recent radio protocols and we present current architectures and solutions for programming sdr. We also list the challenges to overcome in order to reach mastery of future cognitive radios systems.La radio logicielle a évolué rapidement pour atteindre la maturité nécessaire pour être mise sur le marché, offrant de nouvelles solutions pour les applications de radio cognitive. Cependant, beaucoup de problèmes restent à étudier. Dans ce papier, nous présentons les contraintes imposées par les nouveaux protocoles radios, les architectures matérielles existantes ainsi que les solutions pour les programmer. De plus, nous listons les difficultés à surmonter pour maitriser les futurs systèmes de radio cognitive

LTE implementation on CGRA based SiLago Platform

Abstract. This thesis implements long term evolution (LTE) transmission layer on a coarse grained reconfigurable called, dynamically reconfigurable resource array (DRRA). Specifically, we implement physical downlink shared channel baseband signal processing blocks (PDSCH) at high level. The overall implementation follows silicon large grain object (SiLago) design methodology. The methodology employs SiLago blocks instead of mainstream standard cells. The main ambition of this thesis was to prove that a standard as complex as LTE can be implemented using the in-house SiLago framework. The work aims to prove that customized design with efficiency close to application specific integrated circuit (ASIC) for LTE can be generated with the programming ease of MATLAB. During this thesis, we have generated a completely parametrizable LTE standard at high level