Power consumption benchmarking for reconfigurable platforms

Software defined radios (SDR) wideband mobile terminals must be capable of data processing while consuming low power and keeping the design and manufacturing costs as low as possible. SDR can combine high performance signal processing and flexibility, but power efficiency of SDR nodes is an issue that needs to be addressed. Analysis of power consumption for various target technologies is challenging, since each technology typically contains its own benchmarking tools and thus, results are not comparable. In this paper, we illustrate how the GroundHog2009 benchmark suite, designed to be platform independent, can be used to evaluate power dissipation of four modern FPGAs and one microcontroller. We also introduce a generic RTL library for the GroundHog2009 design cases and test bench infra-structure to make the toolset usage easy. In addition, we show that power can be saved by using clock management, available on one of the FGPA-boards. The power savings range from 38 to 1,150?%.     

A framework for reconfigurable computing: task scheduling andcontext management

Dynamically reconfigurable architectures are emerging as a viable design alternative to implement a wide range of computationally intensive applications. At the same time, an urgent necessity has arisen for support tool development to automate the design process and achieve optimal exploitation of the architectural features of the system. Task scheduling and context (configuration) management become very critical issues in achieving the high performance that digital signal processing (DSP) and multimedia applications demand. This article proposes a strategy to automate the design process which considers all possible optimizations that can be carried out at compilation time, regarding context and data transfers. This strategy is general in nature and could be applied to different reconfigurable systems. We also discuss the key aspects of the scheduling problem in a reconfigurable architecture such as MorphoSys. In particular, we focus on a task scheduling methodology for DSP and multimedia applications, as well as the context management and scheduling optimizations     

A soft radio architecture for reconfigurable platforms

While many soft/software radio architectures have been suggested and implemented, there remains a lack of a formal design methodology that can be used to design and implement these radios. This article presents a unified architecture for the design of soft radios on a reconfigurable platform called the layered radio architecture. The layered architecture makes it possible to incorporate all of the features of a software radio while minimizing complexity issues. The layered architecture also enables a methodology for incorporating changes and updates into the system. An example implementation of the layered architecture on actual hardware is presented     

System-level power-performance tradeoffs for reconfigurable computing

In this paper, we propose a configuration-aware data-partitioning approach for reconfigurable computing. We show how the reconfiguration overhead impacts the data-partitioning process. Moreover, we explore the system-level power-performance tradeoffs available when implementing streaming embedded applications on fine-grained reconfigurable architectures. For a certain group of streaming applications, we show that an efficient hardware/software partitioning algorithm is required when targeting low power. However, if the application objective is performance, then we propose the use of dynamically reconfigurable architectures. We propose a design methodology that adapts the architecture and algorithms to the application requirements. The methodology has been proven to work on a real research platform based on Xilinx devices. Finally, we have applied our methodology and algorithms to the case study of image sharpening, which is required nowadays in digital cameras and mobile phones.     

Highly configurable platforms for embedded computing systems

Platform chips, which are pre-designed chips possessing numerous processors, memories, coprocessors, and field-programmable gates arrays, are becoming increasingly popular. Platforms eliminate the costs and risks associated with creating customized chips, but with the drawbacks of poorer performance and energy consumption. Making platforms highly configurable, so they can be tuned to the particular applications that will execute on those platforms, can help reduce those drawbacks. We discuss the trends leading embedded system designers towards the use of platforms instead of customized chips. We discuss UCR research in designing highly configurable platforms, highlighting some of our work in highly configurable caches, and in hardware/software partitioning.     

Configuration relocation and defragmentation for run-time reconfigurable computing

Due to its potential to greatly accelerate a wide variety of applications, reconfigurable computing has become a subject of a great deal of research. By mapping the compute-intensive sections of an application to reconfigurable hardware, custom computing systems exhibit significant speedups over traditional microprocessors. However, this potential acceleration is limited by the requirement that the speedups provided must outweigh the considerable cost of reconfiguration. The ability to relocate and defragment configurations on field programmable gate arrays (FPGAs) can dramatically decrease the overall reconfiguration overhead incurred by the use of the reconfigurable hardware. We therefore present hardware solutions to provide relocation and defragmentation support with a negligible area increase over a generic partially reconfigurable FPGA, as well as software algorithms for controlling this hardware. This results in factors of 8 to 12 improvement in the configuration overheads displayed by traditional serially programmed FPGAs.     

Solving satisfiability problems using reconfigurable computing

This paper reports on an innovative approach for solving satisfiability problems for propositional formulas in conjunctive normal form (SAT) by creating a logic circuit that is specialized to solve each problem instance on field programmable gate arrays (FPGAs). This approach has become feasible due to recent advances in reconfigurable computing and has opened up an exciting new research field in algorithm design. SAT is an important subclass of constraint satisfaction problems, which can formalize a wide range of application problems. We have developed a series of algorithms that are suitable for a logic circuit implementation, including an algorithm whose performance is equivalent to the Davis-Putnam procedure with powerful dynamic variable ordering. Simulation results show that this method can solve a hard random 3-SAT problem with 400 variables within 1.6 min at a clock rate of 10 MHz. Faster speeds can be obtained by increasing the clock rate. Furthermore, we have actually implemented a 128-variable 256-clause problem instance on FPGAs     

A reconfigurable multifunction computing cache architecture

A considerable portion of a microprocessor chip is dedicated to cache memory. However, not all applications need all the cache storage all the time, especially the computing bandwidth-limited applications. In addition, some applications have large embedded computations with a regular structure. Such applications may be able to use additional computing resources. If the unused portion of the cache could serve these computation needs, the on-chip resources would be utilized more efficiently. This presents an opportunity to explore the reconfiguration of a part of the cache memory for computing. Thus, we propose adaptive balanced computing (ABC)-dynamic resource configuration on demand from application-between memory and computing resources. In this paper, we present a cache architecture to convert a cache into a computing unit for either of the following two structured computations: finite impulse response and discrete/inverse discrete cosine transform. In order to convert a cache memory to a function unit, we include additional logic to embed multibit output lookup tables into the cache structure. The experimental results show that the reconfigurable module improves the execution time of applications with a large number of data elements by a factor as high as 50 and 60     

改进的移动计算平台直接匿名证明方案

分析了Ge等人提出的直接匿名证明方案的安全缺陷,指出该方案的认证协议在用于远程证明时不能抵抗重放攻击和平台伪装攻击。提出一种改进的直接匿名证明的认证协议,引入会话密钥协商机制,增强互认证功能。分析表明,改进方案在正确进行直接匿名证明的前提下,满足不可伪造性和匿名性,能够抵抗重放攻击和平台伪装攻击,协议性能满足移动计算平台的可信验证需求。     

软件无线电技术与可重配置计算体系结构

1.技术趋势 现代无线通信的主体是移动通信.参照ITU建议M1225,移动通信是在复杂多变的移动环境下工作的,因此必须考虑严重的时变和多径传播的影响.在现代无线通信系统中,特别是在码分多址(CDMA)系统中,为了提高系统容量,提高系统灵敏度和在较低的发射功率下获得较远的通信距离,一般都希望使用智能天线与联合检测技术.     

The research and design of reconfigurable computing for Block cipher

This paper describes a new specialized Reconfigurable Cryptographic for Block ciphers Architecture（RCBA）.Application-specific computation pipelines can be configured according to the characteristics of the block cipher processing in RCBA,which delivers high performance for cryptographic applications.RCBA adopts a coarse-grained reconfigurable architecture that mixes the appropriate amount of static configurations with dynamic configurations.RCBA has been implemented based on Altera’s FPGA,and representative algorithms of block cipher such as DES,Rijndael and RC6 have been mapped on RCBA architecture successfully.System performance has been analyzed,and from the analysis it is demonstrated that the RCBA architecture can achieve more flexibility and efficiency when compared with other implementations.     

基于随机模型的可重构计算芯片互连资源估计

在可重构计算芯片设计初期,确定芯片的各种互连资源数目是一个关键问题.如果设计的互连资源过少,可能导致应用领域中的部分算法无法实现,而过多的互连资源会造成芯片面积的浪费.基于可重构计算的特点,分析了可重构计算的相邻连接、路由连接和近邻连接三种类型互连资源.通过建立互连资源估计的随机模型,提出了可重构计算芯片中各种互连资源数目的估计方法.仿真结果表明,该方法能够比较准确地估计各种互连资源的数目,从而指导可重构计算互连资源的设计,降低设计风险.     

面向云计算平台的层次化性能问题诊断方法

提出一种层次式在线性能问题诊断方法——Magnifier,将用户请求执行路径划分为构件层、模块层和方法层3个层次,自顶向下逐层定位问题根源。基于阿里巴巴云计算平台的实验结果表明,Magnifier能够在调用方法种类多、执行路径复杂的条件下,快速定位出性能降级的主要原因。     

采用多核处理器进行可重构并行仿真的方法

文中对多传感器视觉信息处理算法进行分析,根据可重构处理器的并行计算参数模型提出了一种并行计算仿真的方法。多核处理器环境中,每个线程在独立的核上运行,线程间具有并发性。利用并发的线程模拟可重构阵列单元（PE）的运算方式,调用OpenMP设置多个线程并行执行,在多核计算机平台上模拟可重构处理器的计算过程。利用此方法能在没有具体的PE连接方案前,通过使用计算核模拟PE单元,将算法映射到多核处理器环境中。通过分析算法在多核计算机上的并发执行效率,来优化视觉信息算法在可重构阵列上的映射方案。     

Architecture for integrated telecommunication management platforms

Telecommunication management network (TMN) systems represent diverse telecommunication domains with wide-ranging functionality which frequently employ different technologies and produce isolated solutions. Yet as telecommunications become more sophisticated, there is a growing need for telecommunication management integration and interoperability. The authors present a general TMN computing-platform architecture which is flexible and powerful enough to support contrasting TMN management applications while facilitating integration. To validate the architecture, three diverse management applications were profiled based on components of the TMN platform architecture. Core infrastructure components, required by a broad range of TMN applications, are identified and examined and TMN-specific technology is highlighted     

FinFET CMOS logic gates with non-volatile states for reconfigurable computing systems

A series FinFET based non-volatile logic gates with multiple logic functions defined by embedded non-volatile states are proposed for the first time and demonstrated in advanced CMOS technology platform. The device channels in the proposed CMOS logic gate is controlled by a metal floating gate coupled by slot contacts uniquely available in the FinFET process employed in this study. The new logic gate with non-volatile states only enable reconfiguration ability in a Boolean computing unit at a gate level aimed for adaptive and specialized systems in the AI era. Furthermore, the extended applications in tunable ring oscillators for multi-functional IOT modules are successfully demonstrated in this study.     

Implementation and validation of architectural space exploration techniques for domain-specific reconfigurable computing

Domain specific coarse-grained reconfigurable architectures (CGRAs) have great promise for energy-efficient flexible designs for a suite of applications. Designing such a reconfigurable device for an application domain is very challenging because the needs of different applications must be carefully balanced to achieve the targeted design goals. It requires the evaluation of many potential architectural options to select an optimal solution. Exploring the design space manually would be very time consuming and may not even be feasible for very large designs. Even mapping one algorithm onto a customized architecture can require time ranging from minutes to hours. Running a full power simulation on a complete suite of benchmarks for various architectural options require several days. Finding the optimal point in a design space could require a very long time. We have designed a framework/tool that made such design space exploration (DSE) feasible. The resulting framework allows testing a family of algorithms and architectural options in minutes rather than days and can allow rapid selection of architectural choices. In this paper, we describe our DSE framework for domain specific reconfigurable computing where the needs of the application domain drive the construction of the device architecture. The framework has been developed to automate design space case studies, allowing application developers to explore architectural tradeoffs efficiently and reach solutions quickly. We selected some of the core signal processing benchmarks from the MediaBench benchmark suite and some edge-detection benchmarks from the image processing domain for our case studies. We describe two search algorithms: a stepped search algorithm motivated by our manual design studies and a more traditional gradient based optimization. Approximate energy models are developed in each case to guide the search toward a minimal energy solution. We validate our search results by comparing the architectural solutions selected by our tool to an architecture optimized manually and by performing sensitivity tests to evaluate the ability of our algorithms to find good quality minima in the design space. All selected fabric architectures were synthesized on 130 nm cell-based ASIC fabrication process from IBM. These architectures consume almost same amount of energy on average, but the gradient based approach is more general and promises to extend well to new problem domains. We expect these or similar heuristics and the overall design flow of the system to be useful for a wide range of architectures, including mesh based and other commonly used architectures for CGRAs.     

A framework for reconfigurable computing: task scheduling and context management-a summary

Reconfigurable computing is consolidating itself as a real alternative to ASICs (Application Specific Integrated Circuits) and general-purpose processors. The main advantage of reconfigurable computing derives from its unique combination of broad applicability, provided by the reconfiguration capability, and achievable performance, through the potential parallelism exploitation. The key aspects of the scheduling problem in a reconfigurable architecture are discussed, focusing on a task scheduling methodology for DSP and multimedia applications, as well as the context management and scheduling optimizations.     

Architecture,challenges and applications of dynamic reconfigurable computing

As a computing paradigm that combines temporal and spatial computations,dynamic reconfigurable computing provides superiorities of flexibility,energy efficiency and area efficiency,attracting interest from both academia and industry.However,dynamic reconfigurable computing is not yet mature because of several unsolved problems.This work introduces the concept,architecture,and compilation techniques of dynamic reconfigurable computing.It also discusses the existing major challenges and points out its potential applications.     

Integrated vehicle health management for aerospace platforms

This article introduces IVHM (integrated vehicle health management) fundamentals, identifies the primary challenges that face the aerospace IVHM developer, enumerates some of the approaches that are being integrated into Boeing products, and identifies key lessons learned that can be applied to new IVHM developments. Using automobile electronic systems for comparison, the following topics are discussed: diagnostic functions; prognostic functions; automated inspections; anomaly detection; aerospace systems complexity; affordability and interoperability; system lifespan requirements; operational and maintenance environments; market implications; practical application of IVHM techniques.