HW/SW for an intelligent transducer network based on IEEE 1451 standard

This work describes a hardware/software co-design system development, named IEEE 1451 platform, to be used in process automation. This platform intends to make easier the implementation of IEEE standards 1451.0, 1451.1, 1451.2 and 1451.5. The hardware was built using NIOS II processor resources on Alteras Cyclone II FPGA. The software was done using Java technology and C/C++ for the processors programming. This HW/SW system implements the IEEE 1451 based on a control module and supervisory software for industrial automation.     

Hardware/software co-design for particle swarm optimization algorithm

This paper presents a hardware/software (HW/SW) co-design approach using SOPC technique and pipeline design method to improve design flexibility and execution performance of particle swarm optimization (PSO) for embedded applications. Based on modular design architecture, a Particle Updating Accelerator module via hardware implementation for updating velocity and position of particles and a Fitness Evaluation module implemented either on a soft-cored processor or Field Programmable Gate Array (FPGA) for evaluating the objective functions are respectively designed to work closely together to carry out the evolution process at different design stages. Thanks to the design flexibility, the proposed approach can tackle various optimization problems of embedded applications without the need for hardware redesign. To further improve the execution performance of the PSO, a hardware random number generator (RNG) is also designed in this paper in addition to a particle re-initialization scheme to promote exploration search during the optimization process. Experimental results have demonstrated that the proposed HW/SW co-design approach for PSO algorithms has good efficiency for obtaining high-quality solutions for embedded applications.     

高效软硬件划分算法及其提升技术

软硬件划分是软硬件协同设计的关键环节,它决定系统中哪些组件由软件实现,哪些由硬件实现。软硬件划分问题已被证明是NP完全问题。将一类软硬件划分问题看作变异的0-1背包问题,在求解背包问题的算法基础上构造出软硬件划分问题的优质启发解。此外,采用禁忌搜索(Tabu Search)算法对求得的启发解进行改进,在软件开销和通信开销满足一定约束的条件下,使得硬件开销尽可能小。实验结果证明,所提算法对当前最新算法的改进最大可达到28%。     

HW/SW co-design for public-key cryptosystems on the 8051 micro-controller

It is a challenge to implement large word length public-key algorithms on embedded systems. Examples are smartcards, RF-ID tags and mobile terminals. This paper presents a HW/SW co-design solution for RSA and Elliptic Curve Cryptography (ECC) over GF(p) on a 12 MHz 8-bit 8051 micro-controller. The hardware coprocessor has a Modular Arithmetic Logic Unit (MALU) of which the digit size (d) is variable. It can be adapted to the speed and bandwidth of the micro-controller to which it is connected. The HW/SW co-design space exploration is based on the GEZEL system-level design environment. It allows the designer to find the best performance-area combination for the digit size. As a case study of an FPGA prototyping, 160-bit ECC over GF(p) (ECC-160p) was implemented on Xilinx Virtex-II PRO (XC2VP30). The results show that one point multiplication takes only 130 ms including all communications between the 8051 and the coprocessor. The performance is 40 times faster than the most optimized SW implementation on a small CPU in literature. This is achieved by the HW/SW co-design exploration in order to find the optimized digit size of the MALU. On the other hand, the design of ECC-160p maintains a high level of flexibility by using coprocessor instructions. Our proposed architecture proves that HW/SW co-design provides a high performance close to ASIC solutions with a flexible feature of SW even on a small CPU.     

一种基于动态二进制翻译的硬件支持Profile技术

传统的基于动态二进制翻译器的profiling策略分为3种:基于基本块、基于跳转边、基于路径跟踪。使用纯软件的profiling系统一般地说会带来平均30%的性能开销。如果在动态优化中得到硬件的支持,系统的整体性能将得到显著的提高。其中,软硬件协同设计中的难点,就是软硬件之间的通信开销和软硬件划分。该文针对动态二进制翻译中的优化阶段,使用一种硬件支持的运行是profile收集新方法来取代纯软件的profiling方法,把软硬件之间的通信开销降到最低,并以此来提高动态二进制翻译的整体性能。此方法可以在运行时准确地,并且以很小的开销收集Profile信息,从而更好的优化系统。     

多选择软硬件划分问题的计算模型与动态规划算法

软硬件划分是软硬件协同设计的关键环节,划分的结果直接影响目标系统的设计质量。因此,对于一个给定的应用程序,为了使得目标系统快速执行且成本低廉,合理的划分策略十分重要。由于单个任务具有多种不同的硬件实现方式,与传统的单一硬件实现方式的软硬件划分问题相比,多选择的软硬件划分更能客观地反映现实应用。这导致问题的求解更具挑战性,它们已被证明是NP完全问题。基于多核处理器片上系统并针对任务图为二叉树的应用,建立了多选择软硬件划分问题的计算模型,并提出了解决该问题的动态规划算法。实验结果表明,当问题规模适中时,所提动态规划算法能够有效地获得精确解,并展示了算法的计算能力与硬件面积限制之间的关系。     

An efficient GPU-based parallel tabu search algorithm for hardware/software co-design

Hardware/software partitioning is an essential step in hardware/software co-design. For large size problems, it is difficult to consider both solution quality and time. This paper presents an efficient GPU-based parallel tabu search algorithm (GPTS) for HW/SW partitioning. A single GPU kernel of compacting neighborhood is proposed to reduce the amount of GPU global memory accesses theoretically. A kernel fusion strategy is further proposed to reduce the amount of GPU global memory accesses of GPTS. To further minimize the transfer overhead of GPTS between CPU and GPU, an optimized transfer strategy for GPU-based tabu evaluation is proposed, which considers that all the candidates do not satisfy the given constraint. Experiments show that GPTS outperforms state-of-the-art work of tabu search and is competitive with other methods for HW/SW partitioning. The proposed parallelization is significant when considering the ordinary GPU platform.     

多核片上系统的高效软硬件划分及调度算法

软硬件划分与调度是软硬件协同设计的关键环节,是经典的组合优化问题。本文针对调度与软硬件划分问题提出一种高效的启发式算法。调度算法根据任务的出度及软件计算时间对任务赋予不同的优先级,出度越大,优先级越高,出度相同的情况下,软件计算时间越大,优先级越高。划分算法首先寻找关键路径,然后将关键路径上具有最高受益面积比的任务交由硬件去实现。每次迭代更新当前关键路径的调度长度及剩余硬件面积。继续循环,直到剩余的硬件面积不再满足关键路径上的任何一个软件任务所需的硬件面积的要求为止,这样使得硬件面积的使用率比较高。实验表明,该算法对已有算法的改进可达到38%。     

A Novel Hardware/Software Partitioning Method Based on Position Disturbed Particle Swarm Optimization with Invasive Weed Optimization

With the development of the design complexity in embedded systems, hardware/software (HW/SW) partitioning becomes a challenging optimization problem in HW/SW co-design. A novel HW/SW partitioning method based on position disturbed particle swarm optimization with invasive weed optimization (PDPSO-IWO) is presented in this paper. It is found by biologists that the ground squirrels produce alarm calls which warn their peers to move away when there is potential predatory threat. Here, we present PDPSO algorithm, in each iteration of which the squirrel behavior of escaping from the global worst particle can be simulated to increase population diversity and avoid local optimum. We also present new initialization and reproduction strategies to improve IWO algorithm for searching a better position, with which the global best position can be updated. Then the search accuracy and the solution quality can be enhanced. PDPSO and improved IWO are synthesized into one single PDPSO-IWO algorithm, which can keep both searching diversification and searching intensification. Furthermore, a hybrid NodeRank (HNodeRank) algorithm is proposed to initialize the population of PDPSO-IWO, and the solution quality can be enhanced further. Since the HW/SW communication cost computing is the most time-consuming process for HW/SW partitioning algorithm, we adopt the GPU parallel technique to accelerate the computing. In this way, the runtime of PDPSO-IWO for large-scale HW/SW partitioning problem can be reduced efficiently. Finally, multiple experiments on benchmarks from state-of-the-art publications and large-scale HW/SW partitioning demonstrate that the proposed algorithm can achieve higher performance than other algorithms.     

Algorithmic aspects for multiple-choice hardware/software partitioning

Hardware–software partitioning (HW/SW) divides an application into software and hardware. It is one of the crucial steps in embedded system design. For a given task, hardware with different areas may provide different execution speeds due to the potential of parallel execution in hardware implementation. Thus, one task may have multiple-choice in hardware implementation according to the available hardware areas. Existing HW/SW partitioning approaches typically consider only a single implementation manner in hardware, overlooking the multiple-choice of hardware implementations. This paper presents a computing model to cater for the HW/SW partitioning problems with the multiple-choice implementation in hardware. An efficient heuristic algorithm is proposed to rapidly generate approximate solution, that is further refined by a tabu search algorithm also customized in this paper. Moreover, a dynamic programming algorithm is proposed for the exact solution of the relatively small problems. Extensive simulation results show that the approximate solutions are very close to the exact ones, and they can be refined by tabu search to the solutions with the error no more than 1.5% for all cases considered in this paper.     

BOAR: an advanced HW/SW coemulation environment for DSP system development

The BOAR emulation system is targeted to hardware/software (HW/SW) codevelopment of advanced embedded DSP and telecom systems. The challenge of the BOAR system is efficient customization of programmable hardware, and dedicated partitioning routine to target applications and structures, which allows quite high overall system performance. The system allows multiple configurations for communication between processors and field programmable gate arrays (FPGAs) making the BOAR system an efficient tool for real-time HW/SW coverification. The reprogrammable hardware of the emulation tool is based on four Xilinx 4000-series devices, two Texas TMS320C50 signal processors and one Motorola MC68302 microcontroller. With current devices the BOAR hardware provides approximately 40–70 kgates of logic capacity in DSP applications. The emulation capacity can be expanded by connecting several similar boards in chain. The system has also a versatile internal reprogrammable test environment for test bench development, performance evaluations and design debugging. The logic development environment is based on the Synopsys synthesis tools and an automatic design management software, which performs resource mapping and performance-driven design partitioning between FPGAs. The emulation hardware is currently connected to logic and software development environments via an RS-232C bus. The BOAR emulation system has been found a very efficient platform for real-life prototyping of different types of DSP algorithms and systems, and validating correct functionality of a VHDL macro library.     

面向SoC的软硬件协同验证平台设计

针对SoC设计验证的实际需求,介绍一种面向SoC设计的软硬件协同验证平台。平台中软硬件模型分别在不同环境下运行,通过网络实现信息交互。硬件用硬件描述语言实现对系统事务级、RTL级的建模,软件用高级编程语言来编写,使用指令集仿真器完成对硬件的仿真。仿真过程使用不同的进程并行进行,应用进程间通信方式实现仿真器之间的信息交互。     

Real-time embedded systems powered by FPGA dynamic partial self-reconfiguration: a case study oriented to biometric recognition applications

This work aims to pave the way for an efficient open system architecture applied to embedded electronic applications to manage the processing of computationally complex algorithms at real-time and low-cost. The target is to define a standard architecture able to enhance the performance-cost trade-off delivered by other alternatives nowadays in the market like general-purpose multi-core processors. Our approach, sustained by hardware/software (HW/SW) co-design and run-time reconfigurable computing, is synthesizable in SRAM-based programmable logic. As proof-of-concept, a run-time partially reconfigurable field-programmable gate array (FPGA) is addressed to carry out a specific application of high-demanding computational power such as an automatic fingerprint authentication system (AFAS). Biometric personal recognition is a good example of compute-intensive algorithm composed of a series of image processing tasks executed in a sequential order. In our pioneer conception, these tasks are partitioned and synthesized first in a series of coprocessors that are then instantiated and executed multiplexed in time on a partially reconfigurable region of the FPGA. The implementation benchmark of the AFAS either as a pure software approach on a PC platform under a dual-core processor (Intel Core 2 Duo T5600 at 1.83 GHz) or as a reconfigurable FPGA co-design (identical algorithm partitioned in HW/SW tasks operating at 50 or 100 MHz on the second smallest device of the Xilinx Virtex-4 LX family) highlights a speed-up of one order of magnitude in favor of the FPGA alternative. These results let point out biometric recognition as a sensible killer application for run-time reconfigurable computing, mainly in terms of efficiently balancing computational power, functional flexibility and cost. Such features, reached through partial reconfiguration, are easily portable today to a broad range of embedded applications with identical system architecture.     

Hardware-Related Software Errors: Measurement and Analysis

This paper describes an analysis of hardware-related software (HW/SW) errors on an MVS/SP operating system at Stanford University. The analysis procedure demonstrates a methodology for evaluating the interaction between hardware and software as it relates to system reliability. The paper examines the operating system's handling of HW/SW errors and also the effectiveness of recovery management. Nearly 35 percent of all observed software failures were found to be hareware-related. The analysis shows that the operating system is seldom able to diagnose that a software error may be hardware-related. The impact of HW/SW errors on the system is evaluated by measuring the effectiveness of system recovery in containing the propagation of HW/SW errors. The system failure probability for HW/SW errors is close to three times that for software errors in general. The observed HW/SW errors are seen to have a specific pattern, suggesting the possibility of the use of such error patterns for intelligent error prediction and recovery.     

嵌入式系统芯片中SM2算法软硬件协同设计与实现

针对现有的椭圆曲线算法系统级设计中开发周期长,以及不同模块的性能开销指标不明确等问题,提出一种基于电子系统级(ESL)设计的软硬件(HW/SW)协同设计方法.该方法通过分析SM2(ShangMi2)算法原理与实现方式,研究了不同的软硬件划分方案,并采用统一建模语言SystemC对硬件模块进行周期精确级建模.通过模块级与系统级两层验证比较软硬件模块执行周期数,得出最佳性能划分方式.最后结合算法控制流程图(CFG)与数据流程图(DFG)将ESL模型转化为寄存器传输级(RTL)模型进行逻辑综合与比较,得出在180 nm CMOS工艺,50 MHz频率下,当算法性能最佳时,点乘模块执行时间为20 ms,门数83 000,功耗约2.23 mW.实验结果表明所提系统级架构分析对基于椭圆曲线类加密芯片在性能、面积与功耗的评估优势明显且适用性强,基于此算法的嵌入式系统芯片(SoC)可根据性能与资源限制选择合适的结构并加以应用.     

Advanced hardware/software co-design on reconfigurable network-on-chip based hyper-platforms

In this contribution we present a new paradigm and methodology for the Network-on-chip (NoC) based design of complex hardware/software systems. While classical industrial design platforms represent dedicated fixed architectures for specific applications, flexible NoC architectures open new degrees of system reconfigurability. After giving an overview on required demands for NoC hyper-platforms, we describe the realisation of these prerequisites within the HiNoC platform. We introduce a new dynamic hardware/software co-design methodology for pre- and post-manufacturing design. Finally we will summarize the concept combined with an outlook on further investigations.     

A modelling-based methodology for evaluating the performance of a real-time embedded control system

This paper presents a modelling-based methodology for embedded control system (ECS) design. Here, instead of developing a new methodology for ECS design, we propose to upgrade an existing one by bridging it with a methodology used in other areas of embedded systems design. We created a transformation bridge between the control-scheduling and the hardware/software (HW/SW) co-design tools. By defining this bridge, we allow for an automatic model transformation. As a result, we obtain more accurate timing-behaviour simulations, considering not only the real-time software, but also the hardware architecture’s impact on the control performance. We show an example with different model-evaluation results compared to real implementation measurements, which clearly demonstrates the benefits of our approach.     

Efficient heuristic and tabu search for hardware/software partitioning

Hardware/software (HW/SW) partitioning is a crucial step in HW/SW codesign that determines which components of the system are implemented on hardware and which ones on software. It has been proved that the HW/SW partitioning problem is NP-hard. In this paper, we present two approaches for HW/SW partitioning that aims to minimize the hardware cost while taking into account software and communication constraints. The first is a heuristic approach that treats the HW/SW partitioning problem as an extended 0–1 knapsack problem. In the second approach, tabu search is used to further improve the solution obtained from the proposed heuristic algorithm. Experimental results show that the proposed algorithms outperform a recently reported work by up to 28 %.