Combining Task Scheduling in Power Adaptive Dynamic Reconfigurable System

Supplying the electronic equipment by exploiting ambient energy sources is a hot spot. In order to achieve the match between power supply and demands under the variance of environments at real time, a reconfigurable technique is taken. In this paper, a dynamic power consumption model by using a lookup table as a unit is proposed. Then, we establish a system-level task scheduling model according to the task type. Based on single instruction multiple data (SIMD) architecture which contains a processing system and a control system with a Nios Ⅱ processor, a practical dynamic reconfigurable system is built. The approach is evaluated on a hardware platform. The test results show that the system can automatically adjust the power consumption in case of external energy input changing. The utilization of the system dynamic power of their portion is from 80.05% to 91.75% during the first task assignment. During the entire processing cycle, the total energy efficiency is 97.67%.     

HW/SW codesign techniques for dynamically reconfigurable architectures

Hardware/software (HW/SW) codesign and reconfigurable computing are commonly used methodologies for digital-systems design. However, no previous work has been carried out in order to define a HW/SW codesign methodology with dynamic scheduling for run-time reconfigurable architectures. In addition, all previous approaches to reconfigurable computing multicontext scheduling are based on static-scheduling techniques. In this paper, we present three main contributions: 1) a novel HW/SW codesign methodology with dynamic scheduling for discrete event systems using dynamically reconfigurable architectures; 2) a new dynamic approach to reconfigurable computing multicontext scheduling; and 3) a HW/SW partitioning algorithm for dynamically reconfigurable architectures. We have developed a whole codesign framework, where we have applied our methodology and algorithms to the case study of software acceleration. An exhaustive study has been carried out, and the obtained results demonstrate the benefits of our approach.     

基于硬件任务顶点的可重构系统资源管理算法

可重构资源的管理是影响动态可重构系统性能的关键因素之一.本文提出了一种保持任务顶点信息的布局算法KTVP,并将其扩展为KTVS调度算法.KTVP/KTVS算法根据已接收硬件任务的顶点信息安排新到达的硬件任务,可通过对系统资源的编码迅速验证布局/调度的可行性,能有效减少系统资源浪费,提高系统内在的并行度.仿真实验表明,与已有算法相比,KTVP/KTVS算法具有更低的任务拒绝率和更小的运行开销.     

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.     

基于预配置和配置重用的粗粒度动态可重构系统任务调度技术

配置时间过长是制约可重构系统整体性能提升的重要因素,而合理的任务调度技术可有效降低系统配置时间。该文针对粗粒度动态可重构系统(CGDRS)和具有数据依赖关系的流应用,提出了一种3维任务调度模型。首先基于该模型,设计了一种基于预配置策略的任务调度算法(CPSA);然后根据任务间的配置重用性,提出了间隔配置重用与连续配置重用策略,并据此对CPSA算法进行改进。实验结果证明,CPSA算法能够有效解决调度死锁问题、降低流应用执行时间并提高调度成功率。与其它调度算法相比,对流应用执行时间的平均优化比例达到6.13%～19.53%。     

动态电压调整多处理器实时系统任务调度

动态电压调整DVS（Dynamic Voltage Scaling）是根据处理器电压（速度）降低之后，能量消耗平方级的减少这一原理提出的。文章通过DVS机制在多处理器实时系统中进行任务调度．通过对任务调度中的静态能量管理进行分析，在此基础上提出了一种新的基于DVS的适用于多处理器实时系统中的调度算法。这种新的调度算法是通过对贪婪法调度进行研究，发现其不足．并以此为基础进行改进。结合了动态电压调整的多处理器实时系统任务调度的能量消耗比普通的任务调度能量消耗有了很大的改善。     

基于3D碎裂度布局策略的可重构硬件任务调度算法

现有硬件任务调度算法任务描述不完善且忽视时间维上紧凑性。该文考虑任务下载时间、完善任务属性,以器件2维资源与时间建立3维资源模型,将任务布局问题抽象成特殊的3维空间放置问题,在此模型上分析出现有算法不能克服任务不可预知性和资源占用多变性,导致调度成功率和资源利用率低。针对此问题,该文提出了一种3维可重构任务调度算法3D_RTSA。设计并实现了基于任务紧迫度的调度策略和基于3D碎裂度的布局策略。与其他4种算法实验对比结果表明,在重负载、小任务C30情况下,3D_RTSA调度成功率比GC, Look-aheadest, SPSA, DTI算法分别高3%, 21%, 28%, 35%左右;在轻负载、大任务C50情况下,资源利用率比Look-aheadest, SPSA算法分别高5%, 18%左右,且该文算法时间复杂度并未增加。     

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     

Run-time management of systems with partially reconfigurable FPGAs

Partial reconfiguration (PR) of FPGAs can be used to dynamically extend and adapt the functionality of computing systems by swapping in and out HW tasks. To coordinate the on-demand task execution, we propose and implement a Run-Time System Manager (RTSM) for scheduling software (SW) tasks on available processor(s) and hardware (HW) tasks on any number of reconfigurable regions (RRs) of a partially reconfigurable FPGA. Fed with the initial partitioning of the application into tasks, the corresponding task graph, and the available task mappings, the RTSM controls system operation considering the status of each task and region (e.g. busy, idle, scheduled for reconfiguration/execution, etc). Our RTSM supports task reuse and configuration prefetching to minimize reconfigurations, task movement among regions to efficiently manage the FPGA area, and region reservation for future reconfiguration and execution. We validate the correctness and portability of our RTSM executing an image processing application on two Xilinx-based platforms: ZedBoard and XUPV5. We also perform a more extensive evaluation of its features using a simulation framework, and find that – despite the technology limitations – our approach can give promising results in terms of scheduling quality. Since our RTSM supports also the scheduling of parallel SW tasks, we use it to manage the execution of the entire parallel Edge Detection application on a desktop; we compare the application execution time with that using the OpenMP framework and find that with our RTSM execution is 2.4 times faster than the unoptimized OpenMP version. When processor affinity optimization is enabled for OpenMP, our RTMS and the OpenMP are on par, indicating that the scheduling efficiency of our RTSM is competitive to this state-of-the-art scheduler, while supporting in addition the management of HW tasks.     

云计算环境下任务调度算法的研究

在云计算环境中存在庞大的任务数,为了能更加高效地完成任务请求,如何进行有效地任务调度是云计算环境下实现按需分配资源的关键。针对调度问题提出了一种基于蚁群优化的任务调度算法,该算法能适应云计算环境下的动态特性,且集成了蚁群算法在处理NP-Hard问题时的优点。该算法旨在减少任务调度完成时间。通过在CloudSim平台进行仿真实验,实验结果表明,改进后的算法能减少任务平均完成时间、并能在云计算环境下有效提高调度效率。     

Exploiting Application Data-Parallelism on Dynamically Reconfigurable Architectures: Placement and Architectural Considerations

Partial dynamic reconfiguration, often called run-time reconfiguration (RTR), is a key feature in modern reconfigurable platforms. In this paper, we present parallelism granularity selection (PARLGRAN), an application mapping approach that maximizes performance of application task chains on architectures with such capability. PARLGRAN essentially selects a suitable granularity of data-parallelism for individual data parallel tasks while considering key issues such as significant reconfiguration overhead and placement constraints. It integrates granularity selection very effectively in a joint scheduling and placement formulation, necessary due to constraints imposed by partial RTR. As a key step to validating PARLGRAN, we additionally present an exact strategy (integer linear programming formulation). We demonstrate that PARLGRAN generates high-quality schedules with: (1) a set of small test cases where we compare our results with the exact strategy; (2) a very large set of synthetic experiments with over a thousand data-points where we compare it with a simpler strategy that tries to statically maximize data-parallelism, i.e., only considers resource availability; and (3) a detailed application case study of JPEG encoding. The application case-study confirms that blindly maximizing data-parallelism can result in schedules even worse than that generated by a simple (but RTR-aware) approach oblivious to data-parallelism. Last, but very important, we demonstrate that our approach is well-suited for true on-demand computing with detailed execution time estimates on a typical embedded processor. Heuristic execution time is comparable to task execution time, i.e., it is feasible to integrate PARLGRAN in a run-time scheduler for dynamically reconfigurable architectures.     

可重构分组密码指令集处理器自动映射方法研究

计算资源与寄存器资源分配是可重构处理器自动并行映射的重要问题,该文针对可重构分组密码指令集处理器的资源分配问题,建立算子调度参数模型和处理器资源参数模型,研究了分组密码并行调度与资源消耗之间的约束关系;在此基础上提出基于贪婪思维、列表调度和线性扫描的自动映射算法,实现了分组密码在可重构分组密码指令集处理器上的自动映射。通过可用资源变化实验验证算法并行映射的有效性,并对AES-128算法的映射效果做了横向对比验证算法的先进性,所提自动映射算法对分组密码在可重构处理中的并行计算研究有一定的指导意义。     

机载惯导系统的EDF算法优化研究

文章针对机载惯导系统软件的通信模块中出现多任务同时争夺处理机的过载情况,提出一种改进的最早截止时间优先算法（DPEDF）,以最大化完成任务的静态优先级之和为目标,引入动态规划的方法建立调度模型,计算近似最优阔度序列,实现了导致过载发生的各个任务优先级的动态划分。通过示例展示了如何化解过载,保证实时系统正常运行。     

Hardware/software codesign: a systematic approach targeting data-intensive applications

This article presents a systematic approach to hardware/software codesign targeting data-intensive applications. It focuses on the application processes that can be represented in directed acrylic graphs (DAGs) and use a synchronous dataflow (SDF) model, the popular form of dataflow employed in DSP systems when running the process. The codesign system is based on the ultrasonic reconfigurable platform, a system designed jointly at Imperial College and the SONY Broadcast Laboratory. This system is modeled as a loosely coupled structure consisting of a single instruction processor and multiple reconfigurable hardware elements. The paper also introduces and demonstrates a task-based hardware/software codesign environment specialized for real-time video applications. Both the automated partitioning and scheduling environment and the task manager program help to provide a fast robust for supporting demanding applications in the codesign system.     

一种云计算环境下任务调度策略

文章提出的问题是在云计算环境下任务调度策略。该策略的目标是将任务分配到计算单元上达到任务完成总时间最少和资源充分利用。基于此目标文章提出利用遗传算法对任务完成时间进行优化,并为处于空闲状态计算单元动态调整任务分配以改善资源利用率。利用CloudSim仿真平台验证该方法的有效性。     

基于SytemC动态可重构系统硬件任务管理模型

采用基于框架的建模仿真方法,对动态可重构系统进行设计空间搜索,需要建立仿真模型评估任务的管理策略.为此,文中利用SystemC搭建了一种动态可重构系统的硬件任务管理模型,该模型可根据不同的管理策略和重构资源进行调整.仿真实验结果表明,通过模型仿真获得硬件任务,在指定管理策略和资源约束下的实时调度布局信息,并针对具体应用...     

电网调度自动化的任务服务模型和调度算法研究

电网调度自动化是确保电力系统安全、稳定、可靠运行的重要手段,调度中心任务的处理效率将会直接影响到整个系统的性能.本文针对电网调度中心的实时任务特点,提出了一种高可靠的分布式动态镜像服务模型,并在此模型基础上实现了一种基于预测的任务调度算法—动态模糊调度DFS(Dynamic Fuzzy Scheduling)算法,此算法的调度依据是经过模糊变换后的资源调度决策集.对系统的模拟测试结果表明其具有良好的响应特性、服务能力和可靠性,比基于RT-SADS算法进行调度的系统在性能上有较大的改善.     

Temporal Partitioning Data Flow Graphs for Dynamically Reconfigurable Computing

FPGA-based configurable computing machines are evolving rapidly in large signal processing applications due to flexibility and high performance. In this paper, given a reconfigurable processing unit (RPU) with a logic capacity of A_RPU and a computational task represented by a data flow graph G = (V, E, W), we propose a network flow-based multiway task partitioning algorithm to minimize communication costs for temporal partitioning. The proposed algorithm obtains an optimal solution with minimum interconnection under area constraints. The optimal solution is a cut set. In our approach, two techniques are applied. In the initial partition, any feasible min-cut is produced by the proposed network flow-based algorithm, so a set of feasible min-cuts is obtained. From the feasible solutions, the scheduling technique selects an optimal global solution.     

一种可重构阵列结构及其任务调度算法

提出了一种可以利用计算时间覆盖配置时间和数据传输时间的可重构阵列结构,并且针对该可重构阵列结构提出了一种表调度算法进行任务调度.在SOCDesigner平台上进行了软硬件协同仿真,对于IDCT,FFT,4×4矩阵乘法新可重构阵列相比原来的可重构阵列有平均约10%的速度提升.     

一种启发式任务调度策略

本文对分布式计算机系统中的一些任务调度策略进行了介绍和分析,进而提出和介绍了在我们的立方体分布式计算机操作系统(CDCOS)中所采用的启发式动态任务调度算法。该调度算法和CDCOS的运行都是成功的。