嵌入式实时操作系统eCos内存分配策略的分析

本文全面深入的探讨了eCos中内存分配策略的实现。首先，对eCos内核及内存管理方法进行了介绍，然后对四种内存分配策略进行了阐述和性能比较。对于嵌入式系统和应用的开发具有一定的参考价值。     

基于扩展控制流图的片上存储器分配策略

本文提出一种基于扩展控制流图(ECFG)的片上存储器(Scratch-Pad Memory,SPM)分配策略,该策略首先把程序划分为全局变量、全局堆栈、指令块等节点,用包含节点和节点间关系的ECFG来描述应用程序,接着采用考虑了节点间关系的改进的背包算法把选中的节点分配到SPM中.实验表明该策略比采用单纯背包算法的SPM分配策略减少应用程序执行时间11%,比不使用SPM时减少56%,大大提高了SoC存储子系统的性能.     

基于嵌入式设备浏览器内存管理策略研究

为了解决嵌入式设备中内存频繁分配和释放所引起的内存碎片以及浏览器正常运行难问题,提出具有垃圾回收机制的可动态增长池式分配数据结构设计和具有Compaction机制的Vector分配方法;在嵌入式环境系统设计时,采用可回收动态增长池式分配策略,系统无需预测内存大小,而且可以循环使用池内空间;Compaction机制的Vector分配方法可以移动＂在用＂对象和＂废弃＂对象调整内存占用,减少碎片。实验设计中应用上述策略,验证了该内存管理效率比系统级效率要高,嵌入式设备中打开网页文件越大,体现出来的效率更高。     

嵌入式操作系统μC／OS-Ⅱ的一种内存管理算法

针对μc／OS-Ⅱ内存管理机制的不足,提出了一种新的内存管理算法．较小的内存分成固定大小的内存块,用位图索引组织;较大的内存用链表组织．实验表明,该方法能较好地提高内存分配速度和利用率,特别是对于内存块大小变化很大的系统．     

面向SoC任务分配的应用程序存储需求量分析方法

通过分析应用程序的存储需求量,辅助片上系统(System-on-Chip, SoC)任务分配进行数据存储与传输优化,是改善SoC性能的途径之一.目前,存储需求量分析方法的分析粒度单一、速度缓慢,不利于进行多粒度任务分配空间的高效探索.本文面向SoC任务分配,提出一种多粒度、快速存储需求量分析方法.该方法可进行多粒度的存储需求量分析,并针对多媒体程序,引入数组数据域划分技巧,大幅度减少了存储需求量的分析时间.     

基于概率内存分配的内存安全研究

Some unsafe languages, like C and C+ + , let programmers maximize performance but are vulnerable to memory errors which can lead to program crashes and unpredictable behavior. Aiming to solve the problem, traditional memory allocating strategy is improved and a new probabilistic memory allocation technology is presented. By combining random memory allocating algorithm and virtual memory, memory errors are avoided in all probability during software executing. By replacing default memory allocator to manage allocation of heap memory, buffer overflows and dangling pointers are prevented. Experiments show it is better than Die-hard of the following aspects: memory errors prevention, performance in memory allocation set and ability of controlling working set. So probabilistic memory allocation is a valid memory errors prevention technology and it can tolerate memory errors and provide probabilistic memory safety effectively.     

A bit allocation method based on picture activity for still imagecoding

Bit allocation or the quantizer assignment problem is a basic and essential issue in lossy picture coding. The optimal solution for the bit allocation problem can be found by the Lagrangian method. However, it requires much computational time and memory. To reduce complexity overhead, we propose a fast scheme using a picture activity measure. Comparison among the existing activity measurement methods is presented to select the most reliable activity measure and the mapping relation between the activity value, and a quantization parameter is proposed.     

软件内存错误故障原因分析及其防范

介绍了软件中常见的内存读写、内存分配与释放、内存泄漏等内存错误及其所引发的故障,并进行分析。找出原因,提出相应的防范措施。     

Data Allocation with Minimum Cost under Guaranteed Probability for Multiple Types of Memories

As the advance of memory technologies, multiple types of memories such as different kinds of non-volatile memory (NVM), SRAM, DRAM, etc. provide a flexible configuration considering performance, energy and cost. For improving the performance of systems with multiple types of memories, data allocation is one of the most important tasks. The previous studies on data allocation problem assume the worst (fixed) case of data-access frequencies. However, the data allocation produced by employing worst case usually leads to an inferior performance for most of time. In this paper, we model this problem by probabilities and design efficient algorithms that can give optimal-cost data allocation with a guaranteed probability. We propose DAGP algorithm produces a set of feasible data allocation solutions which generates the minimum access time or cost guaranteed by a given probability. We also propose a polynomial-time algorithm, MCS algorithm, to solve this problem. The experiments show that our technique can significantly reduce the access cost compared with the technique considering worst case scenario. For example, comparing with the optimal result generated by employing the worst cases, DAGP can reduce memory access cost by 9.92 % on average when guaranteed probability is set to be 0.9. Moreover, for 90 percents of cases, memory access time is reduced by 12.47 % on average. Comparing with greedy algorithm, DAGP and MCS can reduce memory access cost by 78.92 % and 44.69 % on average when guaranteed probability is set to be 0.9.     

一种基于FAT文件系统的NAND Flash坏块处理方法

NAND Flash具有高存储密度和高存储速率的特点,在嵌入式系统领域得到了广泛应用.但其固有的擦除机制和存在有坏块这一致命弱点,成为其在应用中的主要障碍.本文提出了一种应用于FAT文件系统上的坏块处理方法,使用Flash上其他的空闲块或者空闲空间来代替坏块,并将坏块在FAT表中作出标记以后不作使用.这种方法彻底屏蔽了坏块对上层应用的影响,并对存储介质没有造成任何不良影响,从而很好地克服了上述障碍.工程项目中的应用证明了其较高的可靠性.     

Multi-Module Multi-Port Memory Design for Low Power Embedded Systems

In this paper we describe a multi-module, multi-port memory design procedure that satisfies area and/or energy constraints for embedded applications. Our procedure consists of application of loop transformations and reordering of array accesses to reduce the memory bandwidth followed by memory allocation and assignment procedures based on ILP models and heuristic-based algorithms. The specific problems include determination of (a) the memory configuration with minimum area, given the energy bound, (b) the memory configuration with minimum energy, given the area bound, (c) array allocation such that the energy consumption is minimum for a given memory configuration (number of modules, size and number of ports per module). The results obtained by the heuristics match well with those obtained by the ILP methods.     

Memory binding for performance optimization of control-flow intensive behavioral descriptions

This paper presents a memory binding algorithm for behaviors, used in application-specific integrated circuits (ASICs), that are characterized by the presence of conditionals and deeply nested loops that access memory extensively through arrays. Unlike previous works, this algorithm examines the effects of branch probabilities and allocation constraints. First, we demonstrate, through examples, the importance of incorporating branch probabilities and allocation constraint information when searching for a performance-efficient memory binding. We also show the interdependence of these two factors and how varying one without considering the other may greatly affect the performance of the behavior. Second, we introduce a memory binding algorithm that has the ability to examine numerous bindings by employing an efficient performance estimation procedure. The estimation procedure exploits locality of execution, which is an inherent characteristic of target behaviors. This enables the performance estimation technique to look at the global impact of the different bindings, given the allocation constraints. We tested our algorithm using a number of benchmarks from the parallel computing domain. A series of experiments demonstrates the algorithm's ability to produce bindings that optimize performance, meet memory allocation constraints, and adapt to different resource constraints and branch probabilities. One limitation of our algorithm is that, in its current form, it is not well suited for system-on-a-chip synthesis where there is complex communication between general-purpose microprocessors that use custom-designed arrays. Results show that the algorithm requires 41% fewer memories with a performance loss of only 0.2% when compared to a parallel memory architecture. When compared to the best of a series of random memory bindings, the algorithm improves schedule performance by 22%.     

基于C^＊Core的动态内存分配方案与实现

为了解决基于C＊Core系列芯片嵌入式开发过程中,C＊Core系统在某些情况下由于受操作系统、数据格式差异等因素影响,不能动态分配C＊Core系列芯片内存的问题,采用数组与标志位相结合的方法,提出一种C＊Core系列芯片在所有情况下都通用的动态内存分配方案。该方案利用C＊Core C语言编写实现,程序在苏州国芯公司CS32XDV10开发板上运行后,成功实现了动态分配CCM3118芯片内存功能。     

基于C~*Core的动态内存分配方案与实现

为了解决基于C*Core系列芯片嵌入式开发过程中,C*Core系统在某些情况下由于受操作系统、数据格式差异等因素影响,不能动态分配C*Core系列芯片内存的问题,采用数组与标志位相结合的方法,提出一种C*Core系列芯片在所有情况下都通用的动态内存分配方案。该方案利用C*Core C语言编写实现,程序在苏州国芯公司CS32XDV10开发板上运行后,成功实现了动态分配CCM3118芯片内存功能。     

Symbiotic Dynamic Memory Balancing for Virtual Machines in Smart TV Systems

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).     

Configuration selection for two-layer memory network pattern classifiers

Appropriate allocation of decision-making tasks between processing levels in a hierarchical memory network pattern classifier can enhance efficient utilisation of resources and reduce implementation complexity. The letter describes and compares two strategies for such resource allocation, with specific reference to decision refinement between processing levels.     

FIFO segmentation as a substitute to linked lists

We present a technique for dynamic allocation of memory to different queues. Our approach lies between two well-known techniques, linked lists and the relocation of data for preserving reasonable contiguous areas of available memory space. However, we avoid the main drawbacks of both. We never allocate more than two segments of contiguous memory per flow and thus avoid the proliferation of pointers and associated memory fragmentation. Moreover, we never relocate data already admitted into memory. We thus offer a considerably simpler implementation, amenable to hardware realization. The price to pay is also twofold. We cannot guarantee total exhaustion of the available memory before overflow occurs and we can only implement the first in first out (FIFO) discipline for the flows hosted in memory. In fact, we exploit the defining feature of a FIFO: data having arrived first will also leave first, spending in memory as little time as possible and giving the opportunity for rearranging memory allocation to the advantage of future arrivals. Two segments per flow are sufficient to achieve, over time, complete memory reallocation without data movement. Simulation results exhibit this ‘refreshing’ feature of FIFO, as brought to light by our proposed scheme.     

基于GPRS和WAP 2.0的手机Mobile WebServer的实现

文章介绍了WebServer在英飞凌公司的BP2手机平台的实现,以及GPRS和WAP 2.0,详细描述了针对手机平台设计的Mobile WebServer的Socket模块功能及工作流程.简单介绍了其内存分配算法,并与传统算法进行比较.在最后阐述了Mobile WebServer在英飞凌平台移植的可行性,以及对于Mobile WebServer未来的展望.     

Optimal Periodic Memory Allocation for Image Processing With Multiple Windows

One major issue in designing image processors is to design a memory system that supports parallel access with a simple interconnection network. This paper presents an efficient memory allocation to minimize the number of memory modules and processing elements with a parallel access capability when multiple windows with arbitrary shapes are specified. This paper also presents an efficient search method based on regularity of window-type image processing. We give some practical examples including a stereo-matching processor for acquiring 3-D information, and an optical-flow processor for motion estimation. These examples show that the numbers of memory modules are reduced to 2.7% and 10%, respectively, in comparison with a basic approach. It is also shown that the search time is less than 1 ms for practical image sizes and window sizes.      

一种改进的通用ASN.1协议编解码方法

针对开源ASN1C采用动态内存分配方法处理ASN.1协议消息的可选参数,导致编解码软件由于频繁分配和释放内存操作而带来的问题提出了一种改进的方法,避免了ASN.1结构类型编解码中的动态内存分配,减少了整个协议编解码软件进行内存分配和释放操作的频度.测试和实际工程运行结果表明,改进的方法提高了编解码软件的可用性、执行效率和健壮性.