Diagnostic Data Compression Techniques for Embedded Memories with Built-In Self-Test

A system-on-chip (SOC) usually consists of many memory cores with different sizes and functionality, and they typically represent a significant portion of the SOC and therefore dominate its yield. Diagnostics for yield enhancement of the memory cores thus is a very important issue. In this paper we present two data compression techniques that can be used to speed up the transmission of diagnostic data from the embedded RAM built-in self-test (BIST) circuit that has diagnostic support to the external tester. The proposed syndrome-accumulation approach compresses the faulty-cell address and March syndrome to about 28% of the original size on average under the March-17N diagnostic test algorithm. The key component of the compressor is a novel syndrome-accumulation circuit, which can be realized by a content-addressable memory. Experimental results show that the area overhead is about 0.9% for a 1Mb SRAM with 164 faults. A tree-based compression technique for word-oriented memories is also presented. By using a simplified Huffman coding scheme and partitioning each 256-bit Hamming syndrome into fixed-size symbols, the average compression ratio (size of original data to that of compressed data) is about 10, assuming 16-bit symbols. Also, the additional hardware to implement the tree-based compressor is very small. The proposed compression techniques effectively reduce the memory diagnosis time as well as the tester storage requirement.     

Using what we know: Consequences of intentionally retrieving gist versus item-specific information.

The effect of a prior gist-based versus item-specific retrieval orientation on recognition of objects and words was examined. Prior item-specific retrieval increased item-specific recognition of episodically related but not previously tested objects relative to both conceptual- and perceptual-gist retrieval. An item-specific retrieval advantage also was found when the stimuli were words (synonyms) rather than objects but not when participants overtly named objects during gist-based recognition testing, which suggests that they did not always label objects under general gist-retrieval instructions. Unlike verbal overshadowing, labeling objects during recognition attenuated (but did not eliminate) test- and interference-related forgetting. A full understanding of how retrieval affects subsequent memory, even for events or facts that are not themselves retrieved, must take into account the specificity with which that retrieval occurs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Interference effects from grammatically unavailable constituents during sentence processing.

Evidence from 3 experiments reveals interference effects from structural relationships that are inconsistent with any grammatical parse of the perceived input. Processing disruption was observed when items occurring between a head and a dependent overlapped with either (or both) syntactic or semantic features of the dependent. Effects of syntactic interference occur in the earliest online measures in the region where the retrieval of a long-distance dependent occurs. Semantic interference effects occur in later online measures at the end of the sentence. Both effects endure in offline comprehension measures, suggesting that interfering items participate in incorrect interpretations that resist reanalysis. The data are discussed in terms of a cue-based retrieval account of parsing, which reconciles the fact that the parser must violate the grammar in order for these interference effects to occur. Broader implications of this research indicate a need for a precise specification of the interface between the parsing mechanism and the memory system that supports language comprehension. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Contextual cues aid recovery from interruption: The role of associative activation.

A series of experiments introduced interruptions to the execution phase of simple Tower of London problems and found that the opportunity for preparation before the break in task reduced the time cost at resumption. Retrieval of the suspended goal was facilitated when participants were given the opportunity to encode retrieval cues during an "interruption lag" (the brief time before engaging in the interrupting task) but was impeded when these visual cues were subsequently altered following interruption. The results provide useful support for the goal-activation model (E. M. Altmann & G. J. Trafton, 2002), which assumes that context--at the points of both goal suspension and goal retrieval--is critical to efficient interruption recovery. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Parallelism in ILU-preconditioned GMRES

A parallel implementation of the preconditioned GMRES method is described. The method is used to solve the discretized incompressible Navier–Stokes equations. A parallel implementation of the inner product is given, which appears to be scalable on a massively parallel computer. The most difficult part to parallelize is the ILU-preconditioner. We parallelize the preconditioner using ideas proposed by Bastian and Horton (P. Bastian, G. Horton, SIAM. J. Stat. Comput. 12 (1991) 1457–1470). Contrary to some other parallel methods, the required number of iterations is independent of the number of processors used. A model is presented to predict the efficiency of the method. Experiments are done on the Cray T3D, computing the solution of a two-dimensional incompressible flow. Predictions of computing time show good correspondence with measurements.     

PACS系统架构与数字化医院建设

随着我国科技的快速发展和对医院制度的改革,越来越多的新科技引进到医院管理中,医院逐渐步入数字化管理。将PACS系统新型技术应用到医院中,使得医院信息化建设由以病人费用为中心的收费信息,转变为以病人信息为中心的临床信息,全面地解决了医院数字化存档及通信问题,提升了医院信息化管理层次。文章对PACS系统在数字化医院中的建设,首先对PASC系统的发展做出了介绍,然后详细地阐述了PACS系统的设计,最后对我国的数字化医院建设中PACS的应用进行了分析。     

使用矩阵实现LRU的页面置换算法

操作系统的内存管理一直是计算机领域研究的一个重要方向。文中分析了几种常用内存管理中的页面置换算法及其存在的问题,提出了LUR页面置换算法的操作系统内存管理中比较接近理想算法的一种页面置换算法,并阐述了使用矩阵方法实现该页面置换算法的原理。     

紧扣内存变量关系巧解矩阵类问题

C语言学习过程中,不少初学者不能建立思维的模型,无法将形象可行的矩阵运算、旋转事件抽象化成算法语言。讲解了指导学生掌握矩阵操作算法的推导方法。