A Design of Stack Data Cache in IW

A stack data cache is designed according to the features of intelligent workstation(IW) in A1 type intelligent network. Its page fault rate is up to 10 -3 , and the overhead of page replacement is only half of the normal. Stack data cache is suitable for IWs inference engine especially.

内存高效的持久性分布式文件系统客户端缓存DFS-Cache

为了在数据密集型工作流下有效降低缓存碎片整理开销并提高缓存命中率,提出一种持久性分布式文件系统客户端缓存DFS-Cache(Distributed File System Cache)。DFS-Cache基于非易失性内存(NVM)设计实现,能够保证数据的持久性和崩溃一致性,并大幅减少冷启动时间。DFS-Cache包括基于虚拟内存重映射的缓存碎片整理机制和基于生存时间(TTL)的缓存空间管理策略。前者基于NVM可被内存控制器直接寻址的特性,动态修改虚拟地址和物理地址之间的映射关系,实现零拷贝的内存碎片整理;后者是一种冷热分离的分组管理策略,借助重映射的缓存碎片整理机制,提升缓存空间的管理效率。实验采用真实的Intel傲腾持久性内存设备,对比商用的分布式文件系统MooseFS和GlusterFS,采用Fio和Filebench等标准测试程序,DFS-Cache最高能提升5.73倍和1.89倍的系统吞吐量。

A Novel Architecture of Metadata Management System Based on Intelligent Cache

This paper introduces a novel architecture of metadata management system based on intelligent cache called Metadata Intelligent Cache Controller （MICC）. By using an intelligent cache to control the metadata system, MICC can deal with different scenarios such as splitting and merging of queries into sub-queries for available metadata sets in local, in order to reduce access time of remote queries. Application can find results patially from local cache and the remaining portion of the metadata that can be fetched from remote locations. Using the existing metadata, it can not only enhance the fault tolerance and load balancing of system effectively, but also improve the efficiency of access while ensuring the access quality.

A Cache Replacement Policy Based on Multi-Factors for Named Data Networking

Named Data Networking(NDN)is one of the most excellent future Internet architectures and every router in NDN has the capacity of caching contents passing by.It greatly reduces network traffic and improves the speed of content distribution and retrieval.In order to make full use of the limited caching space in routers,it is an urgent challenge to make an efficient cache replacement policy.However,the existing cache replacement policies only consider very few factors that affect the cache performance.In this paper,we present a cache replacement policy based on multi-factors for NDN(CRPM),in which the content with the least cache value is evicted from the caching space.CRPM fully analyzes multi-factors that affect the caching performance,puts forward the corresponding calculation methods,and utilize the multi-factors to measure the cache value of contents.Furthermore,a new cache value function is constructed,which makes the content with high value be stored in the router as long as possible,so as to ensure the efficient use of cache resources.The simulation results show that CPRM can effectively improve cache hit ratio,enhance cache resource utilization,reduce energy consumption and decrease hit distance of content acquisition.

Multi-bit soft error tolerable L1 data cache based on characteristic of data value

Due to continuous decreasing feature size and increasing device density, on-chip caches have been becoming susceptible to single event upsets, which will result in multi-bit soft errors. The increasing rate of multi-bit errors could result in high risk of data corruption and even application program crashing. Traditionally, L1 D-caches have been protected from soft errors using simple parity to detect errors, and recover errors by reading correct data from L2 cache, which will induce performance penalty. This work proposes to exploit the redundancy based on the characteristic of data values. In the case of a small data value, the replica is stored in the upper half of the word. The replica of a big data value is stored in a dedicated cache line, which will sacrifice some capacity of the data cache. Experiment results show that the reliability of L1 D-cache has been improved by 65% at the cost of 1% in performance.

KDS-CM:A Cache Mechanism Based on Top-K Data Source for Deep Web Query

Caching is an important technique to enhance the efficiency of query processing. Unfortunately, traditional caching mechanisms are not efficient for deep Web because of storage space and dynamic maintenance limitations. In this paper, we present on providing a cache mechanism based on Top-K data source （KDS-CM） instead of result records for deep Web query. By integrating techniques from IR and Top-K, a data reorganization strategy is presented to model KDS-CM. Also some measures about cache management and optimization are proposed to improve the performances of cache effectively. Experimental results show the benefits of KDS-CM in execution cost and dynamic maintenance when compared with various alternate strategies.

Multi-Level Web Cache Model Used in Data Grid Application

This paper proposed a novel multilevel data cache model by Web cache （MDWC） based on network cost in data grid. By constructing a communicating tree of grid sites based on network cost and using a single leader for each data segment within each region, the MDWC makes the most use of the Web cache of other sites whose bandwidth is as broad as covering the job executing site. The experiment result indicates that the MDWC reduces data response time and data update cost by avoiding network congestions while designing on the parameters concluded by the environment of application.

A Predicted Region based Cache Replacement Policy for Location Dependent Data in Mobile Environment

Caching frequently accessed data items on the mobile client is an effective technique to improve the system performance in mobile environment. Proper choice of cache replacement technique to find a suitable subset of items for eviction from cache is very important because of limited cache size. Available policies do not take into account the movement patterns of the client. In this paper, we propose a new cache replacement policy for location dependent data in mobile environment. The proposed policy uses a predicted region based cost function to select an item for eviction from cache. The policy selects the predicted region based on client’s movement and uses it to calculate the data distance of an item. This makes the policy adaptive to client’s movement pattern unlike earlier policies that consider the directional / non-directional data distance only. We call our policy the Prioritized Predicted Region based Cache Replacement Policy (PPRRP). Simulation results show that the proposed policy significantly improves the system performance in comparison to previous schemes in terms of cache hit ratio.

Adaptive Cache Allocation with Prefetching Policy over End-to-End Data Processing

With the speed gap between storage system access and processor computing, end-to-end data processing has become a bottleneck to improve the total performance of computer systems over the Internet. Based on the analysis of data processing behavior, an adaptive cache organization scheme is proposed with fast address calculation. This scheme can make full use of the characteristics of stack space data access, adopt fast address calculation strategy, and reduce the hit time of stack access. Adaptively, the stack cache can be turned off from beginning to end, when a stack overflow occurs to avoid the effect of stack switching on processor performance. Also, through the instruction cache and the failure behavior for the data cache, a prefetching policy is developed, which is combined with the data capture of the failover queue state. Finally, the proposed method can maintain the order of instruction and data access, which facilitates the extraction of prefetching in the end-to-end data processing.

Towards Cache-Assisted Hierarchical Detection for Real-Time Health Data Monitoring in IoHT

Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.

Exadata数据库一体机FlashCache缓存淘汰算法改进

IT及互联网产业迅速发展,带来的信息量以几何级数量增长,这对存储系统的要求也不断提高,存储系统的性能、容量、与成本之间的矛盾也日益突出。分层存储作为一种能够有效解决上述矛盾的技术,在近年来成为热点。本文主要介绍Oracle公司的Exadata存储管理软件中对FlashCache缓存的管理,以及Exadata FlashCache缓存淘汰算法中目前存在的缺陷,最终给出该淘汰算法的改进建议。

DOOC:一种能够有效消除抖动的软硬件合作管理Cache

作为弥补处理器和主存之间速度巨大差异的桥梁,Cache已经成为现代处理器中不可或缺的一部分.经研究发现,传统Cache单独使用硬件进行管理,使用固定的Cache策略和一致性协议难以适应程序中数据访存模式的多样性,容易造成Cache抖动,以致影响性能.提出了一种新的软硬件合作管理Cache——面向数据对象Cache(data-object oriented cache,DOOC).DOOC动态地为程序中的数据对象分配Cache段,并且动态变化段容量、段内相联度、块大小和一致性协议,从而适应数据访存模式的多样性.还介绍了DOOC软件管理的编译方法以及面向数据对象的预取机制.分别使用CACTI和基于LEON3处理器的实验平台对DOOC的硬件开销进行评估,验证了DOOC的硬件可实现性.还使用软件模拟的方式分别测试了DOOC在单核和多核处理器平台上的性能.在单核处理器上对15个基准测试程序的评测结果表明,与传统Cache相比,DOOC失效率平均降低44.98%(最大降低93.02%),平均加速比为1.20(最大为2.36).同时,通过在4核处理器平台上运行NPB的OpenMP版本测试程序,失效率平均降低49.69%(最大降低73.99%).

静态物化视图的动态Cache优化算法

针对静态物化视图集动态适应能力的不足,提出一种动态cache优化算法DCO(dynamiccacheoptimization).它在保持静态算法获取最优物化集能力的基础上,将cache机制直观、快速的动态特性结合进来,以提高数据仓库的动态自适应性能.在cache机制具体实现中提出了一种新颖的空间申请方法,可以充分利用系统剩余空间提高查询响应性能.实验结果在表明算法有效、可行的同时,也显示出该算法可以在一定程度上克服静态物化集存在的空间-性能饱和效应(space-performancesaturationeffect,简称SPSE),使通过增加物化空间进一步提高数据仓库对查询的响应速度成为可能.

GridDaen数据网格中Cache机制的设计与实现

数据网格是一个典型的分布式系统,访问其中的广域分布的海量数据需要很大的时间开销。介绍GridDaen数据网格系统实现高速数据统一访问的Cache技术。GridDaen采用二级Cache机制,使用两个数据缓冲表来快速定位缓冲数据和控制缓冲数据访问,给出了各级Cache的数据替换算法,并提供了灵活的配置方法,可以将Cache与客户机、服务器独立分布,实现了Cache的可扩展性。

Cache对磁盘阵列性能的影响

Cache对磁盘阵列的性能影响很大 .本文从磁盘参数和通道性能两方面出发 ,利用排队论和Petri网模型计算磁盘阵列的性能 ,从理论上分析了磁盘和高速缓存各部分参数对磁盘阵列性能的影响 。

面向非一致Cache的智能多跳提升技术

非一致Cache体系结构(Non-Uniform Cache Architecture,NUCA)几乎已经成为未来片上大容量Cache的设计趋势.非一致Cache中,数据提升技术通过将经常访问的数据放置在距离处理器较近的Cache bank中减少处理器对该数据访问的等待时间,对NUCA的性能有着重要影响.然而,目前已有的数据提升技术使用固定的提升策略,没有考虑所要提升到目标bank的实际状态,容易将目标bank中更有用的数据"挤"得远离处理器,从而产生Cache污染问题,严重制约了提升技术的性能发挥.针对这一问题,文中提出智能多跳提升技术.智能多跳提升技术能够感知候选目标bank的状态,为被提升的数据动态地选择合适的目标bank,从而提高了提升效率,减少了Cache污染.同时,智能多跳提升技术的设计巧妙地利用了处理器访问的反向路径,只是简单地扩充了处理器访问报文的格式,并没有增加对Cachebank的额外访问.最后使用全系统模拟器对来自NAS Parallel Benchmark和Livermore Benchmark的15个基准测试程序进行了详细测试,智能多跳提升技术单位提升操作节省的时钟周期数是已有提升技术的1.50倍,最多达到2.61倍;系统的IPC性能平均提高了6.24%,最高达到19.03%.

存储系统的集中式Cache替换算法

为了最大限度地优化存储系统的I/O性能,通过对存储系统性能的分析,提出一种Cache替换算法———最小访问时间算法(LAT).该算法为Cache中数据对象定义一个排队函数,该函数不仅与对象的Cache命中率有关,还与对象的设备访问速度有关.按照此函数,Cache替换访问次数少、设备访问时间短的对象,从而使得存储系统的平均I/O时间最短.实验结果表明,随着设备访问速度差的增加,LAT算法的平均I/O性能远远优于LRU和LFU.

基于Cache行为的旁路攻击

分析新型高速缓冲存储器(Cache)旁路攻击技术,给出一种Cache旁路攻击方法。针对S盒操作使用查找表处理的数据加密标准(DES)算法实现,通过获取DES加密过程中前2轮加密运算对应的Cache命中信息,结合数学分析方法,可以有效地缩小DES密钥搜索空间。对Cache存储器行为和数学分析攻击进行仿真实现的结果显示,通过2~6个选择明文,大约耗费2^(30)次离线DES加密时间成功地恢复了DES密钥。给出了防御Cache攻击的基本对策。

YHFT-DX高性能DSP中Cache失效流水设计

YHFT-DX是国防科技大学自主研制的一款高性能DSP。以提升YHFT-DX的Cache性能为目标,研究了降低Cache失效延迟的优化策略,设计并实现了一种针对高频高性能DSP的一级数据Cache优化策略——失效流水。与传统优化策略相比,该策略将连续访问Cache的失效请求并进行流水化处理,使多个Cache失效延迟重叠,从而达到降低平均Cache失效代价的目的。将该策略应用到YHFT-DX芯片的一级数据Cache控制器的设计与优化中,使访问Cache失效引起的流水线停顿从8拍降为2拍,显著提升了系统性能。

针对RSA算法的踪迹驱动数据Cache计时攻击研究

Cache计时攻击是旁路攻击领域的研究热点.针对滑动窗口算法实现模幂运算的RSA算法,分析了RSA算法访问驱动Cache计时攻击的难点,建立了踪迹驱动数据Cache计时攻击模型.在攻击模型与原有踪迹驱动计时攻击算法的基础上,利用幂指数与操作序列的相关性、窗口大小特征和预计算表索引值与窗口值的映射关系,提出了一种改进的幂指数分析算法,并给出了利用幂指数dp和dq的部分离散位恢复出私钥d的格攻击过程.利用处理器的同步多线程能力实现了间谍进程与密码进程的同步执行,针对OpenSSL v0.9.8b中的RSA算法,在真实环境下执行攻击实验.实验结果表明:新的分析算法大约能够获取512位幂指数中的340位,比原有算法进一步降低了密钥恢复的复杂度;同时对实际攻击中的关键技术以及可能遇到的困难进行分析,给出相应的解决方案,进一步提高了攻击的可行性.