A physical view
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This document discusses the key resources that make up a computing grid: networks, processors, storage, and other resources. It describes how networks are the fundamental resource that enables grid computing by linking together the distributed processors, storage, and other resources. It also discusses how processors, storage, and other resources like scientific instruments can be shared across a grid to provide more computation power, data storage, and capabilities than any single system could alone.
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GridComputing-an introduction.ppt
Grid computing is a form of distributed computing that utilizes a network of loosely coupled computers acting together to perform large tasks. It facilitates large-scale resource sharing and coordinated problem solving among organizations. The key aspects of grid computing covered in the document include grid middleware, methods of grid computing like distributed supercomputing and data-intensive computing, grid architectures like layered grid architecture and data grid architecture, and simulation tools for modeling grid systems.
An asynchronous replication model to improve data available into a heterogene...
This document summarizes a research paper that proposes an asynchronous replication model to improve data availability in heterogeneous systems. The proposed model uses a loosely coupled architecture between main and replication servers to reduce dependencies. It also supports heterogeneous systems, allowing different parts of an application to run on different systems for better performance. This makes it a cost-effective solution for data replication across different system types.
Grid
Grid computing is a distributed processing architecture that shares CPU resources across a network to function as a single large supercomputer. It allows unused processing power from machines across multiple domains to be allocated to applications that require massive computation. Grids can work on specialized applications too big for a single supercomputer while maintaining flexibility to process smaller problems. They deliver a multi-user infrastructure to accommodate fluctuating large data processing demands.
Network attached storage different from traditional file servers & implemen
This document discusses Network Attached Storage (NAS), specifically Windows-based NAS. It begins by defining NAS and how it differs from traditional file servers and direct attached storage. It then discusses the advantages of NAS such as expandability, fault tolerance, and easier management. The document outlines several key technologies that Windows-based NAS utilizes, such as high availability features, easy deployment and management through a web interface, and seamless integration with Active Directory. It concludes by discussing NAS servers and their benefits like rapid installation, support for heterogeneous environments, server consolidation, and improved server performance.
Data-Intensive Technologies for Cloud Computing
This document provides an overview of data-intensive computing technologies for cloud computing. It discusses key concepts like data-parallelism and MapReduce architectures. It also summarizes several data-intensive computing systems including Google MapReduce, Hadoop, and LexisNexis HPCC. Hadoop is an open source implementation of MapReduce while HPCC provides distinct processing environments for batch and online query processing using its proprietary ECL programming language.
Grid computing: An Emerging Technology
Internet is the networking infrastructure which helps in connecting many users through interconnected networks through which users can communicate to each other. The World Wide Web is built on top of the internet to share information. The grid is again a service that is built on top of internet but is able to share computational power, databases, disk storage and software applications. The paper mainly focuses on significance Grid computing, its architecture, the grid middleware Globus toolkit and wireless grid computing.
H017144148
This document summarizes a research paper that proposes using a Google File System (GFS) configuration with MapReduce to improve CPU and storage utilization in a cloud computing system. It discusses how GFS with MapReduce can split large files into chunks and distribute the processing of those chunks across idle cloud nodes to make better use of resources. The document also addresses using encryption to improve security of data in the cloud.
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
This document summarizes a research paper that proposes using Google File System (GFS) and MapReduce in a cloud computing environment to improve resource utilization and processing of large datasets. The paper discusses GFS architecture with a master node and chunk servers, and how MapReduce can split large files into chunks and process them in parallel across idle cloud nodes. It also proposes encrypting data for security and using a third party to audit client files. The goal is to provide fault tolerance, optimize workload processing time, and maximize utilization of cloud resources for data-intensive applications.
DISTRIBUTED AND BIG DATA STORAGE MANAGEMENT IN GRID COMPUTING
Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal with large amounts of data. In traditional approaches high-performance computing consists dedicated servers that are used to data storage and data replication. In this paper we present a new mechanism for distributed and big data storage and resource discovery services. Here we proposed an architecture named Dynamic and Scalable Storage Management (DSSM) architecture in grid environments. This allows in grid computing not only sharing the computational cycles, but also share the storage space. The storage can be transparently accessed from any grid machine, allowing easy data sharing among grid users and applications. The concept of virtual ids that, allows the creation of virtual spaces has been introduced and used. The DSSM divides all Grid Oriented Storage devices (nodes) into multiple geographically distributed domains and to facilitate the locality and simplify the intra-domain storage management. Grid service based storage resources are adopted to stack simple modular service piece by piece as demand grows. To this end, we propose four axes that define: DSSM architecture and algorithms description, Storage resources and resource discovery into Grid service, Evaluate purpose prototype system, dynamically, scalability, and bandwidth, and Discuss results. Algorithms at bottom and upper level for standardization dynamic and scalable storage management, along with higher bandwidths have been designed.
5. the grid implementing production grid
‘Grids’areanapproachforbuildingdynamicallyconstructedproblem-solvingenvironmentsusing
geographically and organizationally dispersed,
high-performance computing and
data handling resources.
Gridsalsoprovideimportantinfrastructuresupportingmulti-institutionalcollaboration.
grid mining
The document discusses grids and their potential use for data mining applications in Earth science. Some key points:
- Grids can connect distributed computing and data resources to enable large-scale applications and collaboration.
- The Grid Miner application was developed to mine satellite data on NASA's Information Power Grid as a demonstration.
- Grids could help couple satellite data archives to computational resources, allowing users to process large datasets.
- For this to be realized, data archives need to be connected to grids and tools developed to enable scientists to access and analyze data.
Inroduction to grid computing by gargi shankar verma
Grid computing allows for sharing and coordination of distributed computer resources to address large-scale computation problems. It enables dynamic, scalable, and inexpensive access to computing power by connecting computers and other resources together with open standards. Key aspects of grid computing include dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities through coordination of distributed and often heterogeneous resources not subject to centralized control.
50120130405014 2-3
This document summarizes an article from the International Journal of Computer Engineering and Technology (IJCET) that proposes a new dynamic data replication and job scheduling strategy for data grids. The strategy aims to improve data access time and reduce bandwidth consumption by replicating data based on file popularity, storage limitations at nodes, and data category. It replicates more popular files that are in the same category as frequently accessed data to nodes close to where jobs are run. This is intended to optimize performance by locating data and jobs close together. The document provides context on related work and outlines the proposed system architecture and replication/scheduling approach.
Grid1
The document provides an overview of grid computing, including definitions, architectures, related technologies like cluster and peer-to-peer computing, applications such as distributed supercomputing and data-intensive computing, communities that may use grids, and projects involving grid technologies like Globus, Condor, and Nimrod-G. It summarizes key grid challenges including data movement, resource management, and job submission.
An experimental evaluation of performance
Hadoop is an open source implementation of the MapReduce Framework in the realm of distributed processing.
A Hadoop cluster is a unique type of computational cluster designed for storing and analyzing large datasets
across cluster of workstations. To handle massive scale data, Hadoop exploits the Hadoop Distributed File
System termed as HDFS. The HDFS similar to most distributed file systems share a familiar problem on data
sharing and availability among compute nodes, often which leads to decrease in performance. This paper is an
experimental evaluation of Hadoop's computing performance which is made by designing a rack aware cluster
that utilizes the Hadoop’s default block placement policy to improve data availability. Additionally, an adaptive
data replication scheme that relies on access count prediction using Langrange’s interpolation is adapted to fit
the scenario. To prove, experiments were conducted on a rack aware cluster setup which significantly reduced
the task completion time, but once the volume of the data being processed increases there is a considerable
cutback in computational speeds due to update cost. Further the threshold level for balance between the update
cost and replication factor is identified and presented graphically.
Similar to A physical view (20)
A New Architecture for Group Replication in Data Grid
A New Architecture for Group Replication in Data Grid
IRJET- Distributed Decentralized Data Storage using IPFS
IRJET- Distributed Decentralized Data Storage using IPFS
An asynchronous replication model to improve data available into a heterogene...
An asynchronous replication model to improve data available into a heterogene...
Network attached storage different from traditional file servers & implemen
Network attached storage different from traditional file servers & implemen
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Base...
DISTRIBUTED AND BIG DATA STORAGE MANAGEMENT IN GRID COMPUTING
DISTRIBUTED AND BIG DATA STORAGE MANAGEMENT IN GRID COMPUTING
Inroduction to grid computing by gargi shankar verma
Inroduction to grid computing by gargi shankar verma
More from Pooja Dixit
Combinational circuit.pptx
This document discusses combinational circuits and provides examples of half adders and full adders. It defines combinational circuits as those whose outputs only depend on the current inputs. A half adder is described as having two inputs (A and B) and two outputs (sum and carry), which can add two single bits. Its truth table and logic diagram using an XOR gate and AND gate are shown. A full adder handles three inputs (A, B, and a carry input) and produces a sum and carry output based on its truth table.
number system.pptx
The document discusses different number systems used in digital electronics, including binary, decimal, octal, and hexadecimal. It provides examples and explanations of how to convert between these number systems. In particular, it outlines the process for converting binary numbers to decimal numbers by multiplying each bit by its place value weight and summing the results. This includes approaches for fractional binary numbers and mixed binary numbers containing both integer and fractional parts.
Multiplexer.pptx
This document discusses different types of multiplexers, including 2x1, 4x1, and 8x1 multiplexers. It provides the block diagram and truth table for each type of multiplexer. A 2x1 multiplexer has 2 inputs, 1 selection line, and 1 output. A 4x1 multiplexer has 4 inputs, 2 selection lines, and 1 output. An 8x1 multiplexer has 8 inputs, 3 selection lines, and 1 output. The logical expressions and circuits for each type of multiplexer are also provided.
Logic Gates.pptx
Logic gates are basic building blocks of digital circuits and systems. Common logic gates include AND, OR, NOT, NAND, NOR, XOR, and XNOR gates. AND gates output 1 only if all inputs are 1, while OR gates output 1 if any input is 1. NOT gates output the inverse of the single input. NAND and NOR gates are combinations of AND/OR with NOT gates. XOR and XNOR gates output 1 only if inputs are both the same or different respectively.
K-Map.pptx
The document discusses Karnaugh maps, which are a graphical technique for simplifying boolean functions. A K-map is a diagram with squares that each represent minterms or maxterms. Variables are represented along rows and columns. Groups of 1s can be combined according to grouping rules to simplify boolean expressions. The example shows a 2-variable K-map used to minimize the boolean expression XY' + X'Y + X'Y' to X' + Y'. K-maps allow boolean functions to be reduced more easily than boolean algebra.
Karnaugh Map Simplification Rules.pptx
The document discusses rules for minimizing Boolean functions using K-maps. It explains that K-maps are used to graphically represent Boolean functions according to the number of variables. Values are filled in the K-map and grouped based on several rules: groups must contain only 0s or 1s but not both; groups can overlap; groups must contain a power of 2 cells and be horizontal or vertical only; groups should be as large as possible with fewest groups overall. Examples are provided to illustrate opposite and corner grouping.
Half Subtractor.pptx
The half subtractor is a digital circuit that subtracts two single bit binary numbers and outputs the difference and borrow. It contains two inputs, A and B, and two outputs, Diff and Borrow. The Diff output is the difference of A and B, calculated as A XOR B. The Borrow output is 1 only when A is 1 and B is 0, calculated as A'B. The full subtractor expands on this to subtract three 1-bit numbers by adding a third input, Borrowin, and producing Diff and Borrow outputs based on all input combinations.
Gray Code.pptx
The document discusses Gray code, which is a binary numbering system where two successive numbers differ in only one bit. This reduces switching errors during transitions between numbers. Gray code is used in digital communications and applications where normal binary could produce errors. The document provides examples to show how decimal numbers convert to binary and Gray code. In binary, more bits may change between numbers, while Gray code ensures only one bit changes.
Flip Flop.pptx
The document provides information about Prof. Neeraj Bhargava and Mrs. Pooja Dixit who work in the Department of Computer Science in the School of Engineering & System Sciences at MDS University in Ajmer, Rajasthan.
Encoder.pptx
This document discusses encoders and provides examples of 4-to-2 and 8-to-3 line encoders. It defines an encoder as a combinational circuit that performs the reverse operation of a decoder, with a maximum of 2n input lines and n output lines. Truth tables and logic circuits are given for 4-to-2 and 8-to-3 line encoders. Uses of encoders include converting decimal to binary numbers to perform binary operations like addition and subtraction in digital systems.
De-multiplexer.pptx
This document discusses demultiplexers, which are combinational circuits with one input and multiple outputs. It describes 1x2 and 1x4 demultiplexers specifically. For a 1x2 demultiplexer, there are two outputs, one selection line, and a single input. The input is directed to one of the two outputs based on the selection line value. A 1x4 demultiplexer has four outputs, two selection lines, and one input. The input is directed to one of the four outputs based on the combination of values on the two selection lines. Block diagrams and truth tables are provided to illustrate the functionality of 1x2 and 1x4 demultiplexers.
DeMorgan’s Theory.pptx
The document discusses DeMorgan's theorems, which state that a NOR gate is logically equivalent to an AND gate with inverted inputs, and a NAND gate is equivalent to an OR gate with inverted inputs. DeMorgan's theorems are important in digital logic, as they allow basic gates like NAND and NOR to be used to implement more complex logic functions. The theorems are verified through truth tables.
Combinational circuit.pptx
This document discusses combinational circuits and provides examples of half adders and full adders. It defines combinational circuits as those whose outputs only depend on the current inputs. A half adder is described as having two inputs (A and B) and two outputs (sum and carry), which can add two single bits. Its truth table and logic diagram using an XOR gate and AND gate are shown. A full adder handles three inputs (A, B, Cin) to add two bits along with a carry bit, with outputs of sum and carry out. Its block diagram and truth table are presented.
Boolean Algebra.pptx
The document discusses Boolean algebra, which uses binary numbers (0 and 1) to analyze and simplify digital logic circuits. It was invented by George Boole in 1854. The document outlines several important rules of Boolean algebra, including commutative, associative, distributive, identity, idempotent, complement, and double negation laws. It also discusses de Morgan's theorem and finding the dual of Boolean expressions.
Binary Multiplication & Division.pptx
Binary multiplication and division work similarly to decimal operations but use only 0s and 1s. For binary multiplication, there are four basic rules and the process involves multiplying each bit of one number by the other number and summing the results. Examples show multiplying 1010 x 101 to get 10100 and comparing the binary result to its decimal equivalent. Binary division uses long division to divide strings of binary digits. Examples demonstrate dividing several binary numbers by powers of two.
Binary addition.pptx
Binary arithmetic is essential for digital computers and systems. It includes four rules for binary addition and subtraction. Binary addition examples show that adding two 1s results in a 1 in the next column with a carry of 1. Binary subtraction uses borrowing to subtract binary numbers, as shown through several examples.
Basics of Computer Organization.pptx
This document provides an overview of computer organization. It defines computer organization as how the various parts of a computer are organized and work together. It describes the main components of a computer like the CPU, memory (RAM and cache), and buses. It also discusses number systems like binary, decimal, octal, and hexadecimal. Additional topics covered include Gray codes, Boolean algebra, logic gates, and flip flops.
Decoders
A decoder is a logic circuit that takes binary input and provides an output based on the input. It performs the reverse operation of an encoder. There are different types of decoders including a 2 to 4 line decoder and a 3 to 8 line decoder. A 2 to 4 line decoder has 3 inputs (A0, A1, E) and 4 outputs (Y0, Y1, Y2, Y3). It uses AND gates to activate one output based on the input. A 3 to 8 line decoder has 3 inputs (A0, A1, A2), 8 outputs (Y0-Y7), and an enable input. It uses AND gates and logic expressions to activate one of the 8 outputs based on the
Three Address code
The document discusses three address code, which is an intermediate code used by optimizing compilers. Three address code breaks expressions down into separate instructions that use at most three operands. Each instruction performs an assignment or binary operation on the operands. The code is implemented using quadruple, triple, or indirect triple representations. Quadruple representation stores each instruction in four fields for the operator, two operands, and result. Triple avoids temporaries by making two instructions. Indirect triple uses pointers to freely reorder subexpressions.
Cyrus beck line clipping algorithm
The Cyrus-Beck algorithm is used for line clipping against non-rectangular convex polygons. It uses a parametric equation to find the intersection point of the line with the polygon boundary. The algorithm calculates the time values for the line endpoints at each polygon edge, then uses those times in the parametric equation to find the clipped line segment P'0 and P'1 that is visible within the polygon clipping window.
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学校原件一模一样【微信：741003700 】《(ANU毕业证书)澳洲国立大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
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Low power architecture of logic gates using adiabatic techniques
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
一比一原版(UC Berkeley毕业证)加利福尼亚大学|伯克利分校毕业证成绩单专业办理
UC Berkeley毕业证原版定制【微信：176555708】【加利福尼亚大学|伯克利分校毕业证成绩单-学位证】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
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◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
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◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
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选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
学历顾问：微信：176555708
Heap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTS
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Modelagem em função de transferencia. CSTR não-linear.
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A physical view
- 1. Prof. Neeraj Bhargava Pooja Dixit Department of Computer Science School of Engineering & System Sciences MDS, University Ajmer, Rajasthan, India 1
- 2. A grid is a collection of networks, processors, storage, and other resources. Networks The networking mechanism is the most fundamental resource for the grid and also is the theme of this book. In fact, without networking grid computing would not be possible. The recent growth in communication capacity makes grid computing practical, compared to the limited bandwidth available when distributed computing was first emerging. Transmission of content and job supervision within the grid are important for sending jobs and the required data to points within the grid (some jobs require a large amount of data to be processed and it may not always reside on the processor running the job. 2
- 3. Computation The next most common resource on a grid is obviously computing cycles provided by the processors on the grid. The processors can vary in speed, architecture, software platform, and storage apparatus. There are efforts underway to develop very high- speed supercomputers. Whereas clustering is a common approach at the TFLOPS speeds, grid computing can also play a role in these initiatives by refining architectures that link remote computers into an assembly of loosely or tightly coupled processors. At the business level, grid computing is expected by the industry to be more practical than cluster-based supercomputing. 3
- 4. Storage The next most common resource used in a grid is data storage. In a grid environment, a file or data base can span several physical storage devices and processors, bypassing size restrictions often imposed by file systems that are preembedded with operating systems. Storage capacity available to an application can be increased by making use of the storage on multiple processors with a unifying file system. Each processor on the grid usually provides some quantity of storage for grid use. Storage can be “primary storage,” “secondary storage,” or “tertiary storage.” Memory directly attached to a processor has fast access capabilities but is volatile; this kind of memory is used to cache data to serve as temporary storage for running applications. “Secondary storage” is generally implemented in hard disk drives, such as with RAID (redundant array of inexpensive drives). “Tertiary storage” is generally implemented in near-real-time accessible media such as tape or other permanent storage media. Many grid systems use mountable networked file systems, such as Network File System (NFS), Distributed File System (DFS), or General Parallel File System (GPFS). Special grid database software can “federate” a group of individual data bases and files to form a larger, more inclusive data base. A PHYSICAL VIEW 4
- 5. Scientific Instruments Grids, particularly an intergrid, can provide shared access to expensive scientific equipment or interconnect dispersed equipment into a larger overall scientific tool. We will not discuss this issue further, since our emphasis is on commercial applications. Software and Licenses Two issues are of interest to organizations: application software and licensed software. Regarding application software, the most basic approach is to use the grid environment to allow the application to run on an available processor on the grid (rather than running locally.) Further along the transition trajectory, one can modify the application to segment its work in such a way that the separate parts can execute in parallel on different grid processors. “scalability” is a measure of how efficiently the multiple processors on a grid are used. However, there may be limits to scalability. A PHYSICAL VIEW 5