Cluster Computing: History, Applications and Benefits

Cluster Computing: History, Applications and Benefits Abstract This report will provide a detailed review of the cluster computing. In this report we look at the birth of cluster computing till the present and the future direction the technology is headed. After the literature review, we move on to the explanation of theories involved from the author’s point of view. The final section of the report covers the current trends and future evolution of the technology as perceived from the author’s point of view. The essence of the report would be a better understanding of the cluster computing and its many uses in today’s world. Introduction A computer cluster consists of a set of loosely connected or tightly connected computers that work together so that in many respects they can be viewed as a single system. The components of a cluster are usually connected to each other through fast local area networks (LAN), with each node (computer used as a server) running its own instance of an operating system. Computer clusters emerged as a result of convergence of a number of computing trends including the availability of low cost microprocessors, high speed networks, and software for high performance distributed computing. Clusters are usually deployed to improve performance and availability over that of a single computer, while typically being much more cost-effective than single computers of comparable speed or availability.[1] Computer clusters have a wide range of applicability and deployment, ranging from small business clusters with a handful of nodes to some of the fastest supercomputers in the world such as IBMs Sequoia. [2] Literature review In 1967 a paper published by Gene Amdahl of IBM, formally invented the basis of cluster computing as a way of doing parallel work. It is now known as Amdahl’s Law. It is a model for correlation between the expected speedup of parallelized implementations of an algorithm relative to the serial algorithm, assuming the problem size remains the same. [3] Types of Clusters Computer clusters are used in many organizations to increase processing time, faster data storing and retrieval time, etc. These computer clusters can be classified in three main types of clusters but these can be mixed to achieve higher performance or reliability. High performance clusters High availability clusters Load Balancing clusters High Performance Cluster: High performance computing sometimes refer to as high performance computing are used for computation-intensive applications, rather than handling IO-oriented applications such as web service or databases.[4] examples of HPCs can include the computational simulations of vehicle crashes or weather. Very tightly coupled computer clusters are designed for work that may approach supercomputing. The worlds fastest machine in 2011 was the K computer which has a distributed memory, cluster architecture.[5] High Availability Cluster: High availability clusters are commonly known as failover clusters. They are used to improve the availability of the cluster approach. In high availability clusters, redundant nodes are used which take over in case of component failure. It is used to eliminate single point of failure by having redundant cluster components.[6] High Availability clusters are often used for critical databases, file sharing on a network, business applications, and customer services such as electronic commerce websites. Load Balancing Cluster: Load balancing clusters, as the name suggests are the cluster configurations where the computational workload is shared between the nodes for better overall performance. One of the best examples of load balancing cluster is a web server cluster. It may use a round robin method to assign each new request to a different node for overall increase in performance. [7] Benefits of Clusters: There are numerous advantages to using cluster computing. Some of these are detailed below. Cost: Cluster technique is cost effective compared to other techniques in terms of the amount of power and processing speed being produced due to the fact that it used off the shelf hardware and software components as compare to the mainframe computers, which use custom build proprietary hardware and software components. Processing speed: In a cluster, multiple computers work together to provide unified processing, which in turn provides faster processing. Flexibility: In contrast to a mainframe computer, a computer cluster can be upgraded to a higher specification or expanded by adding extra nodes. Higher availability: Single component failure is mitigated by redundant machines taking over the processing uninterrupted. This type of redundancy is lacking in mainframe systems. Cluster Management: Message passing and communication The two most often used approaches for cluster communications are PVM and MPI. PVM stands for parallel virtual machine. It was developed around 1989 by Oak Ridge National Laboratory. It is directly installed on every node and it provides a set of libraries that make the node a â€Å"parallel virtual machine†. It provides a run time environment for resource task management, fault notification and message passing. User programs written in C, C++ or Fortran can use PVM.[8][9] MPI stands for message passing interface. It emerged in 1990s and supersedes PVM. MPI design is based on various commercially available systems of the time. Its implementation typically uses TCP/IP and socket connection. Currently it’s the most widely used communication system enabling parallel programming in C, Fortran, Python etc.[9][10] Task scheduling Task scheduling becomes a challenge, when a large multiuser cluster needs access to huge amounts of data. In a heterogeneous CPU-GPU cluster, mapping tasks onto CPU cores and GPU devices provide quite a challenge because it’s a complex application environment and the performance of each job depends on the abilities of the underlying technologies. Task scheduling is an active area of ongoing research and there have been proposals to build an algorithms which combine and extend MapReduce and Hadoop. [11] Node failure management Node failure management is a technique used to handle a failed node in a cluster using strategies such as â€Å"fencing†. It isolates the node or a shared resource when it detects a malfunction. There are two types of fencing. First is to disable the node and the second is to prevent access to resources like shared disks. [12] The first method uses STONITH. Which stands for â€Å"Shoot The Other Node In The Head†. This method disables or power off the malfunctioning node. For example, power fencing uses a power controller to turn off the faulty node. [12] The second method uses the resource fencing approach, which prevents access to resources rather than to turn off the node. For example, fiber channel fencing can be used to disable the fiber channel port. [12] 1137395 Muhammad Khurram Shehzad Trends The demand for powerful computers that can be used for simulation and prediction are of great interest to both the public and private sector. Last decade, was the most exciting periods in computer development. As a result of Moore’s law, microprocessors have become smaller, denser, and more powerful. The result is that microprocessor based supercomputing is rapidly becoming the technology of preference in attacking some of the most important problems of science and engineering. A recent report from Intersect360 Research highlighted some interesting trends in HPC. Below are a few of the highlights. [13] More Memory with Multi-core: While memory usage per core is nearly constant in years past, the broader adoption of multi-core systems is creating a demand for more memory. This can be expected but the report also warns of additional system costs as the need for more memory rises.[13] Processors per Nodes: According to summary of the report, two-processors per node is still the preferred configuration with 60% of the market, with just 14% opting for four-processor nodes. These ratios have stayed about the same over the past five years.[13] Future Outlook High Performance Computing (HPC) is expected to increase with which Big Data is analyzed to address variety of scientific, environmental and social challenges, especially on very large and small scales. In order of magnitude more powerful than laptop computers, HPC processes information using parallel computing, allowing for many simultaneous computations to occur concurrently. These integrated machines are measured in â€Å"flops† which stands for â€Å"floating point operations per second.† [14] As of June 2013, Tianhe-2 (or, Milky Way-2), a supercomputer developed by China’s National University of Defense Technology, is the world’s fastest system with a performance of 33.86 petaflop/s. [15] HPC is expected to move into â€Å"exascale† capacity by 2020, developing computing capacities 50 times greater than today’s most advanced supercomputers. Exascale feasibility rests on the rise of energy efficient technology: the processing power exists but the energy to run it, and cool it, does not. Currently, the American supercomputer MIRA, [16] while not the fastest, is the most energy efficient thanks to circulating water-chilled air around the processors inside the machine rather than merely using fans. Applications of the technology High-performance computing (HPC) is a broad term that in essence represents compute intensive applications that need acceleration. Users of application acceleration systems range from medical imaging, financial trading, oil and gas expiration, to bioscience, data warehousing, data security, and many more. In the information age, the need for acceleration of data processing is growing exponentially and the markets deploying HPC for their applications are growing every day. The HPC expansion is being fueled by the coprocessor, which is fundamental to the future of HPC. 1137784 Samra Mohammad 8Future trends, outlook and applications of cluster computing: Computer plays an important role in the information age. Different countries have undertaken thorough studies on computing to improve the information level. I may observe some current trends and speculate a bit about the future of parallel programming models. As far as we can foresee today, the future of computing is parallel computing, dictated by physical and technical necessity. 8.1New trends in cluster computing: These days, there is a new computing paradigm as computer networks called the Grid. It becomes very cheap and very fast .What is a Grid? It is a big system of computing resources that provides to users a single point of access and performs tasks. It is based on the WWW (World Wide Web) interface, to these distributed resources[17] The Grid technology is currently in progress intensive development. The Grid is also the first tools which are already available for developers. In this type of application, we can use a high-speed network in regarding the interconnection between the parts of the grid via internet. Nowadays , the Grid is agree to enable for scientific collaborations to share resources on an unprecedented level and geographically distributed groups to collaborate together in a manner that were previously impossible by using scalable, secure, high performance mechanisms for discovering and negotiating access to remote resources. 8.2Future: In the future, the increase of industry support for low latency clusters will help in availability and performance, but restrictions may require a departure from the current multicast-oriented data distribution strategies. However, latency and bandwidth performance will continue to improve in the Ethernet with a very low cluster with multicast support. 8.3Application and outlook: Obviously, cluster computing is quickly becoming the architecture of choice. One of the categories of applications is called Grand Challenge Applications (GCA). It are defined as fundamental problems in science and engineering with broad economic and scientific impact whose solution can be advanced by applying high performance computing and communication technologies. The high scale of complexity in GCAs demands enormous amount of resources needs, such as processing time, memory space and communication bandwidth. A common characteristic of GCAs is that they involve simulations that are computationally intensive. Examples of GCAs are applied fluid dynamics, environmental modeling, ecosystem simulation, biomedical imaging, biomechanics, molecular biology, and computational sciences. [17] Other than GCAs, cluster computing is also being applied in other applications that demand high availability, scalability and performance. Clusters are being used as replicated storage and backup servers that provide the essential fault tolerance and reliability for critical applications. For example, the internet, search engine, Google uses cluster computing to provide reliable and efficient internet search services. Conclusion Cluster computing offers a comparatively cheap, alternative to large server or mainframe computer solutions. New trends in hardware and software technologies are likely to make clusters more promising. Statement of contribution Member 1: Muhammad Khurram Shehzad (1137395), Abstract, Introduction, Literature review Conclusion as a Group and Trends, Future Outlook applications as individual. Member 2: Samra Mohammad (1137784), Abstract, Introduction, Literature review Conclusion as a Group and Trends, Future Outlook applications as individual. Member 3: Muhammad Faheem Abbas (1137391), Abstract, Introduction, Literature review Conclusion as a Group and Trends, Future Outlook applications as individual. References: [1] Bader, David; Robert Pennington (June 1996). Cluster Computing: Applications. Georgia Tech College of Computing. Retrieved 2007-07-13. [2] Nuclear weapons supercomputer reclaims world speed record for US. The Telegraph. 18 Jun 2012. Retrieved 18 Jun 2012. [3] Amdahl, Gene M. (1967).Validity of the Single Processor Approach to Achieving Large-Scale Computing Capabilities.AFIPS Conference Proceedings(30): 483–485.doi:10.1145/1465482.1465560 [4] High Performance Computing for Computational Science VECPAR 2004 by Michel Daydà ©, Jack Dongarra 2005 ISBN 3-540-25424-2 pages 120-121 [5] M. Yokokawa et al The K Computer, in International Symposium on Low Power Electronics and Design (ISLPED) 1-3 Aug. 2011, pages 371-372 [6] Evan Marcus, Hal Stern: Blueprints for High Availability: Designing Resilient Distributed Systems, John Wiley Sons, ISBN 0-471-35601-8 [7] High Performance Linux Clusters by Joseph D. Sloan 2004 ISBN 0-596-00570-9 page [8] Distributed services with OpenAFS: for enterprise and education by Franco Milicchio, Wolfgang Alexander Gehrke 2007, ISBN pages 339-341 [9] Grid and Cluster Computing by Prabhu 2008 8120334280 pages 109-112 [10] Gropp, William; Lusk, Ewing; Skjellum, Anthony (1996). A High-Performance, Portable Implementation of the MPI Message Passing Interface. Parallel Computing. CiteSeerX: 10.1.1.102.9485 [11] K. Shirahata, et al Hybrid Map Task Scheduling for GPU-Based Heterogeneous Clusters in: Cloud Computing Technology and Science (CloudCom), 2010 Nov. 30 2010-Dec. 3 2010 pages 733 740 ISBN 978-1-4244-9405-7 [12] Alan Robertson Resource fencing using STONITH. IBM Linux Research Center, 2010 [13] http://www.intersect360.com/industry/reports.php?id=67 (Accessed 12/05/2014) [14] http://ec.europa.eu/digital-agenda/futurium/en/content/future-high-performance-computing-supercomputers-rescue (Accessed 12/05/2014) [15] http://www.top500.org/system/177999#.U3ORpPmSzDs (Accessed 12/05/2014) [16] http://en.wikipedia.org/wiki/IBM_Mira (Accessed 12/05/2014) [17] http://www.slideshare.net/shivakrishnashekar/computer-cluster (Accessed 14th May 2014)

Plato’s Laches

During his lifetime Socrates’ various interactions with his fellow Athenians left his intentions debatable. Popular belief in Athens seemed to be that, â€Å"he [Socrates] was an evildoer, and a curious person, who searches into things under the earth and in heaven? and makes the worse appear the better cause† (Plato, pg. 5) as stated by the unofficial charges against him in The Apology. After discussions, his interlocutor’s were left confused in a state of aporia, with no conclusion.And so while negative views of Socrates became increasing popular in Athens right up until his death, Socrates was, on the contrary, serving as Athens’s benefactor, opening up their eyes to the truth of world in which they lived in. In Plato’s Laches, Socrates does in fact tear down his interlocutors’ claims but only to prove to them that they don’t know what they claim to know by exposing holes in their fundamental thoughts and to redirect them on a path to finding true knowledge.Through a method of elenchus, Socrates aimed to prove to his interlocutor that the ideas they held about certain topics were in fact false. When a person would come to him with a question, as Laches and Nicias do in Laches, Socrates would first direct the conversation in such a way that the question lying before the men is a foundational one, and not necessarily the original question.In his explanation of this Socrates states, â€Å"So, in a word, whenever a man considers a thing for the sake of another thing, he is taking counsel about that thing for the sake of which he was considering, and not about what he was investigating for the sake of something else† (Plato 185D) and redirects the question of whether or not young boys should learn the art of fighting in armor to how to care for the souls of young men. By doing this Socrates is able to expose the very source of his interlocutors’ belief system and demonstrate that if the basis of the s ystem isn’t true nothing built on it can be true.Socrates goes on to have the men discus virtue, because they are trying to discover what virtue could be added to their sons’ souls to make them better men and because virtues are the basis for the moral ethics by which they live.. He then invites them to define a virtue: courage. When Laches gives a less than sufficient answer, Socrates rephrases his question and asks for a true definition of courage, one that would encompass every sort of courageous act. Eventually Laches gets to a point where he is unsure of how to proceed, saying, â€Å"I am really getting annoyed at being unable to express what I think in this ashion. I still think I know what courage is, but I can’t understand how it has escaped me just now so that I can’t pin it down in words and say what it is† (Plato 194B). By admitting that he is unable to concisely express the definition of something he considered himself knowledgeable abo ut, Laches allowed Socrates’ method to have a reflective effect on him. The dialogue ends in an aporia, or a state of unknowing, leaving Laches and Nicias still without an answer to whether or not young men should learn the art of fighting in armor and more importantly without what a proper definition of courage.They leave the conversation confused, realizing, that they don’t know what they thought they knew, which is what Socrates had originally intended for them to eventually understand. Coming out of a Socratic dialogue usually left the interlocutor feeling one of two ways. Laches, after conversing with Socrates and Nicias, is aware that he isn’t as informed on the idea of courage as he would have like to think, but still agrees to go Lysimachus’ house the next day to continue the discussion in hopes of revealing an answer.Being made aware of his shortcoming, instilled in him a desire to further explore it. Leaving the Socratic dialogue left Laches wan ted more; because it ended in aporia, the only piece of knowledge he got of the conversation was that his definitions were wrong. Instead of giving Laches the answer, and having him just accept it as true, Socrates invited him to search for it, because in searching for an answer to the definition of courage, Laches would gradually begin to question and search for other pieces of knowledge relevant to his life, and it would become an ongoing process.However, other Athenians eventually grew tired of Socrates’ extensive questioning and can be seen in The Apology putting Socrates on trial for it. Instead of taking Socrates’ conversations for what they were worth, they labeled him as argumentative and a man who was corrupting the youth of the city. By breaking down his interlocutors’ various thoughts, ideas, and theses, Socrates was trying to reveal to them that they were not in fact wise and that the knowledge they thought they possessed was not true knowledge.Socra tes himself was only considered wiser than his fellow Athenians because he considered his one piece of knowledge to be that he didn’t know anything. By breaking down, piece by piece, the arguments of those he conversed with, he intended for them to realize that their knowledge was relative and therefore meaningless in the grander scheme of things. By recognizing this, only then could they begin living a life in search of finding true meaning. In searching for meaningful things they would have to learn to question things.While he is on trial in The Apology, Socrates tells the jury that, â€Å"The unexamined life is not worth living† (Plato pg. 24) Living life without asking questions, and without inquiry, is not living life at all, and is therefore worthless. As an Athenian himself, Socrates wants to help the fellow men of his city led â€Å"examined† lives and is quick to let them know, if they do away with him, there might never be someone else who does for the m what he is attempting to do. In conclusion, Socrates is

Questions on Finance - 1947 Words

FIN 3403 SAMPLE MIDTERM EXAM II 1. A share of common stock has a current price of $82.50 and is expected to grow at a constant rate of 10 percent. If you require a 14 percent rate of return, what is the current dividend on this stock? a. $3.00 b. $3.81 c. $4.29 d. $4.75 e. $6.13 ANS: A = $4.40 = D0 (1.10) D0 = $3.00. DIF: Easy OBJ: TYPE: Problem TOP: Constant growth stock 2. The last dividend paid by Klein Company was $1.00. Kleins growth rate is expected to be a constant 5 percent for 2 years, after which dividends are expected to grow at a rate of 10 percent forever. Kleins required rate of return on equity (ks) is 12 percent. What is the current price of Kleins common stock? a. $21.00 b. $33.33 c. $42.25 d. $50.16 e. $58.75†¦show more content†¦(In other words, what is P3?) a. $40.00 b. $42.35 c. $45.67 d. $46.31 e. $49.00 ANS: E Step 1 Calculate ks: ks = kRF + (RPM)ï  ¢ = 6% + (5%)1.2 = 12%. Step 2 Calculate g: 7% = g Step 3 Calculate : = (1 + g)3 = $40(1.07)3 = $49.00 7. The Seattle Corporation has been presented with an investment opportunity which will yield cash flows of $30,000 per year in Years 1 through 4, $35,000 per year in Years 5 through 9, and $40,000 in Year10. This investment will cost the firm $150,000 today, and the firms required rate of return is 10 percent. Assume cash flows occur evenly during the year, 1/365th each day. What is the payback period for this investment? a. 5.23 years b. 4.86 years c. 4.00 years d. 6.12 years e. 4.35 years ANS: B Using the even cash flow distribution assumption, the project will completely recover initial investment after 30/35 = 0.86 of Year 5: DIF: Easy OBJ: TYPE: Problem TOP: Payback period 8. The capital budgeting director of Sparrow Corporation is evaluating a project which costs $200,000, is expected to last for 10 years and produce after-tax cash flows, including depreciation, of $44,503 per year. If the firms required rate of return is 14 percent and its tax rate is 40 percent, what is the projects IRR? a. 8% b. 14% c. 18% d. -5% e. 12% ANS: C Tabular solution: $200,000 = $44,503 (PVIFAIRR,10) PVIFAIRR,10 = 4.49408 IRR ï‚ » 18% Financial calculatorShow MoreRelatedFinance Questions723 Words   |  3 Pages Provide detailed descriptions and show all calculations used to arrive at solutions for the following questions: 1. Community Hospital has annual net patient revenues of $150 million. At the present time, payments received by the hospital are not deposited for six days on average. The hospital is exploring a lockbox arrangement that promises to cut the six days to one day. If these funds released by the lockbox arrangement can be invested at 8 percent, what will the annual savings be? Assume theRead MoreQuestion Finance950 Words   |  4 PagesEXERCISE 5 (RISK AND RETURN) 1. Perry purchased 100 shares of Ferro, Inc. common stock for $25 per share one year ago. 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