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Lecture 4 principles of parallel algorithm design updatedVajira Thambawita
The main principles of parallel algorithm design are discussed here. For more information: visit, https://sites.google.com/view/vajira-thambawita/leaning-materials
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Lecture 4 principles of parallel algorithm design updatedVajira Thambawita
The main principles of parallel algorithm design are discussed here. For more information: visit, https://sites.google.com/view/vajira-thambawita/leaning-materials
Error tolerant resource allocation and payment minimization for cloud systemIEEEFINALYEARPROJECTS
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The theory behind parallel computing is covered here. For more theoretical knowledge: https://sites.google.com/view/vajira-thambawita/leaning-materials
program partitioning and scheduling IN Advanced Computer ArchitecturePankaj Kumar Jain
Advanced Computer Architecture,Program Partitioning and Scheduling,Program Partitioning & Scheduling,Latency,Levels of Parallelism,Loop-level Parallelism,Subprogram-level Parallelism,Job or Program-Level Parallelism,Communication Latency,Grain Packing and Scheduling,Program Graphs and Packing
A natural extension of the Random Access Machine (RAM) serial architecture is the Parallel Random Access Machine, or PRAM.
PRAMs consist of p processors and a global memory of unbounded size that is uniformly accessible to all processors.
Processors share a common clock but may execute different instructions in each cycle.
Along with idling and contention, communication is a major overhead in parallel programs.
The cost of communication is dependent on a variety of features including the programming model semantics, the network topology, data handling and routing, and associated software protocols.
Scheduling in distributed systems - Andrii VozniukAndrii Vozniuk
My EPFL candidacy exam presentation: http://wiki.epfl.ch/edicpublic/documents/Candidacy%20exam/vozniuk_andrii_candidacy_writeup.pdf
Here I present how schedulers work in three distributed data processing systems and their possible optimizations. I consider Gamma - a parallel database, MapReduce - a data-intensive system and Condor - a compute-intensive system.
This talk is based on the following papers:
1) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
2) Improving MapReduce performance in heterogeneous environments by Matei Zaharia, Andy Konwinski, Anthony D. Joseph, Randy Katz and Ion Stoica
3) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
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The theory behind parallel computing is covered here. For more theoretical knowledge: https://sites.google.com/view/vajira-thambawita/leaning-materials
program partitioning and scheduling IN Advanced Computer ArchitecturePankaj Kumar Jain
Advanced Computer Architecture,Program Partitioning and Scheduling,Program Partitioning & Scheduling,Latency,Levels of Parallelism,Loop-level Parallelism,Subprogram-level Parallelism,Job or Program-Level Parallelism,Communication Latency,Grain Packing and Scheduling,Program Graphs and Packing
A natural extension of the Random Access Machine (RAM) serial architecture is the Parallel Random Access Machine, or PRAM.
PRAMs consist of p processors and a global memory of unbounded size that is uniformly accessible to all processors.
Processors share a common clock but may execute different instructions in each cycle.
Along with idling and contention, communication is a major overhead in parallel programs.
The cost of communication is dependent on a variety of features including the programming model semantics, the network topology, data handling and routing, and associated software protocols.
Scheduling in distributed systems - Andrii VozniukAndrii Vozniuk
My EPFL candidacy exam presentation: http://wiki.epfl.ch/edicpublic/documents/Candidacy%20exam/vozniuk_andrii_candidacy_writeup.pdf
Here I present how schedulers work in three distributed data processing systems and their possible optimizations. I consider Gamma - a parallel database, MapReduce - a data-intensive system and Condor - a compute-intensive system.
This talk is based on the following papers:
1) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
2) Improving MapReduce performance in heterogeneous environments by Matei Zaharia, Andy Konwinski, Anthony D. Joseph, Randy Katz and Ion Stoica
3) Batch Scheduling in Parallel Database Systems by Manish Mehta, Valery Soloviev and David J. DeWitt
Dear students get fully solved assignments by professionals
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Aarong's Tanvir Hossain presents at Social Innovation Lab's Innovation Forum on "Breaking down the silos: Lessons from cross-porgramme initiatives at BRAC"
There is a lot of confusion and misunderstanding about what the Affordable Care Act (Obamacare) is and how it will affect your business and employees. It is important to learn how it relates to you, your employees and your business. There are many moving parts and there are changes ahead. Our blog series and webinars will describe what the Affordable Care Act is "in plain English" and keep you up to date on the latest information.
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Introduction to distributed systems
Architecture for Distributed System, Goals of Distributed system, Hardware and Software
concepts, Distributed Computing Model, Advantages & Disadvantage distributed system, Issues
in designing Distributed System,
Concurrency and Parallelism, Asynchronous Programming, Network ProgrammingPrabu U
The presentation starts with concurrency and parallelism. Then the concepts of reactive programming is covered. Finally network programming is detailed
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Cloud Computing Load Balancing Algorithms Comparison Based SurveyINFOGAIN PUBLICATION
Cloud computing is an online primarily based computing. This computing paradigm has increased the employment of network wherever the potential of 1 node may be used by alternative node. Cloud provides services on demand to distributive resources like info, servers, software, infrastructure etc. in pay as you go basis. Load reconciliation is one amongst the vexing problems in distributed atmosphere. Resources of service supplier have to be compelled to balance the load of shopper request. Totally different load reconciliation algorithms are planned so as to manage the resources of service supplier with efficiency and effectively. This paper presents a comparison of assorted policies used for load reconciliation.
Hardback solution to accelerate multimedia computation through mgp in cmpeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Analysis of a Pool Management Scheme for Cloud Computing Centres by Using Par...IJERA Editor
A monolithic model may suffer from and poor scalability due to large number of parameters. A cloud user may
submit a super task at once. The user request is sent to the global queue and then to the Resource Assigning
Module (RAM). A number of heterogeneous server pools placed in the RAM. First is Hot, in which the servers
will be handling the jobs currently, second is Warm, in which the servers are kept in ideal state, then Finally
Cold, in which the servers are Turned Off state. Initially the request is send to Hot, if those servers are busy the
request is forwarded to warm, then finally if required to Cold if both the hot and warm server pools are busy.
The user submitted supertask may split so that the individual task run on different physical machines, this is
called as partial acceptance policy. So the supertask rejection ratio will be reduced.
Machine learning in Dynamic Adaptive Streaming over HTTP (DASH)Eswar Publications
Recently machine learning has been introduced into the area of adaptive video streaming. This paper explores a novel taxonomy that includes six state of the art techniques of machine learning that have been applied to Dynamic Adaptive Streaming over HTTP (DASH): (1) Q-learning, (2) Reinforcement learning, (3) Regression, (4) Classification, (5) Decision Tree learning, and (6) Neural networks.
A survey of various scheduling algorithm in cloud computing environmenteSAT Journals
Abstract Cloud computing is known as a provider of dynamic services using very large scalable and virtualized resources over the Internet. Due to novelty of cloud computing field, there is no many standard task scheduling algorithm used in cloud environment. Especially that in cloud, there is a high communication cost that prevents well known task schedulers to be applied in large scale distributed environment. Today, researchers attempt to build job scheduling algorithms that are compatible and applicable in Cloud Computing environment Job scheduling is most important task in cloud computing environment because user have to pay for resources used based upon time. Hence efficient utilization of resources must be important and for that scheduling plays a vital role to get maximum benefit from the resources. In this paper we are studying various scheduling algorithm and issues related to them in cloud computing. Index Terms: cloud computing, scheduling, algorithm
A survey of various scheduling algorithm in cloud computing environmenteSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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(SPRING 2015 ASSIGNMENT
PROGRAM BCA (REVISED FALL 2012)
SEMESTER 2
SUBJECT CODE & NAME BCA2010 – OPERATING SYSTEM
CREDIT 2
BK ID B1405
MAX.MARKS 60
Note: Answer all questions. Kindly note that answers for 10 marks questions should be
approximately of 400 words. Each question is followed by evaluation scheme.
1. Differentiate between Simple Batch Operating Systems and Timesharing Operating Systems.
Answer : Batch Operating System:
In earlycomputersystems,the userdidnotinteractdirectlywiththe computersystem.The dataand
programswere firstprepared on the input media such as punched cards or punched tape. The data
and programspreparedonthe punchedtape or punched cards were referred to as jobs. These jobs
were submitted to the computer operator. The computer operator would arrange the jobs into
propersequence knownasbatchesandrun the batchesthroughthe computer. The batch operating
system was used to manage and control such type of operations.
The simple batchoperatingsystemtransfersthe jobs to the processor one by one. When one job is
completed, then control is transferred to
2 Explain the different process states.
Answer : A process is a program in execution. The execution of a process must progress in a
sequential fashion. Definition of process is following.
A processwhichis Executedbythe Processhave variousStates,the State of the Processisalsocalled
as the Status of the process,The Status includes whether the Process has Executed or Whether the
processisWaitingfor Some input and output from the user and whether the Process is Waiting for
the CPU to Run the Program after the Completion of the Process.
The various States of the Process are as Followings:-
1) New State : When a user request for a Service
2. 3 Define Deadlock. Explain necessary conditions for deadlock.
Answer : A deadlock is a situation in which two computer programs sharing the same resource are
effectivelypreventingeachotherfromaccessingthe resource,resultinginboth programs ceasing to
function.The earliestcomputeroperatingsystemsranonlyone program at a time. Eventually some
operating systems offered dynamic allocation of resources. Programs could request further
allocations of resources after they had begun running. This led to the problem of the deadlock.
Coffman (1971) identified four (4) conditions that must hold simultaneously for there to be a
deadlock.
4. Differentiate between Sequential access and direct access methods.
Answer : The hypertext and hyperlink exemplify the direct-access paradigm and are a significant
improvement over the more traditional, book-based model of sequential access.
(Directaccesscan also be calledrandomaccess,because itallowsequallyeasyandfastaccess to any
randomlyselecteddestination.Somewhatlike traveling by a Star Trek transporter instead of driving
alongthe freewayandpassingthe exitsone ata time,whichiswhatyou getwithsequentialaccess.)
In a normal, physical book, the reader is supposed to read pages one by one, in the order in which
theyare providedbythe author.Formost books(fiction,atleast),itmakeslittle sense forthe reader
to turn directlypage 256 andstart readingthere.Unless,of course, that is where the reader left off
in their last reading session. Getting to page 256 in a 500-
5. Differentiate between Daisy chain bus arbitration and Priority encoded bus arbitration.
Answer : In most mini- and mainframe computer systems, a great deal of input and output occurs
betweenthe disksystemandthe processor.Itwouldbe veryinefficienttoperformthese operations
directlythroughthe processor;itismuch more efficientif such devices, which can transfer data at a
veryhighrate,place the data directlyintothe memory,or take the data directly from the processor
without direct intervention from the processor. I/O performed in this way is usually called direct
memory access, or DMA. The controller for a device employing DMA must have the capability of
generating address signals for the memory, as well as all of the memory control signals. The
processor informs the DMA controller that data is available (or is to be placed into) a block of
memory locations starting at a certain address in
3. 6. Explain LRU page replacement algorithm with example
Answer:A goodapproximationtothe optimal algorithmisbasedonthe observation that pages that
have been heavily used in the last few instructions will probably be heavily used again in the next
few. Conversely, pages that have not been used for ages will probably remain unused for a long
time. This idea suggests a realizable algorithm: when a page fault occurs, throw out the page that
has been unused for the longest time. This strategy is called LRU (Least Recently Used) paging.
Although LRU is theoretically realizable, it is not cheap. To fully implement LRU, it is necessary to
maintaina linkedlistof all pages in memory, with the most recently used page at the front and the
leastrecentlyusedpage atthe rear. The difficultyisthatthe list must be updated on every memory
reference. Finding a page in the list, deleting it,
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