Dynamic scheduling of irregular stream programs toward many core scalability

•

0 likes•111 views

Dynamic scheduling of irregular stream programs toward many core scalability +91-9994232214,8144199666, ieeeprojectchennai@gmail.com, www.projectsieee.com, www.ieee-projects-chennai.com IEEE PROJECTS 2015-2016 ----------------------------------- Contact:+91-9994232214,+91-8144199666 Email:ieeeprojectchennai@gmail.com Support: ------------- Projects Code Documentation PPT Projects Video File Projects Explanation Teamviewer Support

Education

Dynamic Scheduling of Irregular Stream Programs toward Many-Core
Scalability
Abstract:
The stream programming model has received much interest because it
naturally exposes task, data, and pipeline parallelism. However, most
priorwork has focused on the static scheduling of regular stream programs.
Therefore, irregular applications cannot be handled in static scheduling,
and the load imbalance caused by static scheduling faces scalability
limitations in many-core systems. In this paper, we introduce the DANBI
programming model, which supports irregular stream programs, and
propose dynamic scheduling techniques. Scheduling irregular stream
programs is very challenging, and the load imbalance becomes a major
hurdle to achieving scalability. Our dynamic load-balancing scheduler
exploits producer-consumer relationships already expressed in the DANBI
program to achieve scalability. Moreover, it effectively avoids the
thundering-herd problem and dynamically adapts to load imbalance in a
probabilistic manner. It surpasses prior static stream scheduling
approaches which are vulnerable to load imbalance and also surpasses
prior dynamic stream scheduling approaches which result in many
restrictions on supported program types, on the scope of dynamic
scheduling, and on data ordering preservation. Our experimental results

on a 40-core server show that DANBI achieves an almost linear scalability
and outperforms state-of-the-art parallel runtimes by up to 2.8 times.
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk ` : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• RAM : 256 Mb.
Software Requirements:
• Operating system : - Windows XP.
• Front End : - JSP
• Back End : - SQL Server
Software Requirements:
• Operating system : - Windows XP.
• Front End : - .Net

The document discusses the next generation design of Hadoop MapReduce. It aims to address scalability, availability, and utilization limitations in the current MapReduce framework. The key aspects of the new design include splitting the JobTracker into independent resource and application managers, distributing the application lifecycle management, enabling wire compatibility between versions, and allowing multiple programming paradigms like MPI and machine learning to run alongside MapReduce on the same Hadoop cluster. This architecture improves scalability, availability, utilization, and agility compared to the current MapReduce implementation.

Simple Helix Presentation | The 2nd Annual eCommerce Expo South Florida

Rand Internet Marketing

1. The document discusses planning for variable traffic on a Magento site by moving to a stateless architecture that allows horizontal and vertical scaling. 2. A stateless design keeps no local session or state records, allowing unlimited scaling of nodes and centralized data storage. 3. The summary outlines how to expand a Magento cluster from a single server to a stateless configuration with load balancing, separate databases, caching, and media servers for scalability.

A Modified Genetic Algorithm based Load Distribution Approach towards Web Hot...

idescitation

Web hotspot is a serious problem often experienced in case popular websites. It provides dramatic load spike in a website, which occurs when a huge number of users accessing the same website. A prominent solution to this problem is server load balancing. Dynamic load balancing involves allocation of requests to the server or processor dynamically when they arrive. For effective load balancing, a near-optimal schedule of incoming requests or processes must be determined “on-the-fly”, so that execution of requests can be completed in shortest possible time. So we have proposed a Genetic Algorithm based load balancing scheme which relies on a process scheduling policy. Genetic Algorithm provides to search for the optimal solution out a search of candidate solutions. It follows the survival-of-the-fittest principle, to achieve the optimal solution, through a number of generations. The proposed algorithm is evaluated for various population size and number of generations, to maximize the processor utilization of nodes/ processors in the system.

Efficient Dynamic Load-Balance Flow Scheduling in cloud for Big Data Centers.

IRJET Journal

This document proposes a novel dynamic load balancing scheduling (DLBS) approach to maximize network throughput in big data centers by dynamically balancing data flows. It formulates the DLBS problem and develops heuristic scheduling algorithms for two OpenFlow network models - three-layer non-blocking fully populated network (FPN) and three-layer fat-tree network (FTN). The algorithms balance data flows each time slot by migrating the largest flows on the most congested links to the lightest links. Experimental results show DLBS significantly improves network performance compared to other load balancing algorithms under different traffic patterns.

A Study on Replication and Failover Cluster to Maximize System Uptime

YogeshIJTSRD

This document summarizes a study on using replication and failover clusters to maximize system uptime for cloud services. It discusses challenges in ensuring high availability of cloud services from a provider perspective. The study aims to present a high availability solution using load balancing, elasticity, replication, and disaster recovery configuration. It reviews related literature on digital media distribution platforms, content delivery networks, auto-scaling strategies, and database replication impact. It also covers methodologies like CloudFront, state machine replication, neural networks, Markov decision processes, and sliding window protocols. The scope is to build a scalable, fault-tolerant environment with disaster recovery and ensure continuous availability. The conclusion is that data replication and failover clusters are necessary to plan data

IRJET- Commercial Web Application Load Balancing based on Hybrid Cloud

IRJET Journal

This document discusses load balancing of traffic from a commercial web application across instances on Amazon Web Services (AWS) cloud infrastructure. It begins with an abstract describing the goal of balancing traffic across AWS to reduce hardware needs. It then covers background on load balancing, AWS services like EC2 instances, and algorithms like round robin. The methodology section outlines deploying a website to a private cloud, using AWS services like Elastic Load Balancer and auto-scaling instances to balance traffic. Load is balanced using a round robin algorithm across instances to improve website performance and user experience. In conclusion, balancing traffic across a hybrid cloud provides smooth access to websites for users.

Conference Paper: CHASE: Component High-Availability Scheduler in Cloud Compu...

Ericsson

Cloud computing promises flexible integration of the compute capabilities for on-demand access through the concept of virtualization. However, uncertainties are raised regarding the high availability of the cloud-hosted applications. High availability is a crucial requirement for multi-tier applications providing business services for a broad range of enterprises. This paper proposes a novel component high availability-aware scheduling technique, CHASE, which maximizes the availability of applications without violating service level agreements with the end-users. This paper presents the advantages and shortcomings of CHASE compared to an optimal solution, OpenStack Nova scheduler,high availability-agnostic, and redundancy-agnostic schedulers.The evaluation results demonstrate that the proposed solution improves the availability of the scheduled components compared to the latter schedulers. CHASE prototype is also defined for runtime scheduling in OpenStack environment. Full abstract in IEEE Xplore, DOI: 10.1109/CLOUD.2015.70 Authors Ali Kanso, Ericsson Resarch; Manar Jammal, Abdallah Shami, Western University, London, Canada. Published June 27, 2015, IEEE 8th International Conference on Cloud Computing (CLOUD). © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

How to Build a Scalable Web Application for Your Project

BitCot

Case Study 4 Carlson Companies Carlson Companies is one of the largest privately held companies in the United States, with more than 180,000 employees in more than 140 countries. Carlson enterprises include a presence in marketing, business and leisure travel, and hospitality industries. Its Information Technology (IT) division, Carlson Shared Services, acts as a service provider to its internal clients and consequently must support a spectrum of user applications and services. The IT division uses a centralized data processing model to meet business operational requirements. The central computing environment includes an IBM mainframe and over 50 networked Hewlett-Packard and Sun servers [KRAN04, CLAR02, HIGG02]. The mainframe supports a wide range of applications, including Oracle financial database, e-mail, Microsoft Exchange, Web, PeopleSoft, and a data warehouse application. In 2002, the IT division established six goals for assuring that IT services continued to meet the needs of a growing company with heavy reliance on data and applications: Implement an enterprise data warehouse. Build a global network. Move to enterprise-wide architecture. Established six-sigma quality for Carlson clients. Facilitate outsourcing and exchange. Leverage existing technology and resource. The key to meeting these goals was to implement a storage area network (SAN) with a consolidated, centralized database to support mainframe and server applications. Carlson needed a SAN and data center approach that provided a reliable, highly scalable facility to accommodate the increasing demand of its users. Storage Requirements Until recently, the central DP shop included separate disc storage for each server, plus that of the mainframe. This dispersed data storage scheme had the advantage of responsiveness; that is, the access time from a server to its data was minimal. However, the data management cost was high. There had to be backup procedures for the storage on each server, as well as management controls to reconcile data distributed throughout the system. The mainframe included an efficient disaster recovery plan to preserve data in the event of major system crashes or other incidents and to get data back online with little or no disruption to the users. No comparable plan existed for the many servers. As Carlson’s databases grow beyond 10 terabytes (TB) of business-critical data, the IT team determined that a comprehensive network storage strategy would be required to manage future growth. Solution Concept The existing Carlson server complex made use of Fibre Channel links to achieve communication and backup capabilities among servers. Carlson considered extending this capability to a full-blown Fibre Channel SAN that would encompass the server, the mainframe, and massive centralized storage facilities. The IT team concluded that further expansion using Fibre Channel technologies alone would be difficult and costly to manage. At the same time, in supporting ...

Best Practices for Building Scalable Web Applications.pdf

Isabella Barry

short presentation on caching Caching.ppt

yakashthapar2

IEEE Cloud computing 2016 Title and Abstract

tsysglobalsolutions

Storage area network (san)

Satwik Kumar Shiri

This document outlines a presentation on policy-based validation of SAN (storage area network) configurations. It introduces SANs and compares them to NAS (network-attached storage). It then discusses factors like global access, economics, issues, and challenges in SAN management. It covers relevant data structures, protocols, components like HBAs. The future work section outlines an architecture for policy-based validation including a policy evaluator, request generator, and action handler.

AWSQ: an approximated web server queuing algorithm for heterogeneous web serv...

IJECEIAES

With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster.

Strategies for Developing Web Applications with Java (1).pdf

GeorgeThomas874377

M.E Computer Science Data Mining Projects

Vijay Karan

Cawsac cost aware workload scheduling and admission control for distributed c...

ieeepondy

An Efficient Distributed Control Law for Load Balancing in Content Delivery N...

IJMER

International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education. International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.

M 94 4

Jack Bloomberg

This paper discusses cloud application services (SaaS) and emphasizes that a SaaS application's data architecture should be robust, secure, efficient, cost-effective, and highly manageable. It argues that multi-tenancy and a meta-data driven architecture can address these issues. The paper outlines three approaches to multi-tenant data management and describes concepts like a meta-data driven reference architecture and conceptual data model. It also compares green field SaaS implementation to migrating an existing application to a SaaS model, noting the latter requires more assessment.

Cloud application services (saa s) – multi tenant data architecture

Johnny Le

The document discusses cloud application services (SaaS) and multi-tenant data architectures. It describes SaaS as software delivered over the internet that eliminates installing/running applications locally. A multi-tenant architecture allows one application instance to serve multiple organizations, lowering costs. There are three approaches to multi-tenant data management with varying levels of isolation. The document advocates for a metadata-driven reference architecture where application components are generated from metadata at runtime to serve tenants' unique needs. It provides conceptual models of the metadata-driven approach.

saas

Prasad Raju

The document discusses three key challenges of implementing Software as a Service (SaaS): multi-tenant deployment, scalability, and reliability. Multi-tenant deployment involves sharing resources among multiple customers simultaneously. Scalability refers to an application's ability to handle increased load by adding more servers. Reliability ensures accurate services and avoids failures by handling error detection and recovery.

M phil-computer-science-data-mining-projects

Vijay Karan

This document provides summaries for several M.Phil Computer Science Data Mining Projects written in C#. The projects cover topics such as bridging virtual communities, mood recognition during online tests, surveying the size of the World Wide Web, knowledge sharing in virtual organizations, adaptive provisioning of human expertise in service-oriented systems, cost-aware rank joins with random and sorted access, improving data quality with dynamic forms, targeted data delivery algorithms, and sentiment classification using feature relation networks.

M.Phil Computer Science Data Mining Projects

Vijay Karan

ACCELERATE SAP® APPLICATIONS WITH CDNETWORKS

CDNetworks

CDNetworks and SAP conducted a proof of concept project to test how CDNetworks' content delivery network (CDN) service could accelerate SAP applications. Testing showed the CDN provided significant performance improvements, reducing response times for login and file downloads by 50-66% on average globally. The CDN also improved reliability, with no errors observed during stress testing of 10,000 transactions, whereas the internet saw around a 4% failure rate. The CDN's global infrastructure and security features were found to enhance the delivery, speed, and reliability of SAP applications for distributed users worldwide.

A big-data architecture for real-time analytics

ramikaurraminder

This paper describes a framework called Real-time Analytics Foundation (RAF) that supports low-latency analytics on large datasets by combining in-memory processing with resilient updates. RAF uses Resilient Distributed Datasets (RDDs) to store data in memory across clusters for fault tolerance. It introduces delegates that bridge data between storage and RDDs to share data efficiently in memory. Evaluation shows RAF provides orders of magnitude latency improvements over HDFS for queries and high scalability for updates.

Distributed RDBMS: Data Distribution Policy: Part 3 - Changing Your Data Dist...

ScaleBase

This document discusses how data distribution policies for distributed relational database systems (RDBMS) need to change and adapt over time to match evolving application usage patterns, workloads, and business needs. It outlines three stages in a data distribution policy's lifecycle where changes are needed: 1) changing demand and traffic loads, 2) changing application usage, and 3) new product capabilities. The key to adapting is regularly "rebalancing" the distributed database by modifying the data distribution policy using software that separates this logic from the application code.

ScaleArc: Why the cloud is no White Knight

ScaleArc

Moving applications to the cloud can introduce challenges like scalability issues due to VM size limitations, I/O bottlenecks due to resource sharing, downtime from hypervisor maintenance, regional outages taking down services, and network latency from distance between devices. These problems stem from how applications access data in the cloud. Database load balancing software provides an abstraction layer between apps and databases that can solve these issues by distributing load, caching queries to reduce I/O, queueing transactions during failovers to prevent downtime, and directing traffic to reduce latency.

Parallel application signature for performance analysis and prediction

Dynamic scheduling of irregular stream programs toward many core scalability

Recommended

Recommended

More Related Content

Similar to Dynamic scheduling of irregular stream programs toward many core scalability

Similar to Dynamic scheduling of irregular stream programs toward many core scalability (20)

More from ieeeprojectschennai

More from ieeeprojectschennai (20)

Recently uploaded

Recently uploaded (20)

Dynamic scheduling of irregular stream programs toward many core scalability