PPT-Security issues in Parallel and Distributed Computing -

Side channel attacks and defenses Presented by Kazi Mejbaul Islam Introduction and Background Microarchitecture Cache hierarchy Side channels in microarchitecture Threats in parallel and distributed systems. Unlike sequential algorithms parallel algorithms cannot be analyzed very well in isolation One of our primary measures of goodness of a parallel system will be its scalability Scalability is the ability of a parallel system to take advantage of incr Uni processor computing can be called centralized computing brPage 3br mainframe computer workstation network host network link terminal centralized computing distributed computing A distributed system is a collection of independent computers interc Goals for Rest of Course. Learn how to program massively parallel processors and achieve. high performance. functionality and maintainability. scalability across future generations. Acquire technical knowledge required to achieve the above goals. Presented by : Ahmed Alalawi. Outline. Introduction. Cloud Computing Components.. Security Issues.. Information Security requirements (ISR). Policy Based and Layered Infrastructure Security :. Dynamic Infrastructure Security Model. Improving Computer Performance. What performance translates into:. Time taken to do computation. Improving performance . → reducing time taken. What key benefits improving performance can bring:. Can solve “now-computationally-attainable” problems in . Jost Berthold. Simon Marlow. Abyd Al Zain. Kevin Hammond. The Parallel Haskell Landscape. research into parallelism using Haskell has been ongoing since the late 1980s. semi-implicit, deterministic programming model: . A View from Berkeley. Dave Patterson. Parallel Computing Laboratory. U.C. Berkeley. July, 2008. Outline. What Caused the Revolution?. Is it an Interesting, Important Research Problem or Just Doing Industry’s Dirty Work?. Recall: Microprocessors are classified by how memory is organized. Tightly-coupled multiprocessor systems use the same memory. They are also referred to as . shared memory multiprocessors. .. The processors do not necessarily have to share the same block of physical memory: . Prof. Nalini Venkatasubramanian. Distributed Systems Middleware - Lecture 2. Global Time & Global States of Distributed Systems. Asynchronous distributed systems consist of several . processes. without common memory which communicate (solely) via . Privacy, Security and Trust Issues arising from Cloud Computing Siani Pearson and Azzedine Benameur International Conference of Cloud Computing Technology and Science, 2010 Presented by Shameek Bhattacharjee Chap 7: Security in Networks. This Chapter Examines…. Threats against networked applications, including denial of service, web site defacements, malicious mobile code, and protocol attacks . Controls against network attacks: physical security, policies, procedures, and other technical controls . CS 6260. Professor: Elise De . Doncker. By: . Lina. Hussein. 1. Topics Covered :. Introduction. What is cluster computing?. Classification of Cluster Computing. Technologies:. Beowulf cluster. Construction of Beowulf Cluster. Dr. . Barsha. . Mitra. CSIS . Dept. , BITS Pilani, Hyderabad Campus. Introduction. Course ID: SS ZG526, Title: Distributed Computing. allows for flexibly sharing resources (e.g., files and multimedia documents) stored across network-wide computers. Computer Science. Purdue University. Research in Cloud Computing. YounSun Cho. cho52@cs.purdue.edu. Computer Science. Purdue University. Anya Kim. anya.kim@nrl.navy.mil. Naval Research Lab. Talk Objectives.