PPT-Appliance-based architectures for high performance data intensive applications Session

Session at Silicon India Rajgopal Kishore Vice President and Global Head of BI amp Analytics HCL Technologies rkishorehclin rkishore9gmailcom State of data Challenges Need of the day. Hardware Parallelism. Computing: execute instructions that operate on data.. Flynn’s . taxonomy (Michael Flynn, 1967) classifies computer architectures based on the number of instructions that can be executed and how they operate on data.. “Computing . is changing more rapidly than ever before, and scientists have the unprecedented opportunity to change computing . directions” . “In . 20 or 30 years, you'll be able to hold in your hand as much computing knowledge as exists now in the whole city, or even the whole world. Session at . Silicon India. Rajgopal Kishore. Vice President and Global Head of BI & Analytics, . HCL Technologies. rkishore@hcl.in. rkishore9@gmail.com. . State of data. Challenges. Need of the day. Yu David Liu. State University of New York (SUNY). at Binghamton. FOAL 2015. Modular Performance Reasoning of. Data-Intensive Programs. Yu David Liu. State University of New York (SUNY). at Binghamton. Overview . Rationale . for . intensive intervention. Introduction . to . Data-Based Individualization (DBI). Academic illustration. Behavior illustration. Wrap-up. Today’s Presentation . 2. Learning Objectives. Efficient and scalable architectures to perform pleasingly parallel, MapReduce and iterative data intensive computations on cloud environments. Thilina. . Gunarathne. (tgunarat@indiana.edu). Advisor : . Software Architecture. Describe how the various software components are to be organized and how they should interact.. It describe the organization and interaction of software components.. System Architecture. by Mahedi Hasan. 1. Table of Contents. Introducing Cluster Concept. About Cluster Computing. Concept of whole computers and it’s benefits. Architecture and Clustering Methods. Different clusters catagorizations. Yu David Liu. State University of New York (SUNY). at Binghamton. FOAL 2015. Modular Performance Reasoning of. Data-Intensive Programs. Yu David Liu. State University of New York (SUNY). at Binghamton. Overview . Rationale . for . intensive intervention. Introduction . to . Data-Based Individualization (DBI). Academic illustration. Behavior illustration. Wrap-up. Today’s Presentation . 2. Learning Objectives. Parallel . Architectures. . & Performance Analysis. Parallel computer: multiple-processor system supporting parallel programming.. Three principle types of architecture. Vector computers, in particular processor arrays. S Jha. 1. , J Qiu. 2. , A Luckow. 1. , P Mantha. 1. , Geoffrey Fox. 2. 1 . Rutgers http://radical.rutgers.edu. 2 . Indiana . . http. ://. www.infomall.org. http://. arxiv.org. /abs/1403.1528. Database Accelerators. Authors: Jian Fang. 1. , Yvo T.B. Mulder. 1. ,. Kangli Huang. 1. , Yang Qiao. 1. ,. Xianwei Zeng. 1. ,. . Jan . Hidders. 2. ,. Jinho Lee. Main Contribution of this Research Work