PPT-1 Models and Frameworks for Data Intensive

Cloud Computing Douglas Thain University of Notre Dame IDGA Cloud Computing 8 February 2011 The Cooperative Computing Lab We collaborate with people who have large scale computing problems in science engineering and other fields. Overview . Rationale . for . intensive intervention. Introduction . to . Data-Based Individualization (DBI). Academic illustration. Behavior illustration. Wrap-up. Today’s Presentation . 2. Learning Objectives. Strand Leaders: . Louis Danielson, Ph.D.. . Rebecca O. Zumeta, Ph.D. . National Center on Intensive Intervention (NCII). American Institutes for Research, Washington, DC  . Understand strategies for identifying, intervening, and evaluating progress of students with intensive intervention needs in academics, specifically in reading and mathematics. . Joseph . Wehby. , Ph.D. . NCII Senior Advisor. Vanderbilt University. January 2013 . Today’s Webinar. The need for intensive intervention. Using Data-Based Individualization (DBI) to provide intensive intervention in . Overview . Rationale . for . intensive intervention. Introduction . to . Data-Based Individualization (DBI). Academic illustration. Behavior illustration. Wrap-up. Today’s Presentation . 2. Learning Objectives. Bologna Board. Chişin. ă. u, January 18, 2016. Sjur Bergan, Council of Europe. Two (later three) tier degree structure (1999, 2003). Role of the first degree in the labor market (1999). Recognition (1998 and later). Amy Matthews, Ph.D., . BCBA. Jamie Owen-DeSchryver, PhD. Grand Valley State University. Linda . Elenbaas. Ottawa Area Intermediate School District. What is possible with . intensive, individualized . Science-based on Data-intensive Computing. How to read the text?. Foreword: . A very interesting foreword by Gordon Bell. discusses innovation and discoveries through the centuries…. Data-intensive science consists of three basic activities: data capture, curation and analysis (we will add one: visualization).. Shannon Quinn. Distinction. General Compute Engines. Hadoop. . MapReduce. Spark. User-facing APIs. Cascading / Scalding. Alternative Frameworks. Apache Mahout. Apache . Giraph. GraphLab. Apache Storm. 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. WHAT WENT WRONG AND HOW TO FIX IT. Joseph E. Stiglitz. Adam Smith Lecture. European Economic Association. Glasgow. August 24, 2010. Outline. The failures of the existing paradigm. And the policy frameworks based on them. Strand Leaders: . Louis Danielson, Ph.D.. . Rebecca O. Zumeta, Ph.D. . National Center on Intensive Intervention (NCII). American Institutes for Research, Washington, DC  . Understand strategies for identifying, intervening, and evaluating progress of students with intensive intervention needs in academics, specifically in reading and mathematics. . Michael Robson. Parallel Programming Lab. Charm Workshop 2016. Charm++ GPU Frameworks. 2. Accelerator Overview. NVIDIA GPUs. Programmed with CUDA. 1,000s of threads. 100s GB/s bandwidth. ~16 GB of memory. Cloud Computing. Douglas . Thain. University of Notre Dame. IDGA Cloud Computing. 8 February 2011. The Cooperative Computing Lab. We collaborate with people who have large scale computing problems in science, engineering, and other fields.. Faculty Professional Learning Series: Webinar #4. December 1, 2020. Lindsey Hayes, M.Ed., & Amy Colpo, M.P.P., American Institutes for Research. Lynn Holdheide, M.Ed., CEEDAR Center. Cara McDermott-.