XSEDE15

Today, many new HPC systems such as Stampede are heterogeneous systems containing traditional processors, co-processors, and/or accelerators. These hardware designs for performance and efficiency greatly complicate the development of large scale applications that now require the consideration of at least three different levels of parallelism (MPI, threading, SIMD) with quite different performance considerations.
 
This tutorial will target application developers who are developing applications for multi- and many- core systems with a focus on the Intel Xeon Phi platform, also known as the MIC. In addition to a presentation of the programming models that are available on systems with MIC co-processors, the tutorial will provide users with hands-on guidance in using wide SIMD units through vectorization, large thread counts on each node through OpenMP, and symmetric and offload modes of execution. Accounts on Stampede will be used for the laboratory exercises.
 
At the completion of the tutorial, the audience will:
* Have hands on experience with the use of Intel's vec-reports options.
* Understand how to create arrays aligned for optimal vectorization.
* Be able to create asynchronous offload codes and control data persistence on the Xeon Phi.
* Understand how to properly place threads/tasks on the Xeon Phi when running in either offload or symmetric mode.

While R has not been considered a traditional application in HPC, R has become the lingua franca for many areas of data analysis, drawing power from its high level expressiveness and its multitude of domain-specific, community-developed packages. In recent years, many efforts by the R and HPC communities have focused on bridging this gap for scaling R to the power of supercomputers. The interest in using R with supercomputing is indeed on the rise within the XSEDE community as well. The two most recent workshops on R organized by NICS and TACC have drawn hundreds of registrations and online participants. The goal of this tutorial is to provide guidance to participants on improving and scaling up existing scientific analysis workflows with R in order to best utilize the resources available through XSEDE. The tutorial consists of two major components. The morning sessions focus on helping users to develop efficient R code. The presentations include how to profile R code and best practices in writing and compiling R code for efficiency. The afternoon session will focus on approaches to scale R computations on resources that are supported by XSEDE. The presentations include using parallel packages (such as parallel, pbdR) with R, utilizing hardware accelerators (such as Xeon Phi and GPGPU) and bridging R with other big data analysis systems (such as Hadoop and Spark).