Wednesday, March 15, 2017

Essential HPC Finance Practice: Total Cost of Ownership (TCO), Internal Funding, and Cost-Recovery Models
The tutorial provides an impartial, practical, non-sales focused guide to the financial aspects of HPC facilities and service. It presents a rare and invaluable opportunity for HPC managers, practitioners, and stakeholders to learn more about calculating and using TCO models; along with the pros and cons of different internal cost recovery and funding models. Well-managed TCO, return on investment and cost recovery models can be hugely beneficial to HPC managers and operators by demonstrating the value of HPC to the organization, driving the continuation and growth of HPC investment. They can also help uncover practical improvements to deliver better services to users. Attendees will benefit from exploration of the main issues, pros and cons of differing approaches, practical tips, hard-earned experience and potential pitfalls. After the tutorial, attendees will be in a stronger position to calculate and use TCO within their organizations, and to design and use internal cost-recovery models. The tutorial is based on experience across a diverse set of real world cases in various countries, in both private and public sectors, with projects of all sizes and shapes.
Andrew Jones (NAG),  Owen Thomas (Red Oak Consulting)
PETSc: The Portable, Extensible Toolkit for Scientific Computation
PETSc, is a suite of data structures and routines for the scalable parallel solution of nonlinear equations, often arising from partial differential equations or boundary integral equations. PETSc has been used for years in the oil and gas industry, including development contributed back from WesternGeco and Shell. It supports MPI,
shared memory pthreads, and GPUs, as well as hybrid MPI-shared memory pthreads or MPI-GPU parallelism. In this brief tutorial, we will highlight basic sparse parallel linear algebra, linear and nonlinear algebraic solvers, structured and unstructured meshes, and timestepping. We will show how optimal, hierarchical, multilevel solvers for complex, multiphysics problems can be dynamically assembled using the PETSc object system.
Matthew G. Knepley, Asst. Professor, Computational and Applied Mathematics, Rice University

10:30-12:00pm (Room 280)
Introduction to OpenMP 4.0 and 4.5
For over a decade, OpenMP has been the de-facto standard for parallel programming on shared memory systems. It has continued to evolve in order to meet the programming needs of a diversity of application developers, and to handle the requirements of new generations of computer architecture. In this tutorial we give a brief overview of the basics of OpenMP and then introduce the new features on OpenMP 4.0 and 4.5, with short examples to illustrate their usage.
Barbara Chapman, Stony Brook, Xinmin Tian, Intel, Amit Amritkar, University of Houston and Deepak Eachempati, Cray Research

10:30-12:00pm (Room 282)
Parallel Adaptive PDE Simulation with libMesh
The libMesh C++ library is an open source set of tool classes and frameworks designed to enable easy yet flexible development of applications for the simulation of boundary value problems on hybrid parallel supercomputers. Utilities for a posteriori adaptive refinement of unstructured and even multi-dimensional meshes allow users to efficiently resolve many multiscale problem-dependent solution features automatically, and support for adjoint methods allows users to perform goal-oriented refinement or parameter
sensitivity analysis based on the specific quantities of interest they intend to post-process. This session will give a brief introduction to finite element software design with libMesh, show how the more advanced capabilities can be enabled, and introduce examples of
libMesh-based application frameworks from academia, the national laboratories, and private industry which have been designed for third party use.
Roy Stogner, Institute for Computational Engineering & Science, University of Texas

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