1Managed by UT-Battelle for the U.S. Department of Energy Discussion questions from you 1.Do we care about exaflops machines? 2.How are we going to compare.

Slides:

Advertisements

Similar presentations

Weather Research & Forecasting: A General Overview

Advertisements

Managed by UT-Battelle for the Department of Energy Vinod Tipparaju P2S2 Panel: Is Hybrid Programming a Bad Idea Whose Time Has Come?

Lawrence Livermore National Laboratory ROSE Compiler Project Computational Exascale Workshop December 2010 Dan Quinlan Chunhua Liao, Justin Too, Robb Matzke,

Life and Health Sciences Summary Report. “Bench to Bedside” coverage Participants with very broad spectrum of expertise bridging all scales –From molecule.

Final Class, ECE472 Midterm #2 due today – 1-5% extra credit for written report of Dally’s video Oral presentation of class project: today Graduate students:

ISC’11 | Hamburg, Germany | June 19 – June 23, 2011 | Frühjahrstreffen des ZKI-Arbeitskreises "Supercomputing“ Dr. Horst Gietl.

Evaluating GPU Passthrough in Xen for High Performance Cloud Computing Andrew J. Younge 1, John Paul Walters 2, Stephen P. Crago 2, and Geoffrey C. Fox.

Introduction CS 524 – High-Performance Computing.

On the Integration and Use of OpenMP Performance Tools in the SPEC OMP2001 Benchmarks Bernd Mohr 1, Allen D. Malony 2, Rudi Eigenmann 3 1 Forschungszentrum.

Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA U N C L A S S I F I E D Slide 1 Exascale? No problem! Paul Henning.

What is X10? X10 is a Java-like language being developed by IBM Research focusing on high-productivity and high performance support for programming multi-core,

CS 732: Advance Machine Learning Usman Roshan Department of Computer Science NJIT.

Undergraduate Poster Presentation Match 31, 2015 Department of CSE, BUET, Dhaka, Bangladesh Wireless Sensor Network Integretion With Cloud Computing H.M.A.

ORNL is managed by UT-Battelle for the US Department of Energy Data Management User Guide Suzanne Parete-Koon Oak Ridge Leadership Computing Facility.

Project Proposal (Title + Abstract) Due Wednesday, September 4, 2013.

Agenda What is Google Summer of Code ? What are the goals of the program ? How does GSoC work ? Google Summer of Code timeline Student stipends Participating.

Slide 1 Auburn University Computer Science and Software Engineering Scientific Computing in Computer Science and Software Engineering Kai H. Chang Professor.

HPC Technology Track: Foundations of Computational Science Lecture 2 Dr. Greg Wettstein, Ph.D. Research Support Group Leader Division of Information Technology.

Introduction to Computers

The iPlant Collaborative Community Cyberinfrastructure for Life Science Tools and Services Workshop Objectives.

Computer Science 1MD3 Introduction to Programming

4.2.1 Programming Models Technology drivers – Node count, scale of parallelism within the node – Heterogeneity – Complex memory hierarchies – Failure rates.

Simulation with Open Source Physics Butch DeBerry Advisor: Dr. Bruce Mason.

Jeff Marino & Ron Reed. Main Concepts Object-oriented programming is programming that is based on using premade objects and writing code for the objects.

NIH Resource for Biomolecular Modeling and Bioinformatics Beckman Institute, UIUC NAMD Development Goals L.V. (Sanjay) Kale Professor.

NIH Resource for Biomolecular Modeling and Bioinformatics Beckman Institute, UIUC NAMD Development Goals L.V. (Sanjay) Kale Professor.

Jaguar/JaguarPF Optimized Library Interface (JOLI) Yashema Mack Florida Agricultural & Mechanical University Dr. Rebecca Hartman-Baker National Center.

Numerical Libraries Project Microsoft Incubation Group Mary Beth Hribar Microsoft Corporation CSCAPES Workshop June 10, 2008 Copyright Microsoft Corporation,

GSoC March Generally Successful owing-to Communication: ns-3 Experiences with GSoC Craig Dowell University of Washington Google SoC Infosession March.

CEA DSM Irfu IRFU site report. CEA DSM Irfu HEPiX Fall 0927/10/ Computing centers used by IRFU people IRFU local computing IRFU GRIF sub site Windows.

Experts in numerical algorithms and HPC services Compiler Requirements and Directions Rob Meyer September 10, 2009.

HPC Platform Futures John Vert HPC Development Manager Microsoft Corporation.

MESQUITE: Mesh Optimization Toolkit Brian Miller, LLNL

ICT-enabled Agricultural Science for Development Scenarios, Opportunities, Issues by ICTs transforming agricultural science, research & technology generation.

TEMPLATE DESIGN © BOINC: Middleware for Volunteer Computing David P. Anderson Space Sciences Laboratory University of.

Breakout Group: Debugging David E. Skinner and Wolfgang E. Nagel IESP Workshop 3, October, Tsukuba, Japan.

Using Charm++ to Mask Latency in Grid Computing Applications Gregory A. Koenig Parallel Programming Laboratory Department.

B5: Exascale Hardware. Capability Requirements Several different requirements –Exaflops/Exascale single application –Ensembles of Petaflop apps requiring.

Contemporary Languages in Parallel Computing Raymond Hummel.

Xolotl: A New Plasma Facing Component Simulator Scott Forest Hull II Jr. Software Developer Oak Ridge National Laboratory

Managed by UT-Battelle for the Department of Energy 1 Decreasing the Artificial Attenuation of the RCSIM Radio Channel Simulation Software Abigail Snyder.

ORNL is managed by UT-Battelle for the US Department of Energy Using Darshan on Titan Verónica G. Vergara Larrea OLCF Users Conference Call August 26,

John Demme Simha Sethumadhavan Columbia University.

Tools for Portals, Search, Assimilation, Provenance Computing Infrastructure for Science Individual University and Lab PIs National and Int’l collabs Research.

Fermi National Accelerator Laboratory & Thomas Jefferson National Accelerator Facility SciDAC LQCD Software The Department of Energy (DOE) Office of Science.

University GPU Club Tues 29 Oct

Integrating Engineering NASA SMD Education Community Meeting Sept , 2015.

11 Brian Van Straalen Portable Performance Discussion August 7, FASTMath SciDAC Institute.

Defining the Competencies for Leadership- Class Computing Education and Training Steven I. Gordon and Judith D. Gardiner August 3, 2010.

1 Panel on Merge or Split: Mutual Influence between Big Data and HPC Techniques IEEE International Workshop on High-Performance Big Data Computing In conjunction.

Geoffrey Fox Panel Talk: February

Panel: Beyond Exascale Computing

Volunteer Computing for Science Gateways

Status and Challenges: January 2017

Quick one: Do you know what these are?

NSF start October 1, 2014 Datanet: CIF21 DIBBs: Middleware and High Performance Analytics Libraries for Scalable Data Science Indiana University.

Three Questions To Ask About Clusters

3.2 Virtualisation.

NSF : CIF21 DIBBs: Middleware and High Performance Analytics Libraries for Scalable Data Science PI: Geoffrey C. Fox Software: MIDAS HPC-ABDS.

Toward a Unified HPC and Big Data Runtime

Tutorial Overview February 2017

Martin Swany Gregor von Laszewski Thomas Sterling Clint Whaley

Jeff Plewak Robin Sachdev

SCIENCE UNIT #4 Conservation of Energy

בארגונים במוסדות ובחברה

Department of Intelligent Systems Engineering

Architecture & System Performance

$1M a year for 5 years; 7 institutions Active:

BETONLINEBETONLINE A·+A·+

System Programming By Prof.Naveed Zishan.

Presentation transcript:

1Managed by UT-Battelle for the U.S. Department of Energy Discussion questions from you 1.Do we care about exaflops machines? 2.How are we going to compare performance? Reference system? 3.How would you use an exaflop machine? 4.How would you analyze your results? 5.Who is willing to contribute time to mentor other MD+GPU coders?

2Managed by UT-Battelle for the U.S. Department of Energy Community 1.How can our community better leverage each others’ work? 2.What about common libraries? OpenMM? 3.More workshops? Open-source code? Sharing of lessons- learned?

3Managed by UT-Battelle for the U.S. Department of Energy Hardware 1.Would you rather have: a)A tightly-coupled exascale machine? b)10 exaflops available to you in the cloud? c)1 petaflops available to you in your very tightly-coupled desktop machine? 2.Which model will be the best for biomolecular simulations of the future? 3.How would you effectively utilize an exascale machine for biomolecular simulation (to do real science)?

4Managed by UT-Battelle for the U.S. Department of Energy Software 1.What are the most important “tricks” that GPU+MD developers should know? 2.What will be the next disruptive technology change that will impact MD simulation?

5Managed by UT-Battelle for the U.S. Department of Energy Programming languages John Levesque suggests that OpenMP will displace CUDA, OpenCL, and MPI-everywhere in the future. Do you agree? Why or why not? What is “wrong” with MPI between the nodes and OpenMP on the node?