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The Ultimate SuperComputer-on-a-Chip for Massive Big Data and Highly Iterative Algorithms
Online Presentations | 10 Apr 2024 | Contributor(s):: Veljko M. Milutinovic
ECE 606: Solid State Devices I - Guest LectureThis presentation analyses the essence of DataFlow SuperComputing, defines its advantages and sheds lighton the related programming model.DataFlow computers, compared to ControlFlow computers, offer speedups of 20 to 200 (even 2000 for some...
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Designing Machine Learning Surrogates for Molecular Dynamics Simulations
Online Presentations | 25 Nov 2021 | Contributor(s):: JCS Kadupitiya
Molecular dynamics (MD) simulations accelerated by high-performance computing (HPC) methods are powerful tools for investigating and extracting the microscopic mechanisms characterizing the properties of soft materials such as self-assembled nanoparticles, virus capsids, confined electrolytes,...
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Perspectives on High-Performance Computing in a Big Data World: Part D - Learning Model Details and Agent-Based Simulations
Online Presentations | 17 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture completes the discussion of MLforHPC. It covers Learning Model Details and Agents and Time-Series Case Studies.
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Perspectives on High-Performance Computing in a Big Data World: Part E - Challenges and Opportunities, Conclusions
Online Presentations | 17 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture covers the computer science issues raised in this talk. The conclusions note that HPDC/HPC is essential; it is good to work closely with industry with student Internships and Collaborations; the Global AI and Modeling Supercomputer GAIMSC is a good framework with an HPC Cloud linked...
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Perspectives on High-Performance Computing in a Big Data World: Part C - MLaroundHPDC/HPC and MLAutotuning
Online Presentations | 10 Oct 2019 | Contributor(s):: Fox, Geoffrey C.
This is the first part of the discussion of MLforHPC. It includes MLAutotuning (Using ML to configure or autotune ML or HPC simulations and MLaroundHPC (Learning outputs from inputs).
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Perspectives on High-Performance Computing in a Big Data World: Part B - More on the Evolution of Interests and Communities
Online Presentations | 30 Sep 2019 | Contributor(s):: Fox, Geoffrey C.
This part contains several topics. It discusses the importance of industry in several facets of the field: SysML conference, clouds, MLPerf, the Global AI Supercomputer. The nature of data science and data engineering jobs. We emphasize the need for HPC. We finish by introducing MLforHPC (AI for...
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Perspectives on High-Performance Computing in a Big Data World: Part A - Data on the Evolution of Interests and Communities
Online Presentations | 13 Aug 2019 | Contributor(s):: Fox, Geoffrey C.
This lecture has an overall outline of the 5 part presentation. It covers trends seen from conferences and journals -- the number of papers, attendees and h5index. Then we look at relevant Google Trends. Cyberinfrastructure related activities are less buoyant than those for AI and ML.
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How do we solve big science problems using all the modern tools and technologies at our fingertips?
Online Presentations | 06 Jul 2019 | Contributor(s):: Jeffrey A. Nichols
Exascale is on the horizon and ORNL just announced our next new system called Frontier to be delivered in 2021 – another order of magnitude more powerful! I will discuss the technologies used in Summit and Frontier.
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Non-Blocking Conjugate Gradient Methods for Extreme Scale Computing
Online Presentations | 07 Feb 2016 | Contributor(s):: Paul Eller
Many scientific and engineering applications use Krylov subspace methods to solve large systems of linear equations. For extreme scale parallel computing systems, the dot products in these methods (implemented using allreduce operations in MPI) can limit performance because they are a...
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Range Decomposition: A Low Communication Algorithm for Solving PDEs on Massively Parallel Machines
Online Presentations | 07 Feb 2016 | Contributor(s):: Tom Manteuffel
The Range Decomposition (RD) algorithm uses nested iteration and adaptive mesh refinement locally before performing a global communication step. Only several such steps are observed to be necessary before reaching a solution within a small multiple of discretization error. The target application...
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Understanding the Propagation of Silent Data Corruption in Algebraic Multigrid
Online Presentations | 04 Feb 2016 | Contributor(s):: Jon Calhoun
Sparse linear solvers from a fundamental kernel in high performance computing (HPC). Exascale systems are expected to be more complex than systems of today being composed of thousands of heterogeneous processing elements that operate at near-threshold-voltage to meet power constraints. The...
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A Performance Comparison of Algebraic Multigrid Preconditioners on GPUs and MIC
Online Presentations | 04 Feb 2016 | Contributor(s):: Karl Rupp
Algebraic multigrid (AMG) preconditioners for accelerators such as graphics processing units (GPUs) and Intel's many-integrated core (MIC) architecture typically require a careful, problem-dependent trade-off between efficient hardware use, robustness, and convergence rate in order to...
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A Massively Parallel Semicoarsening Multigrid for 3D Reservoir Simulation on Multi-core and Multi-GPU Architectures
Online Presentations | 04 Feb 2016 | Contributor(s):: Abdulrahman Manea
In this work, we have designed and implemented a massively parallel version of the Semicoarsening Black Box Multigrid Solver [1], which is capable of handling highly heterogeneous and anisotropic 3D reservoirs, on a parallel architecture with multiple GPU’s. For comparison purposes, the...
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HPGMG: Benchmarking Computers Using Multigrid
Online Presentations | 04 Feb 2016 | Contributor(s):: Jed Brown
HPGMG (https://hpgmg.org) is a geometric multigrid benchmark designed to measure the performance and versatility of computers. For a benchmark to be representative of applications, good performance on the benchmark should be sufficient to ensure good performance on most important applications and...
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Preparing for the Future of Computing: The DOE/ASCR Materials Co-Design Center
Online Presentations | 08 Apr 2015 | Contributor(s):: Jim Belak
The advent of Advanced / Additive Manufacturing and the Materials Genome Initiative has placed significant emphasis on accelerating the qualification of new materials for use in real applications. Within these workflows lies both the engineering scale qualification through building and testing...
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Advanced Parallel CPU Programming Part 1: OmpSs Quick Overview
Online Presentations | 29 Aug 2013 | Contributor(s):: NanoBio Node, Xavier Teruel
High Performance Computing --> Some basic concepts, Supercomputers nowadays, Parallel programming models OmpSs Introduction --> OmpSs main features, A Practical Example: Cholesky factorization BSC’s Implementation --> Mercurium Compiler, Nanos++ Runtime Library, Visualization Tools
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Introductory Parallel CPU Programming
Online Presentations | 23 Aug 2013 | Contributor(s):: Mark Bull
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Advanced Parallel CPU Programming Part 2: Fundamentals of OmpSs
Online Presentations | 21 Aug 2013 | Contributor(s):: Xavier Teruel
Tasking and Synchronization --> Data Sharing Attributes, Dependence Model, Other Tasking Directives Clauses, Taskwait, Synchronization, Outlined Task Syntax; Memory Regions, Nesting and Dependences --> Memory regions and dependences, Nested tasks and dependences, Using dependence sentinels;...
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Tutorial 4b: Introduction to the NEMO3D Tool - Electronic Structure and Transport in 3D
Online Presentations | 29 Mar 2011 | Contributor(s):: Gerhard Klimeck
Electronic Structure and Transport in 3D - Quantum Dots, Nanowires and Ultra-Thin Body Transistors
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Emerging Opportunities, Challenges, and Applications in Exascale Computing
Online Presentations | 10 Mar 2011 | Contributor(s):: Ananth Grama
The move towards exascale computing platforms (capable of 10^18 floating point operations) poses tremendous challenges, while presenting opportunities for foundational advances in a variety of application domains. In this talk, I will describe various technical issues that must be overcome to...