Computing as Fast as an Engineer can Think

Slides:

Advertisements

Similar presentations

Models of Computation Prepared by John Reif, Ph.D. Distinguished Professor of Computer Science Duke University Analysis of Algorithms Week 1, Lecture 2.

Advertisements

Enhanced matrix multiplication algorithm for FPGA Tamás Herendi, S. Roland Major UDT2012.

Algorithms An algorithm is a finite sequence of instructions, logic, an explicit step-by-step procedure for solving a problem. Specific algorithms sometimes.

Chapter 8 Elliptic Equation.

HPC - High Performance Productivity Computing and Future Computational Systems: A Research Engineer’s Perspective Dr. Robert C. Singleterry Jr. NASA Langley.

NASA High Performance Computing (HPC) Directions, Issues, and Concerns: A User’s Perspective Dr. Robert C. Singleterry Jr. NASA Langley Research Center.

A Batch-Language, Vector-Based Neural Network Simulator Motivation: - general computer languages (e.g. C) lead to complex code - neural network simulators.

CS 197 Computers in Society History of Computing.

MA5233: Computational Mathematics

Chapter 01 Introduction Chapter 0 Introduction. Chapter 02 History of Computing - Early Computers Abacus (ancient orient, still in use) Slide rule (17C,

ECIV 301 Programming & Graphics Numerical Methods for Engineers Lecture 4 Programming and Software EXCEL and MathCAD.

Computers in Society History of Computing. Homework Assignment #3 is ready to go – let’s have a look. Questions about HW1? More people to schedule for.

Lecture 14 Go over midterm results Algorithms Efficiency More on prime numbers.

8. Geometric Operations Geometric operations change image geometry by moving pixels around in a carefully constrained way. We might do this to remove distortions.

Hypercomputing With the CORDIC Algorithm

Weak Formulation ( variational formulation)

Bioinformatics Tool Development Dong Xu Computer Science Department 109 Engineering Building West

FPGA Based Fuzzy Logic Controller for Semi- Active Suspensions Aws Abu-Khudhair.

1 The Spectral Method. 2 Definition where (e m,e n )=δ m,n e n = basis of a Hilbert space (.,.): scalar product in this space In L 2 space where f * :

Computer Architecture Computational Models Ola Flygt V ä xj ö University

1 Miodrag Bolic ARCHITECTURES FOR EFFICIENT IMPLEMENTATION OF PARTICLE FILTERS Department of Electrical and Computer Engineering Stony Brook University.

Time Integration Utilities on an FPGA Cris A. Kania with Olaf O. Storaasli, Ph. D. NASA Langley.

Introduction to Numerical Methods for ODEs and PDEs Methods of Approximation Lecture 3: finite differences Lecture 4: finite elements.

Engineering Applications on

©Brooks/Cole, 2003 Foundations of Computer Science from Data Manipulation to Theory of Computation Behrouz A. Forouzan, Brooks/Cole — Thomson Learning,

Computing Faster Without CPUs GOAL: Evaluate FPGA*-based Hypercomputer Potential for NASA Scientific Computations * Field-Programmable Gate Array (e.g.

Software Basics. Some Pioneers Charles Babbage Analytical Engine Countess Ada Lovelace First Programmer ? John Von Neumann storing instructions in memory.

Storaasli 5/9/03 Analytical and Computational Methods Computing Faster without CPUs Scientific Applications on FPGA-based* Reconfigurable Hypercomputers.

Lecture 13: Logic Emulation October 25, 2004 ECE 697F Reconfigurable Computing Lecture 13 Logic Emulation.

MECH345 Introduction to Finite Element Methods Chapter 1 Numerical Methods - Introduction.

Engineering Analysis – Computational Fluid Dynamics –

CprE / ComS 583 Reconfigurable Computing Prof. Joseph Zambreno Department of Electrical and Computer Engineering Iowa State University Lecture #12 – Systolic.

The Third Way: Neither Hardware Nor Software Gordon Brebner Division of Informatics University of Edinburgh.

CS 420 Design of Algorithms Parallel Algorithm Design.

Computer Engineering Rabie A. Ramadan Lecture 2. Table of Contents 2 Architecture Development and Styles Performance Measures Amdahl’s Law.

Flowcharts C++ Lab. Algorithm An informal definition of an algorithm is: a step-by-step method for solving a problem or doing a task. Input data A step-by-step.

The Principles… Make it BIG: Arial 12 is too small Arial 24 is better, Arial are just the size Make it BIG test, look at it from 2 meters away.

KERRY BARNES WILLIAM LUNDGREN JAMES STEED

Drexel University Department of Electrical and Computer Engineering Open Design and Integration Environment.

Solving Ordinary Differential Equations

Chapter I: Introduction to Computer Science. Computer: is a machine that accepts input data, processes the data and creates output data. This is a specific-purpose.

University of Utah Introduction to Electromagnetics Lecture 14: Vectors and Coordinate Systems Dr. Cynthia Furse University of Utah Department of Electrical.

CPE 332 Computer Engineering Mathematics II Part III, Chapter 11 Numerical Differentiation and Integration Numerical Differentiation and Integration.

Electrical Engineering

ELEC 7770 Advanced VLSI Design Spring 2016 Introduction

You have 10 seconds to answer the following question…….

A Methodology for System-on-a-Programmable-Chip Resources Utilization

Parallel Algorithm Design using Spectral Graph Theory

ELEC 7770 Advanced VLSI Design Spring 2014 Introduction

Centar ( Global Signal Processing Expo

Simulation at NASA for the Space Radiation Effort

ELEC 7770 Advanced VLSI Design Spring 2012 Introduction

What is the future of applied mathematics? Chris Budd.

کاربرد موجک در تقریب توابع یک بعدی و حل معادلات دیفرانسیل معمولی

ELEC 7770 Advanced VLSI Design Spring 2010 Introduction

NUMERICAL INTEGRATION

VHDL Introduction.

,. . ' ;; '.. I I tI I t : /..: /.. ' : ····t I 'h I.;.; '..'.. I ' :".:".

Technology History - Goal: To make human tasks easier

Ordinary differentiall equations

COT 6200 Quantum Computing Fall 2010

Objective: To know the equations of simple straight lines.

Parallel Circuits 119.

CPE 332 Computer Engineering Mathematics II

6th Lecture : Numerical Methods

Chapter 0 Introduction Introduction Chapter 0.

EE 616 Computer Aided Analysis of Electronic Networks Lecture 12

Programmable logic and FPGA

Objective: To know the equations of simple straight lines.

Presentation transcript:

Computing as Fast as an Engineer can Think Robert C. Singleterry Jr. Olaf O. Storaasli Analytical and Computational Methods Branch Structures and Materials

How to Program Reconfigurable Computers? Data Flow Programming Style Must Think “Inherently Parallel” Graphical Based “Language” Everything Tied to Clock Signals No Von Neumann Bottlenecks Programming Power Tied to Number of Gates or Area (Number) of FPGAs 10/27/2019 Reconfigurable Computers

Reconfigurable Computers Dot Product Example 10/27/2019 Reconfigurable Computers

Integration Algorithm: Old Idea Simpson’s Rule Simple Straight forward Problem Not an inherently parallel algorithm Procedure based algorithm 10/27/2019 Reconfigurable Computers

Reconfigurable Computers Integration: New Idea a b First Step a b Second Step a b Third Step 10/27/2019 Reconfigurable Computers

Reconfigurable Computers Benchmarking Initial Investigation Benchmarks Dot Product Integration Matrix Solution ODE and PDE Solutions Differencing Finite elements Integral Methods 10/27/2019 Reconfigurable Computers