1 WRB 09/02 HPEC Lincoln Lab Sept 2002 Poster B: Software Technologies andSystems W. Robert Bernecky Naval Undersea Warfare Center Ph: (401) 832-8171 Fax:

Slides:



Advertisements
Similar presentations
Embedded System Lab. What is an embedded systems? An embedded system is a computer system designed for specific control functions within a larger system,
Advertisements

Master/Slave Architecture Pattern Source: Pattern-Oriented Software Architecture, Vol. 1, Buschmann, et al.
10 REASONS Why it makes a good option for your DB IN-MEMORY DATABASES Presenter #10: Robert Vitolo.
Sensor Network Platforms and Tools
Overview: Chapter 7  Sensor node platforms must contend with many issues  Energy consumption  Sensing environment  Networking  Real-time constraints.
Real-Time Video Analysis on an Embedded Smart Camera for Traffic Surveillance Presenter: Yu-Wei Fan.
Chapter 13 Embedded Systems
Chapter 13 Embedded Systems Patricia Roy Manatee Community College, Venice, FL ©2008, Prentice Hall Operating Systems: Internals and Design Principles,
IBM RS6000/SP Overview Advanced IBM Unix computers series Multiple different configurations Available from entry level to high-end machines. POWER (1,2,3,4)
Analysis of power dissipation in embedded systems using real-time operating systems Dick, R.P. Lakshminarayana, G. Raghunathan, A. Jha, N.K. Dept. of Electr.
1 Multi - Core fast Communication for SoPC Multi - Core fast Communication for SoPC Technion – Israel Institute of Technology Department of Electrical.
1 Dr. Frederica Darema Senior Science and Technology Advisor NSF Future Parallel Computing Systems – what to remember from the past RAMP Workshop FCRC.
Generic Sensor Platform for Networked Sensors Haywood Ho.
Chapter 13 Embedded Systems
MEMS for Real time applications On Board diagnostics 6 to 10 PC workstations with Windows/Linux OS DSP Boards, Microcontroller Boards Director: Professor.
CS 441: Charles Durran Kelly.  What are Wireless Sensor Networks?  WSN Challenges  What is a Smartphone Sensor Network?  Why use such a network? 
DCL Concepts STL Concepts ContainerIteratorAlgorithmFunctorAdaptor What New Concepts are Needed for a “DCL”? (Distributed Computing Library) Distributed.
Introduction to Embedded Development. What is an Embedded System ? An embedded system is a computer system embedded in a device with a dedicated function.
Dr. José M. Reyes Álamo 1.  Course website  Syllabus posted.
Course Outline DayContents Day 1 Introduction Motivation, definitions, properties of embedded systems, outline of the current course How to specify embedded.
EMBEDDED SYSTEMS G.V.P.COLLEGE OF ENGINEERING Affiliated to J.N.T.U. By By D.Ramya Deepthi D.Ramya Deepthi & V.Soujanya V.Soujanya.
RSC Williams MAPLD 2005/BOF-S1 A Linux-based Software Environment for the Reconfigurable Scalable Computing Project John A. Williams 1
Lecture 4: Parallel Programming Models. Parallel Programming Models Parallel Programming Models: Data parallelism / Task parallelism Explicit parallelism.
1 Developing Native Device for MPJ Express Advisor: Dr. Aamir Shafi Co-advisor: Ms Samin Khaliq.
CASTNESS‘11 Computer Architectures and Software Tools for Numerical Embedded Scalable Systems Workshop & School: Roma January 17-18th 2011 Frédéric ROUSSEAU.
 What is an operating system? What is an operating system?  Where does the OS fit in? Where does the OS fit in?  Services provided by an OS Services.
ICOM 5995: Performance Instrumentation and Visualization for High Performance Computer Systems Lecture 7 October 16, 2002 Nayda G. Santiago.
Brussels, 1 June 2005 WP Strategic Objective Embedded Systems Tom Bo Clausen.
NSF Critical Infrastructures Workshop Nov , 2006 Kannan Ramchandran University of California at Berkeley Current research interests related to workshop.
A Comparison of Java RMI, CORBA, and Web Services Technologies for Distributed SIP Applications Mark D. Hanes Stanley C. Ahalt Ashok K. Krishnamurthy Department.
Distributed Computation in MANets Robot swarm developed by James Rice University.
Extreme scale parallel and distributed systems – High performance computing systems Current No. 1 supercomputer Tianhe-2 at petaflops Pushing toward.
BLU-ICE and the Distributed Control System Constraints for Software Development Strategies Timothy M. McPhillips Stanford Synchrotron Radiation Laboratory.
Performance Model & Tools Summary Hung-Hsun Su UPC Group, HCS lab 2/5/2004.
4.2.1 Programming Models Technology drivers – Node count, scale of parallelism within the node – Heterogeneity – Complex memory hierarchies – Failure rates.
Cousins HPEC 2002 Session 4: Emerging High Performance Software David Cousins Division Scientist High Performance Computing Dept. Newport,
Introduction Infrastructure for pervasive computing has many challenges: 1)pervasive computing is a large aspect which includes hardware side (mobile phones,portable.
PART II OPERATING SYSTEMS LECTURE 8 SO TAXONOMY Ştefan Stăncescu 1.
May 16-18, Skeletons and Asynchronous RPC for Embedded Data- and Task Parallel Image Processing IAPR Conference on Machine Vision Applications Wouter.
Application of Operating System Concepts to Coordination in Pervasive Sensing and Computing Systems Benjamin J. Ewy, Larry M. Sanders Ambient Computing,
Summary Background –Why do we need parallel processing? Moore’s law. Applications. Introduction in algorithms and applications –Methodology to develop.
Improving I/O with Compiler-Supported Parallelism Why Should We Care About I/O? Disk access speeds are much slower than processor and memory access speeds.
A Systematic Approach to the Design of Distributed Wearable Systems Urs Anliker, Jan Beutel, Matthias Dyer, Rolf Enzler, Paul Lukowicz Computer Engineering.
Chapter 1 — Computer Abstractions and Technology — 1 Below Your Program Application software – Written in high-level language System software – Compiler:
Computer Science 340 Software Design & Testing Software Architecture.
Chapter 1 Basic Concepts of Operating Systems Introduction Software A program is a sequence of instructions that enables the computer to carry.
Real-time Embedded System Lab, ASU WCAE_panel_ 1 Panel on Panel on Teaching Embedded Systems Yann-Hang Lee and Aung Oo Computer Science and Engineering.
High Performance Flexible DSP Infrastructure Based on MPI and VSIPL 7th Annual Workshop on High Performance Embedded Computing MIT Lincoln Laboratory
Software Systems Division (TEC-SW) ASSERT process & toolchain Maxime Perrotin, ESA.
From Use Cases to Implementation 1. Structural and Behavioral Aspects of Collaborations  Two aspects of Collaborations Structural – specifies the static.
MIT Lincoln Laboratory 1 of 4 MAA 3/8/2016 Development of a Real-Time Parallel UHF SAR Image Processor Matthew Alexander, Michael Vai, Thomas Emberley,
What is Cloud Computing? Irving Wladawsky-Berger.
Venu Veeravalli ECE Dept and Coordinated Science Lab University of Illinois at Urbana-Champaign
Embedded System Design and Development Introduction to Embedded System.
From Use Cases to Implementation 1. Mapping Requirements Directly to Design and Code  For many, if not most, of our requirements it is relatively easy.
HPEC-1 SMHS 7/7/2016 MIT Lincoln Laboratory Focus 3: Cell Sharon Sacco / MIT Lincoln Laboratory HPEC Workshop 19 September 2007 This work is sponsored.
Embedded Systems and Real-Time Programming Niklaus Wirth
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING CLOUD COMPUTING
Morgan Kaufmann Publishers
Multi-Processing in High Performance Computer Architecture:
Green Software Engineering Prof
Multi-Processing in High Performance Computer Architecture:
The Extensible Tool-chain for Evaluation of Architectural Models
Multi-Agent Testbed for Emerging Power Systems
ECE 477 Senior Design Group 1  Fall 2006
Hybrid Programming with OpenMP and MPI
Welcome to the FPGA Tools Course Agenda
Introduction and History
Parallel I/O for Distributed Applications (MPI-Conn-IO)
From Use Cases to Implementation
Presentation transcript:

1 WRB 09/02 HPEC Lincoln Lab Sept 2002 Poster B: Software Technologies andSystems W. Robert Bernecky Naval Undersea Warfare Center Ph: (401) Fax: (401) High Performance Embedded Computing Workshop ‘02

2 WRB 09/02 HPEC Lincoln Lab Sept 2002 Software Technologies Dealing with Complexity Software Tools –Map software components to hardware Task mapping cache optimization power consumption –Analyze system performance Flops, Memory, Power, Heat, I/O Bandwidth –Ensure system availability High availability Issues –Availability of tool –Ease of use

3 WRB 09/02 HPEC Lincoln Lab Sept 2002 Programmer Productivity High-Level Languages –Matlab Portability –Capture previous-generation software –VSIPL –Message Passing Interface (MPI) –Middle ware Issue –Program Efficiency % of computational resources used –Often, only 5% to 10%

4 WRB 09/02 HPEC Lincoln Lab Sept 2002 Software Infrastructure Embedded and Distributed Operating Systems Real-time Operating System –Real-Time Linux

5 WRB 09/02 HPEC Lincoln Lab Sept 2002 Sensor Networks Real-time sensors Distributed Wireless Dynamic topology

6 WRB 09/02 HPEC Lincoln Lab Sept 2002 The Ideal Software Technology Easy to use Supports large systems Optimizes across multiple constraints Produces “hand-tuned” performance Portable to next-generation hardware Low cost