Modeling and Simulation for Architecture: Breakout Arun R. Krste A. Dave M. Doe H.Y. Derek C. Lizy J. Kevin L. Dean K. Karen B. Shekhar B. Mike P. Chris.

Slides:



Advertisements
Similar presentations
Operating Systems Components of OS
Advertisements

Systems Engineering From a Life Cycle Perspective John Groenenboom Director Engineering – Mesa Boeing Rotorcraft Dec 12, 2007.
DELOS Highlights COSTANTINO THANOS ITALIAN NATIONAL RESEARCH COUNCIL.
Emmett Witchel Krste Asanović MIT Lab for Computer Science Hardware Works, Software Doesn’t: Enforcing Modularity with Mondriaan Memory Protection.
© Chinese University, CSE Dept. Software Engineering / Software Engineering Topic 1: Software Engineering: A Preview Your Name: ____________________.
CS 325: Software Engineering January 13, 2015 Introduction Defining Software Engineering SWE vs. CS Software Life-Cycle Software Processes Waterfall Process.
Priority Research Direction: Portable de facto standard software frameworks Key challenges Establish forums for multi-institutional discussions. Define.
*time Optimization Heiko, Diego, Thomas, Kevin, Andreas, Jens.
How to: Design and Develop an Application to Ensure its Quality James Hippolite Senior.NET Developer Telecom New Zealand Limited James Hippolite Senior.NET.
Tier 1 Breakout Topics How to study a 100,000-core system (yes that is 100K) using RAMP technologies? Krste What "great" research questions can RAMP help.
Copyright  1999 Daniel D. Gajski IP – Based Design Methodology Daniel D. Gajski University of California
CAD and Design Tools for On- Chip Networks Luca Benini, Mark Hummel, Olav Lysne, Li-Shiuan Peh, Li Shang, Mithuna Thottethodi,
5 th Biennial Ptolemy Miniconference Berkeley, CA, May 9, 2003 MESCAL Application Modeling and Mapping: Warpath Andrew Mihal and the MESCAL team UC Berkeley.
IBM T.J. Watson Research Center & Northwestern University © 2006 IBM Corporation Bin Lin Department of Electrical Engineering & Computer Science, Northwestern.
1 Embedded Computer System Laboratory RTOS Modeling in Electronic System Level Design.
Enterprise Architecture
4.x Performance Technology drivers – Exascale systems will consist of complex configurations with a huge number of potentially heterogeneous components.
1 Portfolio Management – Agile How to plan like a VP Highsmith, Ch 12 CSSE579 Session 6 Part 2 One company’s software product portfolio.
IEBC Sunkosi Webinar © 2015 All rights reserved. Successfully Implementing Your Student Success Plans Ensuring The Success Of Well Managed Interventions.
1/19 Component Design On-demand Learning Series Software Engineering of Web Application - Principles of Good Component Design Hunan University, Software.
Design Space Exploration
1 Operations Research Consulting Solving complex business problems for fun and profit Harlan Crowder Principal Dieselbrain Partners
Exploring Multi-Threaded Java Application Performance on Multicore Hardware Ghent University, Belgium OOPSLA 2012 presentation – October 24 th 2012 Jennifer.
Business Analysis and Essential Competencies
Equipment Capability Customer RIGHT KIT, RIGHT PRICE, RIGHT TIME The role of OA in experimentation? Dave Ferbrache Director Analysis, Experimentation &
STORAGE ARCHITECTURE/ EXECUTIVE: Virtualization It’s not what you think you’re buying. John Blackman Independent Storage Consultant.
Extreme Makeover for EDA Industry
Virtualization: Not Just For Servers Hollis Blanchard PowerPC kernel hacker.
Role-Based Guide to the RUP Architect. 2 Mission of an Architect A software architect leads and coordinates technical activities and artifacts throughout.
Managing an Enterprise GIS Project: Key Things You Need Right from the Start Gerry Clancy Glenn Berger.
High Performance Embedded Computing © 2007 Elsevier Lecture 3: Design Methodologies Embedded Computing Systems Mikko Lipasti, adapted from M. Schulte Based.
System Design with CoWare N2C - Overview. 2 Agenda q Overview –CoWare background and focus –Understanding current design flows –CoWare technology overview.
High Performance Embedded Computing © 2007 Elsevier Chapter 1, part 2: Embedded Computing High Performance Embedded Computing Wayne Wolf.
9/20/6Lecture 3 - Instruction Set - Al1 Program Design.
4.2.1 Programming Models Technology drivers – Node count, scale of parallelism within the node – Heterogeneity – Complex memory hierarchies – Failure rates.
Copyright John C. Knight SOFTWARE ENGINEERING FOR DEPENDABLE SYSTEMS John C. Knight Department of Computer Science University of Virginia.
1 Introduction to Middleware. 2 Outline What is middleware? Purpose and origin Why use it? What Middleware does? Technical details Middleware services.
© 2012 xtUML.org Bill Chown – Mentor Graphics Model Driven Engineering.
CHAPTER 6 - MODELING ANH AU. BACKGROUND Architectural model – an artifact that captures some or all of the design decisions that comprise a system’s architecture.
ICS-FORTH 25-Nov Infrastructure for Scalable Services Are we Ready Yet? Angelos Bilas Institute of Computer Science (ICS) Foundation.
Issues Autonomic operation (fault tolerance) Minimize interference to applications Hardware support for new operating systems Resource management (global.
The GriPhyN Planning Process All-Hands Meeting ISI 15 October 2001.
Infrastructure & Methodology (The cool group). Problem space What is “self-management” anyway? –Defined broadly - anything that does not require (or reduces)
Seeking SC Feedback on Draft Technology Strategy and Roadmap for EarthCube Draft of 3 November 2015 The Technology and Architecture Committee (TAC) Chairs:
1 Copyright  2001 Pao-Ann Hsiung SW HW Module Outline l Introduction l Unified HW/SW Representations l HW/SW Partitioning Techniques l Integrated HW/SW.
Architecture View Models A model is a complete, simplified description of a system from a particular perspective or viewpoint. There is no single view.
Breakout Group: Debugging David E. Skinner and Wolfgang E. Nagel IESP Workshop 3, October, Tsukuba, Japan.
Data Center & Large-Scale Systems (updated) Luis Ceze, Bill Feiereisen, Krishna Kant, Richard Murphy, Onur Mutlu, Anand Sivasubramanian, Christos Kozyrakis.
Introduction Why are virtual machines interesting?
Rational Unified Process (RUP)
Abstractions Abstractions for: – Architectures – Applications – Are others: Runtime environment, … ??? Do they depend on the metrics of interest? – (Performance,
SAS_08_ Architecture_Analysis_of_Evolving_Complex_Systems_of_Systems_Lindvall Architecture Analysis of Evolving Complex Systems of Systems Executive Status.
What’s Ahead for Embedded Software? (Wed) Gilsoo Kim
Virtual Collaborative Social Living Community for Elderly Kick Off Event WP2 Overview Instituto Pedro Nunes Co-Living 12/3/ Paulo Freitas - Instituto.
Guru Parulkar CISE/NSF How can Great Plains Region Contribute to GENI and FIND?
Group #3: Mobility Models and Mobile Testbeds. The Models Motion, Traffic, Network.
CPSC 872 John D. McGregor Session 31 This is it..
The Post Windows Operating System
Structural Simulation Toolkit / Gem5 Integration
Hierarchical Architecture
IP – Based Design Methodology
Systems Engineering for Mission-Driven Modeling
Multi Core Processing What is term Multi Core?.
Panel on Representative Projects
Design Yaodong Bi.
TensorFlow: A System for Large-Scale Machine Learning
Lecture 1 Class Overview
Presentation transcript:

Modeling and Simulation for Architecture: Breakout Arun R. Krste A. Dave M. Doe H.Y. Derek C. Lizy J. Kevin L. Dean K. Karen B. Shekhar B. Mike P. Chris C. Jim K. John H. Sudhakar Y. Luiz C. Steve R. Wilf P. Jim K.. Participants Moderator and Scribe Darren K. and Arun R.

High level Lots of discussion about the SW Issues & Apps Major concern on interaction & interfaces – between communities – “common language” Good at iterative development – Need good starting points – Need an informed path Lots of discussion of HW Design space – Caution over multiple metrics – Know performance well – Weaker on power – don’t know about reliability – Cost very hard, but very important “Cultural” Barriers & IP Issues

1. Object of Modeling: What to Model Goal: “Make Design Decisions” – Gain Insight – “Common Language” “Shared Testbed” Need to Support Co-design Loop – Arch. want Application models – Apps. want Architecture models Abstraction is needed to deal with Complexity Different goals for different times/audiences – Design exploration in terms of power, performance, reliability, and cost – Design validation – SW development Lots of parameters in the design space

2. Can we do it now Good at iterative refinement Lots of discussion on need for abstract model w/ parameters & trend lines (abstract machine model) – Iteratively approaches – Iterative series of definitions (multiple scopes, levels of abstraction) – Good at evolutionary approaches – captures key parameters – capture disruptive changes – Correct abstractions are CRITICAL Caution: radical changes make things difficult, uncertain – Hard to jump 10+ years out

3. Gaps Some research gaps, some interactional gaps “Cultural Barriers” – IP: what is precompetitive? what can we share? – App. vs. HW vs. compiler vs. OS etc... Skeleton Applications & Skeleton Architectures – Multiple levels – Correct abstractions – Not assume a single execution model Need way to interact between HW & SW Fidelity vs. Time vs. Scale tradeoffs (decomposability) Methodology – What scale? what abstractions? – Need community consensus of what is needed Roadmap of Modeling capabilities

Gaps (cont.) Infrastructure – Technology models – Lots of discussion for tech. models for disruptive technologies and how we trust them Modeling Testbed – Bring together architecture & application Multiple levels of abstraction w/ Technology Modeling Resources – Access to state of art machines for simulation – Access to state of art machines for validation

4. Community of Interaction Application Teams (Co-Design Centers) – Also, OS, Runtime, Compiler Different facets within architecture teams – Memory – Processor – Network – Device-level & High level Need lots of cross-cutting interaction

5. Measure for Success #1: No Surprises in Deployed Machine Infrastructure is available, used, and broadly accepted Influence is demonstrated – Impact of methodology is demonstrated – We know which gaps we filled